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Impacts of façade openings' geometry on natural ventilation and occupants’ perception: A review
Journal Pre-proof Impacts of façade openings’ geometry on natural ventilation and occupants’ perception: A review Nima Izadyar, Wendy Miller, Behzad Rismanchi, Veronica Garcia-Hansen PII:
S0360-1323(19)30826-1
DOI:
https://doi.org/10.1016/j.buildenv.2019.106613
Reference:
BAE 106613
To appear in:
Building and Environment
Received Date: 31 October 2019 Revised Date:
3 December 2019
Accepted Date: 18 December 2019
Please cite this article as: Izadyar N, W, B, Garcia-Hansen V, Impacts of façade openings’ geometry on natural ventilation and occupants’ perception: A review, Building and Environment, https:// doi.org/10.1016/j.buildenv.2019.106613. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Ltd. All rights reserved.
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Impacts of façade openings’ geometry on natural ventilation and occupants’ perception:
2
A review
3
Nima Izadyar a, Wendy Miller a,*, Behzad Rismanchi b, Veronica Garcia-Hansen c a
4 5 b
6 7 c
Energy and Process Engineering, Science and Engineering Faculty, School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, Brisbane, QLD, Australia
Renewable Energy and Energy Efficiency Group, Department of Infrastructure Engineering, Melbourne School of Engineering, The University of Melbourne, Victoria, 3010, Australia
8 9 10 11 12 13 14
*Corresponding author email: School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, PO Box 2434, Brisbane, Queensland 4001, Australia. Phone and Fax: +61 7 3138 9126 Email: [email protected]
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Abstract
16
For centuries, natural ventilation (NV) was the smartest technique for conditioning the built
17
environment. However, in modern design, NV has not been utilised to its full potential, especially in
18
high-rise and medium-rise buildings. One of the remaining options is the application of balconies to
19
guide the airflow into the space to moderate the indoor ambient, increase the thermal comfort, and
20
reduce the need for mechanical ventilation. This article investigates literature reporting the impacts of
21
façade openings, particularly balcony, geometry on NV performance and occupants’ perception. It
22
aims to identify to what extent balconies have been considered as an NV strategy and to identify
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research gaps in this field. This review article compared and classified different geometries’ design
24
features based on their effects on NV performance. This review paper also scrutinised the socio-
25
technical impacts of designing façade opening via Post-occupancy Evaluation (POE) methods. The
26
authors believe the POE could be the missing links between designing for NV and occupants’
27
perception. The review outcome found that most of the available literature is carried out in case
28
studies and regions with warm or hot climates that are cooling dominant. The increasing occurrence
29
of heat waves or prolonged summer overheating in buildings in traditionally heating-dominated
30
climates, however, suggests the need for research to evaluate both the technical and socio-technical
31
parameters of balcony geometry for these climates as well.
32
Keywords: Balcony; Design; Façade opening; Geometry; Natural ventilation (NV)
School of Design, Creative Industries Faculty, Queensland University of Technology (QUT), Brisbane 4001, Australia
1
Abbreviations ACH ASHRAE BDS BUS CV D DSF FEM FM GHG H/D HSI HVAC IAD IAV IAQ IEQ IES-VE IDA ICE ISO L LES MAA
Air Change per Hour American Society of Heating, Refrigerating and Air-Conditioning Engineers Bio-climatic Design Strategies NL Natural Light Building Use Studies O Orientation Cross Ventilation OS Opening Size Depth of balcony MSV Mixed-Strategy Ventilation Double skin façade MV Mechanical Ventilation Finite Element Method NV Natural Ventilation Facilities Management PIV Particle image velocimetry Greenhouse gas PMV Predicted Mean Vote Height to Depth ratio of balcony POE Post-Occupancy Evaluation Heat stress index PPD Predicted Percent of Dissatisfied Heating Ventilation and Air Conditioning Indoor Air Distribution RANS Reynolds-Averaged Navier-Stokes Indoor Air Velocity RH Relative Humidity Indoor Air Quality RSM Reynolds Stress Model Indoor Environment Quality RNG Renormalization Group Single-Sided Ventilation Integrated Environmental SolutionsSSV Virtual Environment SV Stack Ventilation IDA Indoor Climate and Energy TSV Thermal Sensation Vote International Standards Organization TVP Transom Ventilation Panel Length of the attached room URANS Unsteady RANS Large Eddy Simulation UL Unit Level Mean Age of Air
33
34
Contents
35
Abstract ............................................................................................................................................................... 1
36
1. Introduction .................................................................................................................................................. 3
37
2. Natural Ventilation (NV) ............................................................................................................................. 6
38
2.1.
Natural Ventilation (NV) Strategies....................................................................................................... 6
39
2.2.
Passive Design Elements ......................................................................................................................... 8
40
3. Design Parameters of Balcony ..................................................................................................................... 9
41
4. Socio-technical parameters ........................................................................................................................ 13
42
4.1.
43
5. Methods for evaluation NV effectiveness.................................................................................................. 19
44
5.1.
Post-Occupancy Evaluation (POE) Methods ...................................................................................... 19
45
5.2.
Evaluation Methods of NV performance ............................................................................................. 20
Application of POE to NV..................................................................................................................... 14
2
46
6. Summary and Suggested Future Studies .................................................................................................. 29
47
7. Conclusion ................................................................................................................................................... 32
48 49
Reference ........................................................................................................................................................... 33
50 51
1. Introduction
52
Climate change as a result of greenhouse gas (GHG) emissions from human activities is one of
53
the critical issues in the current century. It is estimated that buildings consume around 40% of global
54
energy and contribute more than 30% (between 30 % and 40 %) of the GHG emissions [1]. Since a
55
large percentage of these harmful emissions comes from Heating Ventilation and Air Conditioning
56
(HVAC) [2, 3], finding low or zero-carbon alternatives to HVAC is a persuasive idea to reduce GHG
57
emissions. One of these alternatives is natural ventilation (NV) [4], which can be used for cooling as
58
an alternative for Mechanical Ventilation (MV) all around the world.
59
NV, in general, is a process whereby fresh air is introduced to indoor spaces without using any
60
mechanical system [5]. In most cases, NV employs natural forces such as wind and buoyancy, to
61
move fresh air into an indoor area that occurs as results of pressure and density differences [6].
62
These forces are usually affecting the NV simultaneously and can act in isolation, or opposition, or
63
reinforce each other and sometimes operate in synergy [7]; however, one of these forces is always
64
predominant, determined using Archimedes number (less than one is wind-induced) or Froude
65
number (less than one is buoyancy forces) [8, 9]. Applying the NV strategy to modern architecture
66
and quantifying its impact on modern expectations of comfort, could demonstrate a significant
67
potential to reduce Mechanical Ventilation (MV) usage and persuade occupants of its usefulness in
68
meeting their comfort needs. Numerous studies show the remarkable potential of NV strategies for
69
ventilation purposes [10-12] and the critical priorities of these strategies compared with MV.
70
In modern architecture, various architectural elements such as windows, ventilation grills, wind
71
catchers, solar chimneys, wing walls, and overall façade system are typically considered by designers
72
for NV purposes in buildings [13-15]. Among these elements, façade design such as the provision of
73
windows, overhangs and balconies remains one of the leading technologies for NV purpose to reduce 3
74
energy consumption [16-20]. A balcony, as private outdoor space, is perceived by residents as one the
75
most desired features for providing fresh air, particularly in cooling dominant climates such as
76
tropical and subtropical regions [21]. Furthermore, other typical applications of balconies such as
77
entertaining and drying laundry suggest balcony as an essential design element, particularly in
78
residential apartments [22]. Consequently, it seems necessary to investigate balconies’ impacts on NV
79
utilisation and performance in social and technical aspects.
80
The provision of balconies, in general, changes the pressure around building façades and
81
subsequently affects the NV driving forces, including wind and buoyancy [23, 24]. Balconies mostly
82
affect outdoor and indoor airflow profiles and Indoor Air Velocity (IAV) that lead to changing the
83
indoor thermal comfort. Over the last decade, results of some studies that focused on the influence of
84
the balconies on NV performance, reveal the critical role and importance of balconies features such
85
as depth size on the indoor NV and thermal comfort in its attached room [25-28]. Undeniably, the
86
design of balconies appears to be a determinant factor of the NV performance at the purely technical
87
view. Thus, an investigation and classification of the balconies’ geometric features and their impacts
88
of the related parameters to the NV performance, such as IAV, could extract critical information in
89
the sustainable design context.
90
On the other hand, since NV utilisation has a social nature that might be affected by technical
91
design decisions on designing, there is a need to address socio-technical factors (i.e. comfort and
92
satisfaction) and their effects on the quantity and quality of the NV utilisation through balconies to
93
improve design based upon these parameters [29]. For instance, an exploration of the literature on
94
Post-Occupancy Evaluation (POE) revealed some design-related disruptive impacts such as balcony
95
scale on NV utilisation [22, 30, 31]. Subsequently, there is a significant opportunity of design
96
improvement through investigation of socio-technical factors to firstly realise the critical design-
97
related factors that have been focused in previous studies, and then find the degree of effectiveness
98
through a detailed review of these POE studies in the concept of NV through balconies.
99
The design of balconies should also be carried out with consideration of vital standards of the
100
health and comfort of attached indoor spaces. Because, a conflict between occupant satisfaction,
101
comfort, and health on one side and energy saving on the other side is usually a critical issue, which 4
102
sometimes sparks controversy over the impacts of energy saving on occupants’ comfort and health.
103
The importance of efficient and sustainable design, as well as various standards, criteria, and rules
104
for designing, are attempting to reduce the gap between the occupants’ comfort and higher usage of
105
energy in buildings. One benefit of these national or international standards such as American
106
Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) [32] is to recommend
107
criteria of living spaces to satisfy residents’ health and comforts with regards to energy saving
108
matters. Occupants also play a crucial role since they carry out the act of energy-saving. A review on
109
buildings design, as well as users’ forgiveness factor, which depends on overall comfort and average
110
satisfaction scores of ventilation or air and temperature in summer [33-35], could determine the
111
interaction between these parameters.
112
This review article aims to explore the impacts of designing balconies’ geometry on NV
113
performance and perceptions and behaviour of users, as two vital technical and socio-technical
114
factors, respectively. For this, the current paper firstly summarises the application of the most
115
considered passive design elements, for NV utilisation in building. For this, the article explores the
116
number of studies that have focused on the application of balconies for NV utilisation, the principal
117
focus of the current research, compared to other elements for passive design in Section 2. Section 3
118
focuses on studies that have investigated the influence of design features of balconies on NV
119
performance and classified the crucial parameters based on the degree of impacts reported in the
120
literature. Socio-technical factors such as occupants’ comfort are considered through an exploration of
121
the application of POE on NV utilisation through different façade openings, and specifically through
122
balconies, to find the degree of comfort, critical obstacles, and incentives, under NV mode instead of
123
MV (Section 4). The most common methods that have been employed to identify the critical design
124
elements of balconies and impacts of geometry’s features on users are investigated in Section 5.
125
Results, including research gaps, are summarized and lead to a comprehensive discussion and
126
recommendations for possible future studies to fill the gaps (Section 6). Finally, the current article
127
draws an overall conclusion in Section 7.
128
5
2. Natural Ventilation (NV)
129 130
Ventilation is employed to supply fresh air, maintain comfort (temperature and humidity),
131
eliminate or dilute contamination [36]. There are two primary types of ventilation, MV and NV,
132
which are usually applied by occupants, particularly for cooling purposes. Energy consumption
133
concerns and Global warming due to the GHG emission are the critical reasons caused that NV has
134
been considered as an appropriate alternative for MV. NV uses outside air movement and buoyancy
135
pressure differences to refresh the air and ventilate a space instead of electricity consumption, which
136
is usually applied for MV. NV technologies have been shown a significant capability for the
137
adequate cooling and thermal comfort [37-39], so NV could be an attractive option for the building
138
designers and architects to design more energy-efficient and saleable apartments.
139
Various studies reported a range of advantages of NV, compared with MV, such as less required
140
space for NV [40, 41], lower cost [42], providing reasonable thermal comfort [43, 44], less GHG
141
emission [45], and fresh air that leads to improving Indoor Air Quality (IAQ) and healthier indoor
142
area [46, 47]. There is also evidence that NV could increase the adaptability of people to the outdoor
143
environment and contribute to a higher forgiveness factor reported in some NV buildings [43]. These
144
capabilities can be solutions for critical issues of ventilation systems in the new era. For example,
145
occupying less space through an innovative passive cooling design is a remarkable capability for the
146
gradually urbanised populations who are living in cramped and small apartments. Besides, the higher
147
adaptability of occupants can lead to better thermal comfort without using MV due to the higher
148
forgiveness factor of occupants. These benefits have attracted architects attention to NV as a useful
149
ventilation process for several types and applications of buildings [48, 49], mainly for the
150
increasingly urbanised society in cities that include a large number of towers and skyscrapers [50,
151
51].
152
2.1. Natural Ventilation (NV) Strategies
153
NV strategies are mainly categorised in four strategies: Cross Ventilation (CV) [52], Single-Sided
154
Ventilation (SSV) [53], Stack Ventilation (SV) [54], and Mixed-Strategy Ventilation (MSV) [55,
155
56], displayed in Fig.1. 6
Cross-Ventilation (CV)
Stack-Ventilation (SV)
Single-Sided Ventilation (SSV)
Mixed-Strategy Ventilation (MSV)
156 Fig. 1. Schematic of natural ventilation (NV) strategies
157 158
CV and SV are both unidirectional and at least two openings, an inlet and an outlet, are required
159
for these strategies. They differ, however, in that CV is a horizontal process, and SV is a vertical
160
process. In CV (wind effect or wind-induced), openings are mainly located on two sides of a
161
building, and the pressure difference between these two openings make indoor air flows, which
162
move from higher to lower pressure [14, 57]. SV is a thermal buoyancy-driven strategy and airflow
163
arises because of the temperature gradient between the inlet and outlet. The warm air rises due to the
164
lower density and is replaced by colder air from outside.
165
In contrast, SSV describes units or apartments with only one opening or only openings on one
166
side. Examination of SSV is perhaps more applicable than SV or CV in urban environments, given
167
the higher number of apartments with single-sided openings [58]. Wind, buoyancy, or a combination
168
of these forces can lead to SSV [59, 60]. The wind and buoyancy ventilation rate (m3/s) can be
169
calculated using Equation 1 and 2, respectively [61]. ( ( ) and (
)=
)=
2 (
=
2
− ) ℎ = +
(1) (
) ℎ
(2)
170
where (
171
pressure (
172
external air density (
173
the vertical interval between openings (ℎ[ ]), and gravitational acceleration ( [
[
), respectively, represent opening discharge and pressure coefficients. Mean static !
]), air density ( ["# ]), reference velocity ( and
"
[ $ ]), area ( [
%
]), internal and
), temperature differences between indoor and outdoor ( "& ]) $
7
=
−
),
are the other
174
variables that contribute to calculating the wind and buoyancy ventilation rate.
175
Among NV strategies, although most of the apartments rely on SSV due to the predominant use
176
of only one opening at an attached indoor area, CV usually provides more fresh air and IAV than
177
SSV [62, 63]. Both the location and the opening size of design elements such as windows, balconies,
178
chimneys, courtyards, and ventilation grills could be critical points in the success of these NV modes
179
[12] and the role that element features. Selection and location of architectural elements for passive
180
design in buildings are widely studied in the literature [50, 64]. 2.2. Passive Design Elements
181 182
The effectiveness of design elements such as windows [65-67], façade system like double-skin
183
façade [68] and balconies [69], ventilation grills, wing wall and Windcatcher [70, 71], solar chimney
184
[72, 73], and integration of these systems [71] was reported in scientific literature to varying degrees.
185
For example, the application of windows for NV utilisation in buildings is reported in [74], and a
186
Scopus database search (with the keywords of “windows” and “natural ventilation” in titles, abstract,
187
and keywords, in related subject areas) reveals 829 articles on the role of windows in NV. In
188
contrast, a similar search for “wind catcher” resulted in only 80 articles. Table 1 displays the results
189
of the same search strategy for the most considered passive ventilation elements, as reported in [48].
190
Table 1. Number of publications on NV thru passive design elements by August 2019 Rank Passive elements Period Number of studies* 1
Windows
2
Chimney
3
Atrium
4
Double skin façade (DSF)
5
Wind catcher
6
Courtyard
7
Wind tower
8
Balcony (or porch or veranda)
9
Void
10
Wing Wall
2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019
334 495 74 119 21 83 32
Before2015
77
2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015
42 31 27 45 23 27 10 26 10 10 7 4
8
191
* These numbers are recorded with limitation to engineering or energy or environment sciences in Scopus
192
This literature search reveals that far fewer studies have been published relating to the role of
193
balconies for NV, compared with most other design elements, and compared to windows. It is
194
curious given that windows and balconies are two commonly used elements in medium and high-rise
195
residential buildings in multiple climate zones and cultures globally. The Scopus database reveals
196
around 1700 research articles relating to balconies in general, however only 2% of these investigated
197
NV through balconies. It suggests that designers and researchers have not actively considered a
198
balcony as a potential passive design element to enhance or drive NV, and reveals a research gap
199
that is worth investigating [75].
200
The construction of balconies significantly affects the wind velocity and pressure profile around
201
façades [23, 76] that can lead to changing the IAV and NV performance in the attached room. The
202
impacts of balcony geometry on the NV performance was explored as a critical hypothesis by
203
researchers in some literature [25-27]. These studies debunk the null hypothesis that the geometry of
204
balconies does not impact on NV and build the case for further research in this area. The next section
205
dedicates to the literature on the impact of balcony geometry on NV.
206 207
3. Design Parameters of Balcony
208
Studies on how balcony design features affect NV performance and thermal comfort inside the
209
apartments are limited in the literature, and these parameters have not been adequately explored,
210
unlike other openings such as windows. Among the limited number of publications, a few articles
211
focused on the impacts of balcony design on the NV performance. These studies mainly explored the
212
effects of the availability of the balcony and then investigated the impact of various balcony design
213
parameters on NV performance and thermal comfort. The design parameters examined include
214
Orientation (O) or Wind Angle (WA), Unit Level (UL) within the building, Depth of balcony (D),
215
Length of the attached room (L), Depth to Length ratio (D/L %), and Opening Size (OS). A
216
summary of these studies is presented in Table 2.
217
Table 2. Literature on the influence of balcony design parameters on NV performance 9
Balcony design parameters* Row
1
Ref
[77]
2
[78]
Ventilation mode &
Balcony Type
Studied Features
Open and semi-open
D/L (%) = 0, 10, 20, 30 & 40 WA(º)= 0, 45, 90 & 180
SSV
Open
Availability of balconies, upper & lower vents at balconies UL= 4, 5 & 6 (at the End (E) and Middle (M)) Availability of balconies & location D=1.5 and 3 m UL= 1 to 12 WA(º)= 0, 45, 90
CV & SSV
3
[25]
CV
Semi-open (balcony with wing wall)
4
[76]
CV & SSV
Open
5
[79]
CV & SSV
Open
6
[80]
CV & SSV
Open
7
[23]
CV & SSV
Open
Availability of balconies UL= 3 & 4, WA(º)= 0 & 45 OS (single & double) = 0.9 & 1.8 m Opening locations= 2 models (middle=1.8m, left & right= 0.9m) UL= 1 to 12 & WA(º)= 0 & 45 Availability of balconies UL= Ground to 5 WA(º)= 0, 22.5, 45, 67.5 & 90 Availability of balconies UL= Ground to 12 WA (º)= 0 & 45 Availability of balconies OS= 6 scenarios (with &without balconies, Small and Big opening at Middle & End), UL= Ground to 5
Best Scenario or Classification Open balcony, CV & D/L=10%, WA=0º Deeper balcony lead to lower NV performance Upper and lower vents at middle floors enhance the NV rate and make airflow recirculation UL=4E with balcony Available balcony (with regards to opening’s location), WA=0º & UL=10 Deeper balcony lead to lower NV performance Not Available (Best method is steady-state RANS) For CV, WA=0º & UL= 8 & 9 For SSV, with balcony, WA=45º & UL= 10 is the best Adding balconies increased NV rate intermediate levels (UL= 2, 3, 4), best UL= 3 & WA(º)= 0 1- Highest NV rate: CV without balcony, 2- SSV with balcony (WA=45º) was the best CV: Ground level with balcony & UL=G & 3 without balcony (small opening) SSV: UL=4 with balcony, UL= 4 (without balcony big opening) Based on the payback results, with balcony at SW
8
[81]
CV & SSV
Open
9
[82]
SSV
Open
10
[27]
SSV
Open
11
[83]
CV & SSV
Open
12
[84]
SSV
Open
Availability of openings or balconies, OS (33 models)
Different balcony & opening configurations significantly change airflows.
13
[85]
CV & SSV
Open
Availability of balconies UL= Ground to 5 WA(º)= 0 & 90
Available balcony at WA=90º& D=1.5m.
Availability of balconies O= N, S, E, W, NE, SE, SW Availability of balconies Opening: 2 vertical & 1 horizontal UL= Ground to 5 D= 0.75, 1.5, 3m, WA(º)= 45 & 90 Balustrade with & without solid Availability of balconies or/and wing wall or/and overhang WA(º)= 0, 45, 90 & 180
Best Scenario: with balcony, UL=5, vertical opening& WA=90º Best Scenario for the NV through balcony: Not Available
218
Table 2 shows the small number of studies investigated the impacts of balconies’ design
219
parameters on NV performance. Among the examined parameters, orientation (or WA) and UL were
220
studied by most of the articles, while features such as D, D/L ratio, and OS have not been
221
investigated thoroughly. Some unitless factors like Height to Depth (H/D) ratio and other
222
characteristics such as balustrade type (materials, shape, height) are not represented in the literature 10
223
at all. The following paragraphs report on four critical features containing present or absent of
224
balcony, unit level, depth, and orientation, which more considered in the literature based on Table 2.
225
First, some researchers investigated the availability of balconies on façades and explored the
226
effects of NV performance on indoor areas in the present or absents of balconies [76, 81]. The
227
availability of balconies as well as the impact of the location of a balcony opening on NV
228
performance was investigated using validated simulation and experimental data (at both full-scale and
229
small-scale) [25, 84]. Results of these studies show that adding a balcony can enhance NV
230
performance, but the improvement level depends on the NV strategy (i.e. SSV and CV) and balcony’s
231
geometry [26, 80-83].
232
It was found that although SSV performance can be enhanced with appropriate balcony design, the
233
highest CV rate occurred in a scenario without any balcony on the façade [23]. Furthermore, most of
234
the studies in Table 2; highlight the significant impacts of balconies’ design parameters on NV
235
performance, but Ai et al. [80] mentioned the negligible impact of balcony geometry on CV
236
performance. This difference might have occurred because of the different airflow pathway options
237
available in the CV that caused the impacts of changing geometry was lower on CV [23, 26, 79].
238
Table 2 reveals that the latest studies have focused on SSV more than other NV strategies and
239
investigated the geometry impacts on SSV performance. Besides, a substantial proportion of
240
apartments are now more reliant on SSV than CV; therefore, the geometry impacts seem to be critical
241
in most of the case studies.
242
Second, the literature review also revealed unit levels (balconies’ height above ground), as one of
243
the most investigated parameters, affected the NV performance at an indoor area [78, 80]. Although
244
there is not a specific conclusion regarding the impacts of unit levels on NV performance through
245
balconies, table 2 shows the significant difference between the unit level impacts on SSV and CV
246
strategies [23, 80, 81, 85]. For instance, a comparison between the impacts of different unit levels, in
247
a medium height building (5 levels), on NV performance for both SSV and CV shows that the
248
ground level had the best NV performance for CV, while the best SSV performance occurred in level
249
4 [86]. Therefore, there is not a clear conclusion on the impacts of the balcony’s height on NV
250
performance that could be considered as an essential gap in further studies. 11
251
Third, the results of the previous studies highlight the depth of balconies as an essential parameter
252
that crucially affects NV performance on both SSV and CV [28, 77]. These studies reveal a deeper
253
balcony could lead to a lower NV performance at an indoor area, but the authors have not explored
254
and compared the depth impacts with regards to other feature such as orientation. Finally,
255
concerning the orientation of balconies, literature shows in-case conclusions instead of clear trends
256
or relations between the impacts of orientation and other critical design-related parameters on NV
257
performance. For example, the impacts of depth on NV performance in different orientations have
258
not been investigated and compared yet. Therefore, there is a gap in this context to find the
259
interaction between these geometric factors.
260
Even though the authors investigated these four design-related parameters of balconies, the
261
review indicates there are no adequate studies on the classification of the most crucial geometric
262
factors, and the impacts of these factors on SSV and CV were not explored and compared with each
263
other. Omrani et al. [26] studied depth, type (open and semi-open balconies) and orientation (or
264
WA), on SSV and CV performance and thermal comfort in residential buildings. This study
265
classified the mentioned parameters based on their effect on NV performance, reporting that
266
changing WA can affect the NV performance and thermal comfort more than varying depth scales
267
and types of the balcony.
268
To conclude, the key findings of this section are as below:
269
•
Adding a well-designed balcony can improve the NV performance.
270
•
The effects of adding a balcony, as well as changes to balcony geometry were not identical for CV and SSV.
271 272
•
orientation did not have the same effects on CV and SSV performance.
273 274
•
The interaction between balcony depth with other geometric factors with heights and orientation have not been investigated.
275 276
All investigated parameters containing present or absent of balcony, unit level, depth, and
•
There is no precise classification of the impact of design parameters on NV.
277
12
278
4. Socio-technical parameters
279
Because the purpose of NV is to assist in occupant comfort, it is critical to investigate the impact
280
of balcony design features on occupant sensation, comfort, and behaviour due to the social nature of
281
NV utilisation [87]. Passive designers should always be aware of drawbacks, as well as incentives,
282
that could affect the utilisation of NV through balconies. For instance, violating thermal comfort and
283
privacy are crucial factors that sometimes stop users from utilising NV, while having access to a
284
breeze, refreshing air, and better Indoor Environment Quality (IEQ) due to a proper design of
285
balconies could encourage occupants to open balcony doors [22]. Occupant feedback can assist
286
architects and designers in developing more robust and acceptable solutions. POE is a standard
287
method for seeking feedback from buildings; however, it is not universally applied in practice by the
288
design and construction industry as part of quality assurance and a continuous-improvement process.
289
POE, in general, is a qualitative procedure of collecting feedback from occupants concerning their
290
behaviour, experiences, and expectations about the performance of buildings [88, 89]. POE is
291
designed to investigate results from social, spatial design, and planning through occupants’ feedback
292
[90]. It gathers the firsthand data from users that is crucial for designers, managers and planners to
293
understand and perhaps to enhance the current status of a building. Feedbacks from building
294
occupants can highlight obstacles, as well as motivations, that may lead to improving efficiency and
295
performance of the buildings regarding construction (i.e. costs), suitability (e.g. design and location),
296
utilisation (such as function, size, and capacity), performance (e.g. energetic and environmental
297
aspects), and other critical subjects [91, 92]. POE, then, can be an appropriate tool for seeking
298
occupant perceptions regarding NV as well as the geometry and utilisation of balconies.
299
POE as an evaluation method was proposed in the 1960s and 70s in the United Kingdom, and
300
then in Australia and the USA based on social science, architecture, and building planner concepts
301
[14, 93, 94]. The first generation of the POE focused on occupants’ feedbacks on the indoor
302
environment such as HVAC performance. The 1980s saw POE deployed in diverse areas within the
303
built environment [95-97]. As deployment increased, the tools used for POE also became more
304
refined and sophisticated [91]. Nowadays, researchers are broadly applying POE to evaluate a range
13
305
of criteria such as energy-saving, occupant comfort (e.g. thermal and luminance), and indoor
306
environment in diverse types of buildings (i.e. residential, commercial, educational, and so on) [98,
307
99].
308
Compared with technical building performance evaluation that can occur at any or all of the six
309
main phases of a building’s life cycle: planning, scoping, design, construction, occupancy and end-
310
of-life [90], POE occurs only in the occupancy stage. It seeks occupants’ feedback regarding their
311
experiences and perceptions and satisfaction with the building’s performance [100-102].
312
Furthermore, other issues that are related to the users’ satisfaction factors such as cultural, social,
313
and psychological parameters make POE a multidisciplinary approach that addresses socio-technical
314
aspects of a building. POE also has the benefit of time flexibility as it can be deployed at any time
315
during a building’s occupancy and evaluations can be short, medium or long-term, providing the
316
options for capturing ‘instant’ feedback, trends and changes over time.
317
4.1. Application of POE to NV
318
Some consider POE as the inevitable step toward sustainability [103] and a missing link for
319
designing energy-saving buildings [89, 104]. The strong global focus on energy efficiency in
320
buildings has resulted in a large number of studies on the application of POE for assessing NV
321
utilisation and performance in different residential, commercial, and working spaces [105-107].
322
Literature shows that researchers typically conducted POEs on apartment buildings, focusing on
323
environmental condition such as IAQ, temperature, humidity, noise, and light to finding the level of
324
comfort and occupants’ feedbacks regarding their discomfort sources to find perspective solutions
325
[108-110]. Researchers have also widely applied POE to evaluate health, feelings, and thermal
326
comfort through NV utilisation in buildings, and applying these findings to improve the design and
327
function of the buildings [105, 111].
328
NV performance and usage have mainly been an excellent source of information for researchers,
329
and they extracted this information from occupants’ feedbacks regarding thermal comfort and
330
behaviour to help architects and designers to improve their works [92]. There are numerous studies
331
regarding thermal comfort through POE to explore warm feelings of users [112-114]. These POE
332
have also contributed to the foundation of some standards in this context. For example, in the 1970s, 14
333
Fanger [115] created an optimal thermal comfort POE method on occupants’ perception that was
334
associated with some calculations, heat-balance equations, and empirical studies on the metabolism.
335
Fanger also developed two indices, Predicted Mean Vote (PMV) and Predicted Percent of Dissatisfied
336
(PPD) to evaluate thermal feelings and comfort [116]. This approach was further accepted by the
337
International Standards Organization (ISO) 7730 and ASHRAE as a standard to quantify thermal
338
comfort [116, 117].
339
Although Fanger approach (including PMV and PPD indexes) is considered by some to be an
340
appropriate tool to evaluate thermal sensation, it was highlighted in some studies [118-120] that these
341
indices are not always considered to be accurate in predicting thermal sensation in extreme climates
342
(such as tropical climates) due to different expectations of occupants. Some also indicated that the
343
Fanger approach is also not an excellent tool to evaluate thermal sensation in residential buildings due
344
to the unpredictable behavioural patterns [121]. Indeed, thermal environments in residential buildings
345
are quite different from the more predictable and ‘steady’ thermal environment of offices or the lab
346
conditions where Fanger developed PMV and PPD. Besides, it was found over the earlier studies that
347
PMV underestimate the thermal comfort of buildings under NV mode [122]. Because of these
348
compelling arguments against this approach, Fanger presented the modified approach with a
349
correction for indoor areas under NV modes and extended the first method by introducing the
350
expectation of occupants under NV and multiplying this factor on the basis PMV [123, 124]. The idea
351
of the Fanger approach then was complemented with an adaptive thermal comfort model that was also
352
introduced by some other researcher [125-127].
353
Application of POE in residential areas may also lead to outstanding results since these areas are
354
more undefined and less steady than office work or educational areas [121]. It means POE can
355
monitor residents with different cultures, behaviours, and adaptabilities that have the authority and
356
capacity to control their comfort by changing modes and types of their cooling or heating, or changing
357
their clothing or room location, while this authority is limited in other non-residential areas. For
358
example, NV is sometimes not a possible option in some office buildings due to the windows not
359
being operable. Consequently, the thermal comfort of occupants as well as NV utilisation is in
15
360
different ranges and patterns and POE may extract new understandings, especially for residential
361
buildings.
362
Researchers have employed POE to monitor the behaviour and comforts regarding NV utilisation
363
through different elements such as windows [128], balconies [106], and wind catchers [129, 130].
364
Balconies as private and adaptive outdoor areas are considered as one of the most desirable function
365
spaces, particularly in cooling dominant climates. The results of a technical guide by Wood and Salib
366
[131] reveals more than 40% of users of high-rise buildings, in general, identify access to the outside
367
by balconies or other openings are essential for them. Moreover, findings of a survey on thermal
368
comfort of apartment buildings in the tropical climate of Hyderabad in India indicates 60% of
369
occupants are not comfortable in summer because of reduced availability of adaptive opportunities
370
such as balconies and windows [132]. Additionally, NV utilisation through different passive elements,
371
including balconies being considered more in recent years [133, 134].
372
As POE is a proper tool to discover the gap among current performance and behaviour,
373
experiences and expectations of occupants through their feedbacks, hence it seems a useful procedure
374
to evaluate the current status of balconies and come out new ideas. Table 3 summarised POE projects
375
on NV utilisation based on critical characteristics.
376
Table 3. POE studies on the NV utilisation
Ref
Building Type
Climate
Green Feature (s)
Purposes of POE
Methods
NV
Subjective perceptions when sitting, walking & running under NV vs MV
Questionnaire (Likert Scale) & Physical measurement
T-test using SPSS
NV
Perceived IAQ & Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
PMV & Thermal Sensation Vote (TSV)
PMV & TSV
Thermal comfort vote & TSV
[135]
Workplace (office)
Subtropical (humid)
[38]
Learning places (classrooms)
Between semiarid & humid subtropical
[39]
Workplace (office)
Cold tropics
NV
Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
[136]
Learning places (High school)
Tropical
NV through windows
Thermal comfort
Questionnaire (Likert Scale)
16
Data Analysis
Critical Findings The decreasing magnitude of acceptable temperature was more extensive under AC compared to NV. Measured thermal comfort was less than the PMV. The occupants’ density affected perceived IAQ but not thermal sensation. ASHRAE adaptive model recommends comfort temperature less than TSV. Although most of students accepted the temperature, most of them preferred lower temperature.
[137]
[138]
[139]
Residential
Workplace (office)
Learning places (5 universities)
Five regions contain very cold, cold, hot summer & cold winter, mild, & hot summer and warm winter
NV through windows
Usage of NV vs MV in five different climate zones
Questionnaire (bipolar between NV & MV) & Physical measurement
Statistical analysis (Mean rating)
Subtropical (oceanic)
Natural Light (NL), NV& MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Likert Scale) based on Building Use Studies (BUS)
Statistical analysis (Mean rating)
Subtropical (humid)
NV & NL through windows
IEQ (air, noise, lighting & health), Building Design (BD) & Facilities Management (FM)
Questionnaire (BUS) - Likert Scale
T-test
IEQ (air, noise & lighting) & thermal comfort & Adaptive behaviour
Questionnaire (Likert Scale) & Physical measurement
ANOVA using SPSS TSV & Spearman correlation coefficient
[140]
Residential (dormitory)
Tropical
NV & MM through windows
[111]
Learning places (primary school)
Mediterranean climate
NV & NL
IEQ (air & lighting) & Thermal comfort
Questionnaire (Fanger approach)
PMV, TSV & PD using MATLAB
Tropical
NV & NL through balconies
Thermal and overall comfort under Bioclimatic Design Strategies (BDS) [141]
Questionnaire (Likert Scale)BUS & Experiment
Pearson correlation
NV
Thermal comfort & pleasant sleep environment in bedrooms & behaviour
Questionnaire (Likert Scale)
Statistical analysis (Mean rating)
Questionnaire (Likert Scale)
PMV, SET*, ET*, PPD, Mean radiant temperature & Heat stress index(HSI)
Questionnaire (Likert Scale)
PMV
[75]
[142]
Residential (college)
Residential
Tropical
[120]
Hospitals & Shopping centres
Tropical
NV
Thermal, humidity, air movement sensation & thermal comfort
[143]
Residential (dormitory)
Humid continental
NV through windows
Thermal comfort & IAQ
17
Thermal comfort has priority to IAQ for occupants. Health was the crucial factor that led to preferring MV. NV & MV periods, respectively, have direct & reverse trends with rising outdoor temperature. Office under NV mode slightly more satisfied than MM. NV provides more comfort than MM, as well. Although Green buildings’ occupants are more consistently satisfied than non-green for BD & FM, IEQ satisfaction is lower in non-green buildings. BD affects occupants’ behaviour. Occupants in tropical felt thermal comfort in higher temperature than ASHRAE. Clothing, Higher IAV & MM with NV & Fan were vital adjustments. Thermal satisfaction was significantly different for teachers & pupils. Application of BDS, which assimilates physiology, climatology & building physics, has significantly enhanced overall comfort except for NL. Older people & outdoor workers use more NV & fans instead of AC that may show the impact of users’ adaptability. Two comfortable temperature ranges were defined for hospitals & shopping centres that challenge the ASHRAE PMV thermal comfort. Results show NV & thermal comfort trends & the upsurge of the NV areas decrease the thermal comfort. Authors developed a model for a fair NV utilisation for adequate thermal
[35]
Workplace (office)
Subtropical (oceanic)
Advance d NV & MM
Thermal comfort (static & dynamic)
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
[144]
Learning places (university)
Temperate (Sheffield)
NV & NL
Thermal comfort & Energy efficiency
Questionnaire (Likert Scale)
PMV & t-test
semicontinental
NV through a balcony
IEQ, thermal comfort through different layouts & cooling types (MV & NV)
Domestic questionnaire (Likert Scale) based on (BUS)
Statistical analysis using NVivo software package
Subtropical & Tropical
NV, daylight & view, green space
Health perceptions (physical & psychological)
Cross-sectional questionnaire (Importance & Likert scale)
T-test
NV & NL
IEQ, overall satisfaction (thermal, air & lighting) & energy usage
Questionnaire (Likert Scale) from previous study [135]
T-test, ANOVA using SPSS V18.0
Subtropical
NV
Common usage of balcony & overall comfort & sensation of NV utilisation thro balconies
Questionnaire (Likert Scale) & Interview
Statistical analysis by SPSS
IAQ, Indoor thermal sensation, windows opening habit
Questionnaire (Likert Scale, importance & rating scale) & Interview
SPSS (Crosstab & Chi-square)
[106]
Residential
[145]
Workplace (office) morphology
[146]
[22]
Residential
Residential
Subtropical
[147]
Residential
Continental (humid)
NV through windows
[148]
Workplace (office)
Different climate in China
NV, NL & MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Importance & Likert scale)
ANOVA test
[149]
Workplace (office)
Subtropical
NV
Comfort & design satisfaction, needs, health & productivity
Questionnaire (BUS) - Likert Scale
T-test
[150]
Workplace (office)
Between semiarid & humid subtropical
NV through windows
Thermal comfort & IAQ
Questionnaire (Likert Scale & Bipolar) & Physical
PMV & TSV
18
comfort. Thermal comfort is satisfactory in summer, but dissatisfaction occurred in winter. Static & dynamic thermal comfort matched with POE results in summer & winter, respectively. Environmental control by users improved comfort perception. The Gap between energy performance & comfort can be field using POE results & prediction. Find challenges of designing & critical issues to help researchers, designers & managers for the future projects. There is an association between green features & health perceptions in offices. This article contributes to justify & optimise passive climateadaptive design strategies. A structural model was developed based on the relationship between IEQ, satisfaction & energy usage to enhance IEQ & satisfaction Residents significantly prefer NV to achieve thermal comfort compared with AC in the subtropical climate of Brisbane. People behaviour & habits of opening windows based on room & windows opening size in winter was cleared based on POE results. MM ventilation is very sensible picks for green buildings for high satisfaction. Recommend more awareness & forgiveness factors for green buildings’ users. IAQ has a significant impact on IEQ acceptance. Warm neutral temperature
measurement
[151]
Learning places (university)
[109]
Workplace (office building)
[152]
Workplace (university office)
377
Tropical
Subtropical (humid)
NA
IEQ (air, noise, lighting & cooling device & design) & overall comfort
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
NV
IEQ
Questionnaire (BUS) - Likert Scale & Physical measurement
Pearson correlation
NV & NL
IEQ (air, noise & lighting) & thermal comfort & forgiveness factor
Questionnaire (Likert Scale)
PPD for NV, AC & Mix based on CBE of Berkeley database
NV through windows
found 20 °C (good agreement with Chinese standard). Occupants could achieve thermal comfort without AC, but need for more information to get the optimum usage of NV. Around 90% was satisfied & most of the dissatisfactions occurred due to chiller (staffs work close to vent). Occupants who are usually using AC expressed more negative evaluations (low forgiveness factor); in contrast, the MM and NV buildings.
The key findings from the reviewed POE/NV literature include:
378
•
Workplaces have been studied much more than residential buildings.
379
•
Most studies were carried out in cooling dominated climates, with some studies challenging the ASHRAE thermal comfort standards.
380 381
•
instead of MV.
382 383 384
The literature seems to highlight the importance of occupants’ dedication to NV utilisation
•
Researchers have not discovered what the impacts of design feature on the quantity and quality of NV utilisation and how it could be improved based on POE results.
385 386
5. Methods for evaluation NV effectiveness
387
The literature reveals several methods or techniques used to evaluate the impact of balcony
388
geometries on NV performance and occupant perceptions [107]. This section aims to investigate the
389
most practical approaches through the literature and compare their advantages and limitations.
390
5.1. Post-Occupancy Evaluation (POE) Methods
391
POE typically investigates the building issues in three levels, including indicative that present an
392
indication of performance and find the issues, investigative that usually focuses on finding issues, and
393
finally diagnostic that displays deficiency and presents some actions as corrections [153-155]. In a
19
394
broader view, POE is categorised into two general steps, including planning and implementation
395
[156]. The planning phase is usually divided into four parts, including deciding to accomplish (why
396
POE?), selecting an approach, briefing or details of POE, and method selection. The implementation
397
phase is also clarified through three steps containing carryout, data gathering and analysing, and
398
providing an action plan [157, 158].
399
There are several standard methods used to conduct a POE: questionnaires, interviews, focus
400
groups (i.e. group meetings), workshops, and walk-through evaluations [90, 91, 159-161]. A
401
comparison of the methods, based on time, cost, perspective, results accuracy and quality, was
402
reported in [92, 162]. Although this study shows that individual interviews and questionnaires are the
403
best methods for POE, the reported barriers of these methods include the slow procedure of
404
interviews, the needs for a skilled interviewer, and the need for skilled survey design (to ensure
405
critical points are not omitted). The main advantage of the surveys is the simple distribution of a
406
survey to the targeted participants (i.e. online). Besides, the survey’s results can be analysed using
407
statistical tools to find possible patterns and relations that might be useful for future studies or
408
designs. In summary, the literature concludes that a well-designed, brief, subjective and qualitative
409
questionnaire remains the primary POE method utilised but designing such a survey remains
410
challenging.
411
5.2. Evaluation Methods of NV performance
412
NV performance is usually quantified based on airflow pattern and rate, IAV, Air Change per Hour
413
(ACH), Mean Age of Air (MAA), volumetric flow rate, and other derived quantities from these
414
parameters [163]. The evaluation methods are mainly categorised into analytical and empirical
415
methods [8], numerical or computational analysis [164], experimental methods (small and large scale)
416
[165]. Analytical approaches involve single zone, and multiple zones [60] are driven by the theory of
417
heat transfer and fundamental mathematical fluid dynamics, while the empirical methods are
418
established on measurements and observations. Both analytical and empirical methods are useful for
419
initial steps and estimation of simple geometries [166].
20
420
Researchers have employed these methods or a combination of them such as association of CFD
421
and empirical models [167-169], empirical model integrated to small and full-scale experiment [85,
422
170], coupled CFD simulation [171-173], and de-coupled CFD models [174-176] based on their
423
accuracy, cost and time consuming, and the objective of their studies. Omrani et al. [177] explored,
424
assessed, and categorised robustness and limits of each technique regarding the accuracy, application
425
for complex geometries, resolution of results, cost, and spending time. The authors highlighted the
426
related methods for various situations concerning drawbacks and constraints and suggested a design
427
model for NV in high-rise residential apartments that can be employed in the design and construction
428
phases.
429
Computational simulation methods such as CFD simulation or a combination of CFD and other
430
approaches (e.g. experimental) are introduced as the most applicable approaches to find details of NV
431
such as air velocity, pressure, and particle distribution both indoor and around the buildings [169,
432
178]. Although CFD simulation is usually time-consuming compared with analytical and empirical
433
techniques, it provides details information on NV such as air velocity and pressure. Authors have
434
usually validated the simulation results against real experimental data or outcomes of other evaluation
435
methods to approve the simulation procedure for the further analysis and possible scenarios. There are
436
several methods to validate simulations that CFD combined with network airflow models [60, 179,
437
180] and experimental methods (small and large scale) [165, 181-183] are possible combinations.
438
CFD simulation software numerically describes physics of air movement using Navier-Stokes
439
equations (i.e. Reynolds-Averaged Navier-Stokes (RANS)). The RANS equations are usually
440
calculated along with the governing equations such as k-ε and k-ω models. Three physical principles
441
including conservation of mass (continuity equation), energy conservation (first thermodynamic law),
442
and the second Newton law (momentum equation), in general, are basis of the governing equations
443
that are, respectively, shown in Equation 3, 4, and 5 for the steady incompressible flow [184]: '( ( ) = 0 (3) ')
'(', ( (- . ' ' '( 555555 =− + + ́2 (4́ 1 + 6 ( − /0 / 1− ( ') ')- ')')- ') 21
7)
(4)
'( ( ) 1 ' ' ' 55555 = ;< =+ (− ( 4́ ) (5) ') 9: ')- ') ')444
55555 where ( 7 ), (6), and (( 4́ ), correspondingly, represent the operation temperature, thermal expansion
445
coefficient, and turbulent heat flux. Therefore, the constant values of different governing equations
446
can be calculated based upon these equations [184, 185].
447
NV behaviour, unlike MV, is much less expectable, so modelling tools play an essential role to
448
discover more about the airflows’ motions. Hence, CFD was broadly employed by researchers to
449
simulate NV in buildings and find the airflow related parameters such as IAV, MAA, and ACH [69,
450
169, 178] to show the variation of NV performance due to changing design features of passive
451
elements. Although CFD simulation is a time-consuming procedure, high-accuracy, low cost, and
452
suitability of this simulation method caused CFD becomes a favourite tool to simulate airflow pattern
453
in naturally-ventilated buildings [169]. Besides, as CFD simulation mainly needs to be validated
454
using an auxiliary source, different validation tools, mainly experimental analyses, were suggested for
455
this purpose [169].
456
Experimental analyses, which are divided into small and full scales, are extensively employed to
457
calculate airflow characteristics (i.e. velocity, pressure, and temperature). In the context of NV
458
studies, researchers have usually applied experiments as a validation tool for numerical analysis,
459
which also helps to adjust the grids [69, 169]. Although the literature shows both small and full scales
460
of experiments are the highly accurate studies compared with other validation methods, these studies
461
are usually costly and time-consuming [105, 186, 187]. The magnitude of the cost and time
462
consumption directly depend on the amount of detailed data [169]. Therefore, designing an
463
experiment regarding cost, time, and the required amount of details data are a critical issue, and strong
464
knowledge of the previous studies can be helpful to design an optimum experiment based on the
465
mentioned criteria. Table 4 summarises the recently published articles (from 2014) in the context of
466
evaluation methods of NV to comprehend more details about the simulations and their applied
467
validation tools.
468
Table 4. Evaluation methods of NV through different passive elements 22
Ref
Climate types
[188]
Tropical
[130]
Not a specific climate
[189]
[190]
[191]
[192]
[193]
[195]
Subtropical (humid)
Tropical & Subtropical
Desert (hot & arid)
Tropical
Not Available (NA)
Tropical
[68]
Tropical
[196]
Subtropical (humid)
Passive Element
Purposes
Solver & Software details
Measured Parameters
3D-steady RANS, LB k-ε model FloEFD softwareMentor Graphics
Air velocity (AV) Air temperature (AT) & Relative Humidity (RH)
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
AV on spots indoor, opening & outdoor on diverse WA
Full-scale + System simulation (Thermal comfort PMV)
EnergyPlus
Indoor Average & radiant AT RH & IAV
AV, block ratio
Method
Transom Ventilation Panel (TVP)
Improving ACH through SSV & CV using TVP.
Full-scale experiment + CFD
Windcatcher
Effect of outdoor wind on flow behaviour inside wind catcher.
Wind tunnel (Closed loop) + CFD
DoubleWindow (parallel)
Save energy for the cooling purposes using double window.
Balcony (Vertical farming)
Effect of vertical farming on NV performance & thermal comfort in tropical regions.
Wind tunnel + CFD
3D-steady RANS, Reynolds Stress Model (RSM), Fluent (ANSYS)
Chimney
Maximising IAV by changing chimney’s geometry.
Full-scale experiment (prototype) + CFD Optimisation
3D quasi-steady RANS, RNG k-ε & Fluent (ANSYS)
AV, ACH, AT & solar intensity
Windows
Analysing the thermal & acoustic comfort through windows ventilation.
CFD (PMV Thermal comfort)
Standard (S)k-ε, Finite Element Method (FEM) & Fluent (NA)
No experiment
Windcatcher
Indoor Air Distribution (IAD), living area using (ACH & IAV)
Stereo Particle Image Velocimetry (SPIV) [194] + CFD
3D steady RANS, ST k-ω & SST k-ω, Sk-ε, Rk-ε, RNG kε & RSM& Fluent (ANSYS)
Flow rate (m3/s), IAV & ACH
Atrium
Thermal & airflow conditions of NV through atrium.
Full-scale experiment + CFD
SST k-ω, Sk-ε-, Realizable (R) k-ε & RNG k-ε & Fluent (ANSYS)
IAD (speed, direction & pressure) & temperature
Efficiency of NV based on heat convection and airflow over DSF Simulation of NV at the nonrectangular indoor area
Full-scale experiment (a Test cell) + CFX Wind tunnel database + coupled CFD
DSF
Windows
23
CFX (ANSYS) 3D steady RANS, Spalart Allmaras model, k-ω (ST k-ω & SST k-ω) and k-ε
Temperature on the façade (inner & outer), Air velocities Pressure coefficient (Cp), Temperature & ACH
Critical Findings The IAV could be improved by 400% through TVP depend on outdoor wind speed. ACH has also been improved by 27%. Evaluate NV over wind catchers needs more experimental methods than other elements. 60% of cooling energy was saved using NV. The Setpoint of cooling temperature has a significant effect on energy usage. NV was crucially affected by vertical farming block ratio, so vertical farming needs a suitable design concerning NV performance. Width, inclination angle & airgap, respectively, has the most sever impacts on NV performance. Night NV over windows due to less noise is active & provide sufficient fresh air & improve thermal comfort thru a specific season. Airspeed ratio, as well as ACH & Flow rate, should be considered to find IAD. RNG k-ε was the best prediction tools. Direct ventilation in the atrium improved indoor airflow. Indoor temperature reduced due to obstruction of solar radiation by DSF. NV can decrease around 65% of the cooling hours. Although NV
EnergyPlus
[197]
[70]
[198]
[200]
[201]
[26]
[202]
[204]
Desert (hot & arid)
Not a specific climate
Not a specific climate
Desert (hot & humid summer)
Temperate climate (cold)
Subtropical (humid)
Hot & humid region
Tropical
Effects of varying wind incidents angles on winddriven NV in a combination of 4sided wind catcher & courtyard. Exploring the integration of Windcatcher & Wing wall, its optimum angle & the best wing wall length on NV performance
family (Sk-ε, Rk-ε, & RNG k-ε)
Flow rate (m3/s), IAV
By neglecting stack impact, 4-sided wind catcher provides heat dissipation instead of breeze.
3D-steady RANS, Sk-ε, Rk-ε, RNG kε Fluent (ANSYS)
AV & air flow rate
The optimum length & angle provide the best NV performance considering AV, flow rate, ACH, MAA.
Full-scale experiment in test chamber [199] + CFD
3D-steady RANS, k-ω model, Fluent (ANSYS)
AT, Surface temperature, Airflow & CO2 sensors
Results highlighted vertical slide windows for providing the best NV performance.
Wind tunnel (Closed loop) + CFD (Fluent codes)
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
Indoor airflow velocity and AT
The optimum streamwise distance reduced thermal cooling capacity by 10%.
Wind tunnel (open circuit) + CFD
3D steady-state RANS, SST k-ω Fluent (ANSYS)
Wind tunnel results of [71] + CFD
Windows
Investigation of SSV performance thru typical windows types
Windcatcher with assisted heat pipes
Optimising of heat pipes that are used to improve NV performance through wind catchers
Wind Catcher & Courtyard
Windcatcher & Wing wall
DSF
Investigating NV through DSF
Balcony
Impact of balconies’ features on NV performance & thermal comfort.
Trace
Impacts of Trace’ depth (porous type building) on NV using mean AV & MAA.
Void
Impact of void provision on the wind-driven NV in residential Medium Cost Multi-Storey Housing (MCMSH)
affected ACH, thermal condition was not significantly affected.
Full-scale experiment (Velocity profile & Tracer gas) + CFD Full-scale experiment + CFD (Thermal comfort (SET*)) Wind tunnel (Particle Image Velocimetry (PIV)) [203] + CFD Full-scale experiment & Wind tunnel + CFX
24
2D Unsteady RANS (URANS), Finite-volume, OpenFOAM
Airflow & AT
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
AT, IAV & Related Humidity (RH)
3D-steady RANS, k-ε turbulence model & Fluent (ANSYS)
Sk-ε, RNG k-ε & SST k-ω CFX (ANSYS)
Agreement between building simulation & CFD was remarkable in the prediction of outlet temperature & airflow profile. Incident WA is the vital balcony’s feature. SSV was more sensitive than a CV to varying design features.
IAV & ACH
Increasing on Trace’s depth has significant impacts on IAV by 88%.
AV & Thermal comfort
The suitable void configuration suggested, and results may contribute to better NV performance over void at MCMSH.
[205]
[206]
[207]
[209]
[28]
[212]
[214]
[215]
[216]
Results highlighted the excellent potential of voids for MCMSH in the tropical climate. Close & CV courtyard can attain thermal comfort and avoid unnecessary humidity. Varying width has significant effects on IAD & AV. It is suggested to use this method for optimising wind catcher in other climates. A specific geometry including inclination angle, length, width & air gap, introduced as the optimal design. Coupled CFD methods (finding indoor and outdoor flowrate at once) is useful to assess NV performance. A mixture of vertical & tilted walls, respectively, at upper & lower floors, had the best NV performance. For investigating orientation, the unit layout should be considered.
Void
Finding voids’ potential for NV in residential MCMSH
Wind tunnel [170]+ CFX
Sk-ε & CFX (ANSYS)
Wind pressure distributions on façade in different WA (°)
Courtyard
Effects of internal courtyards on NV to find innovative strategies for urban houses
Full-scale experiment
NA
AT, RH, and air pressure
Windcatcher
Study the best airflow & thermal comfort in six design scenarios of wind catcher (width & height).
3D steady-state RANS, Sk-ε, Rk-ε, RNG k-ε, SST k-ω & Fluent (ANSYS)
AT, AV & RH
Chimney
Achieve optimum NV through solar chimney by finding the optimal geometry.
3D-steady RANS, RNG k-ε & Software (NA)
Flow rate, AT & external AV, Solar radiation
Balcony
Influences of façade shape and openings on wind-induced NV (MAA & ACH)
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
IAV, ACH, outdoor wind speed & pressure distribution
Hot & dry
Atrium
Impact of atrium’s wall angularity on NV performance & thermal comfort.
CFD + Previous analytical models [213]
3D-steady RANS, RNG k-ε & Software (NA)
No experiment
Tropical
Balcony & Window
Full-scale experiment
No simulation
Indoor AT, RH, and air velocity
k-ε model & Fluent (NA)
Indoor & outdoor AT, humidity & AV
SV is the best NV strategy in Yinzi house based on the validated simulation results.
Wind speed, Flow rate & ACH
Large windows on the façade enhance NV performance. Provision of loggia reduces ACH except for the direct airflow to opening.
Tropical
Tropical
Desert (hot & arid)
Desert (hot & arid)
Subtropical (humid)
Subtropical (humid)
Mediterranean climate (hot & arid summer)
Patio
Windows & Loggia
[217]
Not a specific climate
Windows
[218]
Not a specific climate
Void & Lightwell
Impacts of orientation & height of buildings on NV. Find NV pros & cons in Yinzi, traditional Chinese, house as well as the best NV strategy. Effect of loggia & window opening size & façade porosity on CV rate. Finding an innovative design for windows to get the highest NV & lower dispersion of rain. Impact of horizontal &
Wind tunnel + another simulation [208] + CFD (Thermal comfort PMV & PPD) Full-scale experiment (prototype) + CFD Optimisation Wind tunnel [210]+ CFD (Subconfiguratio n validation [211])
Full-scale orthogonal experiment + CFD Full-scale experiment (tracer gas method) & empirical + CFD
3D-steady RANS, RNG k-ε & RSM & Fluent (ANSYS)
Wind tunnel (PIV) + CFD
k-ε model & Fluent (ANSYS Airpack)
AV, ventilation Flow rate (m3/s)
Rain penetration was dropped by 98%, while NV rate decreased by 4 & 9 % in defined scenarios.
Wind tunnel [219] + CFD
3D-steady RANS, RNG k-ε, Rk-ε,
AT & Airflow rate & pattern
Void & lightwell had substantial effects on
25
vertical position of connected to lightwell void on the upward airflow.
[220]
[186]
[222]
[223]
[147]
Hot & arid
Windows
Mediterranean climate (hot & arid summer)
Mediterranean (hot & arid summer)
Subtropical (humid)
Continental (humid)
Patio
Windows & overhang
Atrium
Windows
Focus on the indoor airflow & thermal comfort in a naturally ventilated room with a window opening. Explore aerodynamic features in a residential unit with a patio that connects indoor & outdoor. Effect of windows’ overhangs on thermal mass & night NV to provide a guideline for overhang’s length. Optimum design of atrium for the NV utilisation using validated CFD, which was not well studied before. Find the status of opening windows habit in winter via survey and the reflection of this habit on thermal comfort.
SST k-ω & SST & Fluent (ANSYS)
Wind tunnel (open circuit) [221] + CFD & Network model + CFD & (PMV & PPD)
Wind tunnel + CFD
Full-scale experiment + Dynamic simulation
k-ε model & Fluent (NA)
3D-steady RANS, k-ε model & Software (NA)
TRNSYS software
Full-scale experiment + CFD
k-ε, RNG k-ε & Large Eddy Simulation (LES) & Fluent (NA)
Full-scale experiment (Tracer gas) + Survey & Interview
Data analysis of survey by SPSS (Crosstab and Chisquare)
upward airflow in the interior of lightwell. Wind direction was the most crucial parameters that affect airflow pattern.
AT, AV & Pressure coefficient (Cp)
Window location is the most crucial factor in NV & thermal comfort as PMV & PPD improved up to 12% & 3.5% for the best location.
AV, Airflow profile
Enhancing the indoor airflow & modifying outdoor microclimate (around the building) can improve thermal comfort.
Wind speed & direction, indoor & outside AT, RH
NV integrated with horizontal shading devices, enhance thermal comfort & decrease cooling demand.
AT, AV
Modelling shows bulk downward airflow that highlights the requirement of using precise simulation in atrium design.
Air change rate, AT, feeling of IAQ (by survey)
Effects of window opening size, wind direction & room size on the air change rate in winter were found based on results.
The main results of Table 4 can be summarised as below:
469 470
•
Most of the studies were carried out in climates that are recognised with hot summer.
471
•
A combination of CFD simulation and experimental analysis as a validation tool was the
472
standard method.
26
473
•
CFD was the standard method (via ANSYS) reported in literature review and k–ε models
474
were the most applied model for simulating airflows indoor and outdoor of the buildings,
475
which has also been highlighted in previous studies [28, 169, 224-226].
476
•
measured in most of the experimental studies.
477 478
Indoor air temperature and velocity, which directly affect indoor thermal comfort, was
•
There is a small number of full-scale in-situ experimental studies that highlight the needs for more in-situ measurement.
479 480
•
481
5.2.1.
The significant impacts of openings’ geometry were observed through critical findings. System Simulation
482
CFD is an excellent method that can be alternatively used for measuring the physical parameters in
483
the possible and vital scenarios [227-229]. While this simulation tool might not be a perfect tool for
484
the whole system parameters such as energy indexes in spaces under NV mode and it is better to
485
couple CFD with a whole building energy simulation model such as EnergyPlus [173]. Furthermore,
486
the enormous calculation time of 3D CFD analysis with a very satisfactory mesh can always be a time
487
constraint, so it is a rational solution to find appropriate tools for system simulation.
488
Energy modelling software, in general, predicts the energy consumption of buildings based on
489
various parameters such as cooling and heating load. These simulation tools are useful to design since
490
these tools predict thermal comfort and IAQ for the whole built environment. These are also excellent
491
facilities to determine the energy-saving potential for more accurate retrofitting of buildings (after
492
construction) or design of new structures based on the possible devices [230, 231]. Improved
493
solutions regarding passive design technics can also be determined using these tools [232], which is
494
the reason for applying this software in the current context. Energy simulation methods, overall, seek
495
optimum energy consumption and appropriate thermal comfort simultaneously.
496
There are various energy modelling software, EnergyPlus [233-235], ESP-r [65, 236, 237],
497
TRNSYS [238, 239], IDA Indoor Climate and Energy (IDA ICE) [240], Integrated Environmental
498
Solutions- Virtual Environment (IES-VE) [241, 242], CONTAM [243, 244], and COMIS [245] are
499
some of the most common software for energy simulation inside buildings [246]. These simulation
27
500
tools, as mentioned, typically employ input data, including the geometry of buildings, weather data,
501
internal load, HVAC data, and other required data to simulate required energetic factors [247]. The
502
current review investigates the characteristics, applications, and the capabilities of the available
503
software to find appropriate tools to assess NV performance in buildings. Hence, the suitability,
504
capabilities, advantages, and drawbacks of simulation software are compared and summarized in
505
Table 5 [232, 248-250].
506
Table 5. A comparison between the most applied system simulation software Energy Plus
ESP-r
TRNSYS
IDA ICE
IES VE
CONTAM
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
NO NO
NO YES
NO NO
NO NO
YES YES YES YES YES YES YES
YES YES YES YES YES YES YES
YES YES NO NO YES YES YES
YES YES YES YES YES NO YES
YES YES NO YES YES YES NO
YES YES NO YES YES YES YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
NO
NO
YES*
YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
YES YES
YES YES
YES NO
YES NO
YES NO
YES YES
YES NO YES NO YES NO
YES NO NO NO NO YES
YES YES NO NO NO NO
YES NO NO NO YES NO
YES NO NO NO YES NO
YES NO NO YES NO NO
Platform
Windows, Linux, and Mac
Windows, Linux, and Mac
Windows
Windows
Windows and Mac
Windows, Linux, and Mac
Pricing
Free
Open source
Reduced price for academic
Free Trial
Free Trial
Free
Features Simulation solution Iterative resolution of non-linear systems Simulation of loads, systems, & solutions Calculation time Variable time-step Dynamic variables (transient) Entire geometry description Surfaces including floors & walls Computation of thermal balance Import & export of geometry from CAD Import and export of models Thermal comfort of occupants General calculation of buildings Controllable windows for NV Airflow through the façade openings (i.e. balconies and windows) NV (Pressure and buoyancy driven) Mix-mode ventilation (NV & Mechanical) Multi-zone airflow (by pressure network) Implementation of occupants’ behaviour Control approach (Direct input) Co-simulation Major capabilities Energy simulation of entire building Detailed component simulation Load calculations Simulation of IAQ Code compliance Mixture of flow network & CFD domain General information
28
Relevant studies (Title-ABS-KEY (“software name” and “thermal comfort” and “natural ventil*”) AND Limit to (“ENGI” OR “ENER” OR “ENVI”) ) by August 2019 Total number of found articles 44 4 14 3 4 3 Number of articles over last 5 years 22 0 6 2 2 0 Most relevant studies (Title-ABS-KEY (“natural ventil*” and “thermal comfort” and “CFD” and “software name”)) Reference [173, 251] [252] 507 * Using the hybrid ventilation manager combined with an airflow network or co-simulation
508 509
The critical conclusions from Table 5 are as below: •
system and find the critical indexes.
510 511
EnergyPlus is standard software that has most of the required capabilities to evaluate a whole
•
EnergyPlus cannot directly predict IAQ, which was the most investigated parameter based on
512
the reviewed literature in Table 3 and Table 4. For solving this drawback, authors have
513
usually coupled EnergyPlus with CONTAM for finding IAQ [253].
514
•
ventilated space was remarkably higher than other software.
515 516
The number of articles used EnergyPlus to carry out energy modelling in a naturally-
•
EnergyPlus seems to be a standard tool for evaluating NV performance.
517 518
6. Summary and Suggested Future Studies
519
Although designers and researchers have increasingly considered NV to reduce GHG emissions
520
and energy consumption, there are not comprehensive review studies to investigate the impacts of
521
design-related parameters of passive elements on NV performance and occupations’ perception. The
522
current article, therefore, has comprehensively reviewed the articles on NV through façade openings,
523
particularly balconies that are the key focus of the current study. For this purpose, the current article
524
focuses on technical and socio-technical impacts of designing façade openings on NV, as two main
525
objectives of this review.
526
As a beginning step, a comparison between the numbers of studies on NV through several passive
527
elements using Scopus database indicated that many studies have focused on the balconies, while a
528
small proportion (around 2%) of them investigated the NV through balconies. Besides, very few
529
articles focused on the impacts of design-related parameters on the NV performance, reviewed in
29
530
Table 2. The literature shows that there is an essential need for studies to precisely investigate the
531
effects of some design-related parameters of balconies, such as the interaction between depth size and
532
orientation or H/D unitless factor, which has never been studied yet.
533
The review also revealed that SSV and CV were not identically affected by changing design
534
features of balconies, and SSV is more sensitive to these variations than CV and SV. Hence, the
535
impacts of designing geometries on SSV performance worth to investigate because most of the
536
apartments rely on SSV, as the only option for NV utilisation. The detailed review of the design
537
features of balconies, however, shows there is not any clear outcome regarding the impacts of
538
different geometric factors on NV performance.
539
For exploring the critical socio-technical factors, occupants’ perceptions and behaviour impacts on
540
the NV utilisation, as well as the effects of design-related factors, were reviewed using the literature
541
on POE studies. The current article, indeed, reviewed POE studies on NV utilisation through different
542
façade openings, specifically balconies. Table 3 summarised the recently published POE studies on
543
NV based on primary purposes, methods, case studies, findings, and other critical issues. Researchers
544
have usually selected workspaces for POE studies, which is easy to collect data, and they focused on
545
IEQ, and thermal comfort were the most common purposes of the POE studies.
546
Although the literature shows POE studies explored the logical relations among environmental
547
factors, satisfaction, behaviour, culture, and awareness of users regarding available ventilation
548
devices, the authors have not explicitly focused on the application of façade openings, particularly
549
balconies, for NV utilisation and not asked any questions regarding the geometry impact on NV
550
utilisation by occupants. Additionally, most of these POE studies were carried out in dominant
551
cooling areas such as tropical and subtropical climates, while the severe climate in summer,
552
nowadays, is happening in some other regions such as Mediterranean climate.
553
The present article reviewed the conventional methods for the evaluations of the socio-technical
554
and technical factors in section 5. This study comprehensively investigates the applied evaluation
555
methods of NV performance based on the physical parameters such as ACH, MAA, IAV, and flow
556
rate through literature. For predicting these parameters, applied methods are usually categorised into
557
empirical, analytical, and experimental methods. Table 4 shows the authors widely employed a 30
558
combination of analytical and experimental studies and suggested this approach as the most standard
559
and practical method. Although most of the recently published studies employed a combination of
560
simulation and experimental studies, a significant proportion of these studies employed the results of
561
experiments in literature such as wind tunnel outcomes. This issue highlights the need for
562
measurements, including both in-situ full-scale and small-scale experimental studies, specifically for
563
regions that have recently joined to regions with hot summer.
564
Regarding simulation details, 3D steady-state RANS and k-ε models follow by k-ω, were the most
565
applied solver and turbulence models and recruited in CFD simulations mostly through Fluent in
566
ANSYS software. Thermal comfort as one of the essential criteria for naturally-ventilated was also
567
evaluated mainly by PMV and PPD indexes [121]. Finally, although finding an optimum design of
568
passive elements, amongst balconies, were considered in the literature, there are not any
569
classifications of geometric factors impacts on NV performance and thermal comfort.
570
The next section of the current studies explored the system simulation tools to simulate the energy
571
indexes in spaces under NV mode. For finding the best software to simulate the whole system, Table
572
5 provides a comparison between the most well-known and applied software based on critical criteria.
573
Based on this comparison, EnergyPlus is standard software with the required capabilities to evaluate a
574
whole system and find the critical indexes. EnergyPlus and TRNSYS, as the first and second highest
575
employed software, were recruited in 60% and 20% of the published articles, respectively.
576 577
The following recommendations for the future studies are concluded from what has elaborated above and summarised as the following points:
578
Identification and classification of the different design features of balconies based on their
579
impacts on the NV performance and thermal comfort, specifically in high-rise multi-storey
580
residential buildings.
581
POE study on the impacts of façade openings design, specifically balconies’ geometry, on the
582
occupants’ perceptions, comfort, and behaviour, and analysing the collected feedbacks,
583
specifically in residential areas.
584
POE study in regions formerly recognised with a cool summer, but the GHG emission,
585
nowadays, changed the climate in this region. 31
586
There is a need for studies on thermal comfort standards in different climates, particularly the
587
regions with increasing occurrence of heat waves or prolonged summer overheating in
588
buildings.
589
The current review suggests a study that comprises a combination of POE, simulation, and
590
experimental study. This study could validate the ideas and feedbacks from POE studies by
591
using validated simulation.
592 593
7. Conclusion
594
The current article focuses on the technical and socio-technical impacts of designing façade
595
openings, specifically balconies, on NV performance and thermal comfort through a comprehensive
596
review. The early results show that the application of balconies for NV utilisation has not been
597
adequately investigated yet. The detailed review also recommends that more studies are required to
598
reveal the impacts of design-related parameters of balconies. Besides, the literature review revealed
599
that there is an insufficient number of small and full-scale experiments. Hence, this article strongly
600
suggests identification and classification of the most crucial design feature of balconies through a
601
study that comprises both simulation and experimental study, as a validation tool.
602
This article also explores the impacts of designing passive elements on socio-technical parameters,
603
which affected by different cooling devices. The review highlights that researchers mostly explored
604
the health and comfort factors at the indoor environmental areas without investigating the impacts of
605
the designing process. Therefore, this study suggests more POE studies that focus on the impacts of
606
designing façade openings on the occupants’ perception and comforts. Besides, this study
607
recommends residential buildings for these POE studies due to a limited number of POE studies on
608
the residential areas. Additionally, the residential spaces are unknown compared with workspaces and
609
residents have more freedom to use different cooling devices such as NV. On the other hand, this
610
review recommends POE studies in the climates that have been significantly impressed by climate
611
change. Finally, a combination of both technical and socio-technical parameters can be the title of
32
612
comprehensive research that investigates the design-related parameters as well as occupant’s
613
perception through a validated simulation and a POE study.
614 615
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1169
42
Table 1. Number of publications on NV thru passive design elements by August 2019 Rank Passive elements Period Number of studies* 2015 to 2019 334 1 Windows Before2015 495 2015 to 2019 74 2 Chimney Before2015 119 2015 to 2019 21 3 Atrium Before2015 83 2015 to 2019 32 Double skin façade 4 (DSF) Before2015 77 2015 to 2019 42 5 Wind catcher Before2015 31 2015 to 2019 27 6 Courtyard Before2015 45 2015 to 2019 23 7 Wind tower Before2015 27 Balcony (or porch or 2015 to 2019 10 8 veranda) Before2015 26 2015 to 2019 10 9 Void Before2015 10 2015 to 2019 7 10 Wing Wall Before2015 4 * This numbers are recorded with limitation to engineering or energy or environment sciences in Scopus
1
Table 2. Literature on the influence of balcony design parameters on NV performance Balcony design parameters* Row
1
2
Ref
[25]
[69]
Ventilation mode &
Balcony Type
Studied Features
Open and semi-open
D/L (%) = 0, 10, 20, 30 & 40 WA(º)= 0, 45, 90 & 180
SSV
Open
Availability of balconies, upper & lower vents at balconies UL= 4, 5 & 6 (at the End (E) and Middle (M)) Availability of balconies & location D=1.5 and 3 m UL= 1 to 12 WA(º)= 0, 45, 90
CV & SSV
3
[24]
CV
Semi-open (balcony with wing wall)
4
[68]
CV & SSV
Open
5
[70]
CV & SSV
Open
6
[71]
CV & SSV
Open
7
[22]
CV & SSV
Open
Availability of balconies UL= 3 & 4, WA(º)= 0 & 45 OS (single & double)= 0.9 & 1.8 m Opening locations= 2 models (middle=1.8m, left & right= 0.9m) UL= 1 to 12 & WA(º)= 0 & 45 Availability of balconies UL= Ground to 5 WA(º)= 0, 22.5, 45, 67.5 & 90 Availability of balconies UL= Ground to 12 WA (º)= 0 & 45 Availability of balconies OS= 6 scenarios (with &without balconies, Small and Big opening at Middle & End), UL= Ground to 5
Best Scenario or Classification Open balcony, CV & D/L=10%, WA=0º Deeper balcony lead to lower NV performance Upper and lower vents at middle floors enhance the NV rate and make airflow recirculation UL=4E with balcony Available balcony (with regards to opening’s location), WA=0º & UL=10 Deeper balcony lead to lower NV performance Not Available (Best method is steady-state RANS) For CV, WA=0º & UL= 8 & 9 For SSV, with balcony, WA=45º & UL= 10 is the best Adding balconies increased NV rate intermediate levels (UL= 2, 3, 4), best UL= 3 & WA(º)= 0 1- Highest NV rate: CV without balcony, 2- SSV with balcony (WA=45º) was the best CV: Ground level with balcony & UL=G & 3 without balcony (small opening) SSV: UL=4 with balcony, UL= 4 (without balcony big opening) Based on the payback results, with balcony at SW
8
[72]
CV & SSV
Open
9
[73]
SSV
Open
10
[26]
SSV
Open
11
[74]
CV & SSV
Open
12
[75]
SSV
Open
Availability of openings or balconies, OS (33 models)
Different balcony & opening configurations significantly change airflows.
13
[76]
CV & SSV
Open
Availability of balconies UL= Ground to 5 WA(º)= 0 & 90
Available balcony at WA=90º& D=1.5m.
Availability of balconies O= N, S, E, W, NE, SE,SW Availability of balconies Opening: 2 vertical & 1 horizontal UL= Ground to 5 D= 0.75, 1.5, 3m, WA(º)= 45 & 90 Balustrade with & without solid Availability of balconies or/and wing wall or/and overhang WA(º)= 0, 45, 90 & 180
2
Best Scenario: with balcony, UL=5, vertical opening& WA=90º Best Scenario for the NV through balcony: Not Available
Table 3. POE studies on the NV usage Ref
Building Type
Climate
Green Feature (s)
Purposes of POE
Methods
NV
Subjective perceptions when sitting, walking & running under NV vs MV
Questionnaire (Likert Scale) & Physical measurement
T-test using SPSS
NV
Perceived IAQ & Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
PMV & Thermal Sensation Vote (TSV)
PMV & TSV
Data Analysis
[119]
Workplace (office)
Subtropical (humid)
[120]
Learning places (classrooms)
Between semiarid & humid subtropical
[121]
Workplace (office)
Cold tropics
NV
Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
[122]
Learning places (High school)
Tropical
NV through windows
Thermal comfort
Questionnaire (Likert Scale)
Thermal comfort vote & TSV
Residential
Five regions contain very cold, cold, hot summer & cold winter, mild, & hot summer and warm winter
NV through windows
Usage of NV vs MV in five different climate zones
Questionnaire (bipolar between NV & MV) & Physical measurement
Statistical analysis (Mean rating)
Subtropical (oceanic)
Natural Light (NL), NV& MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Likert Scale) based on Building Use Studies (BUS)
Statistical analysis (Mean rating)
Subtropical (humid)
NV & NL through windows
IEQ (air, noise, lighting & health), Building Design (BD) & Facilities Management (FM)
Questionnaire (BUS) - Likert Scale
T-test
Tropical
NV & MM through windows
IEQ (air, noise & lighting) & thermal comfort & Adaptive behaviour
Questionnaire (Likert Scale) & Physical measurement
ANOVA using SPSS TSV & Spearman correlation coefficient
Mediterranean climate
NV & NL
Tropical
NV & NL
IEQ (air & lighting) & Thermal comfort Thermal and overall comfort
Questionnaire (Fanger approach) Questionnaire (Likert Scale)-
PMV, TSV & PD using MATLAB Pearson correlation
[123]
[124]
[125]
[126]
[101] [67]
Workplace (office)
Learning places (5 universities)
Residential (dormitory)
Learning places (primary school) Residential (college)
3
Critical Findings The decreasing magnitude of acceptable temperature was more extensive under AC compared to NV. Measured thermal comfort was less than the PMV. The occupants’ density affected perceived IAQ but not thermal sensation. ASHRAE adaptive model recommends comfort temperature less than TSV. Although the majority of students accepted the temperature, most of them preferred lower temperature. Thermal comfort has priority to IAQ for occupants. Health was the crucial factor that led to preferring MV. NV & MV periods, respectively, have direct & reverse trends with rising outdoor temperature. Office under NV mode slightly more satisfied than MM. NV provides more comfort than MM, as well. Although Green buildings’ occupants are more consistently satisfied than non-green for BD & FM, IEQ satisfaction is lower in non-green buildings. BD affects occupants’ behaviour. Occupants in tropical felt thermal comfort in higher temperature than ASHRAE. Clothing, Higher IAV & MM with NV & Fan were vital adjustments. Thermal satisfaction was significantly different for teachers & pupils. Application of BDS, which assimilates
through balconies
[128]
Residential
Tropical
under Bioclimatic Design Strategies (BDS) [127]
NV
Thermal comfort & pleasant sleep environment in bedrooms & behaviour
BUS & Experiment
Questionnaire (Likert Scale)
Statistical analysis (Mean rating)
Questionnaire (Likert Scale)
PMV, SET*, ET*, PPD, Mean radiant temperature & Heat stress index(HSI)
[100]
Hospitals & Shopping centres
Tropical
NV
Thermal, humidity, air movement sensation & thermal comfort
[129]
Residential (dormitory)
Humid continental
NV through windows
Thermal comfort & IAQ
Questionnaire (Likert Scale)
PMV
[34]
Workplace (office)
Subtropical (oceanic)
Advance d NV & MM
Thermal comfort (static & dynamic)
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
[130]
Learning places (university)
Temperate (Sheffield)
NV & NL
Thermal comfort & Energy efficiency
Questionnaire (Likert Scale)
PMV & t-test
semicontinental
NV through a balcony
IEQ, thermal comfort through different layouts & cooling types (MV & NV)
Domestic questionnaire (Likert Scale) based on (BUS)
Statistical analysis using NVivo software package
Subtropical & Tropical
NV, daylight & view, green space
Health perceptions (physical & psychological)
Cross-sectional questionnaire (Importance & Likert scale)
T-test
NV & NL
IEQ, overall satisfaction (thermal, air & lighting) & energy usage
Questionnaire (Likert Scale) from previous study [135]
T-test, ANOVA using SPSS V18.0
[95]
Residential
[131]
Workplace (office) morphology
[132]
Residential
Subtropical
4
physiology, climatology & building physics, has significantly enhanced overall comfort except for NL. Older people & outdoor workers use more NV & fans instead of AC that may show the impact of users’ adaptability. Two comfortable temperature ranges were defined for hospitals & shopping centres that challenge the ASHRAE PMV thermal comfort. Results show NV & thermal comfort trends & the upsurge of the NV areas decrease the thermal comfort. Authors developed a model for a fair NV usage for adequate thermal comfort. Thermal comfort is satisfactory in summer, but dissatisfaction occurred in winter. Static & dynamic thermal comfort matched with POE results in summer & winter, respectively. Environmental control by users improved comfort perception. The Gap between energy performance & comfort can be field using POE results & prediction. Find challenges of designing & critical issues to help researchers, designers & managers for the future projects. There is an association between green features & health perceptions in offices. This article contributes to justify & optimise passive climateadaptive design strategies. A structural model was developed based on the relationship between IEQ, satisfaction & energy usage to enhance IEQ & satisfaction
[21]
Residential
Subtropical
NV
Common usage of balcony & overall comfort & sensation of NV usage thro balconies IAQ, Indoor thermal sensation, windows opening habit
Questionnaire (Likert Scale, importance & rating scale) & Interview
SPSS (Crosstab & Chi-square)
Questionnaire (Likert Scale) & Interview
Statistical analysis by SPSS
[133]
Residential
Continental (humid)
NV through windows
[134]
Workplace (office)
Different climate in China
NV, NL & MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Importance & Likert scale)
ANOVA test
[135]
Workplace (office)
Subtropical
NV
Comfort & design satisfaction, needs, health & productivity
Questionnaire (BUS) - Likert Scale
T-test
[136]
Workplace (office)
Between semiarid & humid subtropical
NV through windows
Thermal comfort & IAQ
Questionnaire (Likert Scale & Bipolar) & Physical measurement
PMV & TSV
[137]
Learning places (university)
Tropical
NV through windows
IEQ (air, noise, lighting & cooling device & design) & overall comfort
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
[98]
Workplace (office building)
NV
IEQ
Questionnaire (BUS) - Likert Scale & Physical measurement
Pearson correlation
[138]
Workplace (university office)
NV & NL
IEQ (air, noise & lighting) & thermal comfort & forgiveness factor
Questionnaire (Likert Scale)
PPD for NV, AC & Mix based on CBE of Berkeley database
Subtropical (humid)
NA
5
Residents significantly prefer NV to achieve thermal comfort compared with AC in the subtropical climate of Brisbane. People behaviour & habits of opening windows based on room & windows opening size in winter was cleared based on POE results. MM ventilation is very sensible picks for green buildings for high satisfaction. Recommend more awareness & forgiveness factors for green buildings’ users. IAQ has a significant impact on IEQ acceptance. Warm neutral temperature found 20 °C (good agreement with Chinese standard). Occupants could achieve thermal comfort without AC, but need for more information to get the optimum usage of NV. Around 90% was satisfied & most of the dissatisfactions occurred due to chiller (staffs work close to vent). Occupants who are usually using AC expressed more negative evaluations (low forgiveness factor); in contrast, the MM and NV buildings.
Ref
[173]
[174]
[175]
[176]
[177]
[178]
[179]
Table 4. Evaluation methods of NV through different passive elements Climate Passive Solver & Purposes Method types Element Software details
Tropical
Not a specific climate
Transom Ventilation Panel (TVP)
Improving ACH through SSV & CV using TVP.
Full-scale experiment + CFD
Windcatcher
Effect of outdoor wind on flow behaviour inside wind catcher.
Wind tunnel (Closedloop) + CFD
Measured Parameters
Critical Findings
3D-steady RANS, LB k-ε model FloEFD softwareMentor Graphics
Air velocity (AV) Air temperature (AT) & Relative Humidity (RH)
The IAV could be improved by 400% through TVP depend on outdoor wind speed. ACH has also been improved by 27%.
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
AV on spots indoor, opening & outdoor on diverse WA
Evaluate NV over wind catchers needs more experimental methods than other elements.
Subtropical (humid)
DoubleWindow (parallel)
Save energy for the cooling purposes using double window.
Full-scale + System simulation (Thermal comfort PMV)
Tropical & Subtropical
Balcony (Vertical farming)
Effect of vertical farming on NV performance & thermal comfort in tropical regions.
Wind tunnel + CFD
3D-steady RANS, Reynolds Stress Model (RSM), Fluent (ANSYS)
Chimney
Maximising IAV by changing chimney’s geometry.
Full-scale experiment (prototype) + CFD Optimisati on
3D quasi-steady RANS, RNG k-ε & Fluent (ANSYS)
Windows
Analysing the thermal & acoustic comfort through windows ventilation.
CFD (PMV Thermal comfort)
Desert (hot & arid)
Tropical
Not Available (NA)
EnergyPlus
Indoor Average & radiant AT RH & IAV
AV, block ratio
60% of cooling energy was saved using NV. The Setpoint of cooling temperature has a significant effect on energy usage. NV was crucially affected by vertical farming block ratio, so vertical farming needs a suitable design concerning NV performance.
AV, ACH, AT & solar intensity
Width, inclination angle & airgap, respectively, has the most sever impacts on NV performance.
Standard (S)k-ε, Finite Element Method (FEM) & Fluent (NA)
No experiment
Night NV over windows due to less noise is active & provide sufficient fresh air & improve thermal comfort thru a specific season.
Windcatcher
Indoor Air Distribution (IAD), living area using (ACH & IAV)
Stereo Particle Image Velocimetr y (SPIV) [180] + CFD
3D steady RANS, ST k-ω & SST k-ω, Sk-ε, Rk-ε, RNG kε & RSM& Fluent (ANSYS)
Flow rate (m3/s), IAV & ACH
Airspeed ratio, as well as ACH & Flow rate, should be considered to find IAD.
Full-scale experiment + CFD
SST k-ω, Sk-ε-, Realizable (R) k-ε & RNG k-ε & Fluent (ANSYS)
IAD (speed, direction & pressure) & temperature
Full-scale experiment (a Test
CFX (ANSYS)
Temperature on the façade (inner & outer),
[181]
Tropical
Atrium
Thermal & airflow conditions of NV through atrium.
[60]
Tropical
DSF
Efficiency of NV based on heat convection and
6
RNG k-ε was the best prediction tools. Direct ventilation in the atrium improved indoor airflow. Indoor temperature reduced due to obstruction of solar
airflow over DSF
[182]
[62]
[183]
[185]
Desert (hot & arid)
Not a specific climate
Not a specific climate
Desert (hot & humid summer)
[186]
Temperate climate (cold)
[25]
Subtropical (humid)
[187]
[189]
Hot & humid region
Tropical
Wind Catcher & Courtyard
Windcatcher & Wing wall
Effects of varying wind incidents angles on winddriven NV in a combination of 4sided wind catcher & courtyard. Exploring the integration of Windcatcher & Wing wall, its optimum angle & the best wing wall length on NV performance
Windows
Investigation of SSV performance thru typical windows types
Windcatcher with assisted heat pipes
Optimising of heat pipes that are used to improve NV performance through wind catchers
DSF
Investigating through DSF
NV
Balcony
Impact of balconies’ features on NV performance & thermal comfort.
Trace
Impacts of Trace’ depth (porous type building) on NV using mean AV & MAA.
Void
Impact of void provision on the wind-driven NV in residential Medium Cost Multi-Storey Housing (MCMSH)
cell) + CFX
Air velocities
Wind tunnel (open circuit) + CFD
3D steady-state RANS, SST k-ω Fluent (ANSYS)
Wind tunnel results of [63] + CFD Full-scale experiment in test chamber [184] + CFD Wind tunnel (Closedloop) + CFD (Fluent codes) Full-scale experiment (Velocity profile & Tracer gas) + CFD Full-scale experiment + CFD (Thermal comfort (SET*) ) Wind tunnel (Particle Image Velocimetr y (PIV)) [188] + CFD Full-scale experiment & Wind tunnel + CFX
7
radiation by DSF.
Flow rate (m3/s), IAV
By neglecting stack impact, 4-sided wind catcher provides heat dissipation instead of breeze.
3D-steady RANS, Sk-ε, Rk-ε, RNG kε Fluent (ANSYS)
AV & air flow rate
The optimum length & angle provide the best NV performance considering AV, flow rate, ACH, MAA.
3D-steady RANS, k-ω model, Fluent (ANSYS)
AT, Surface temperature, Airflow & CO2 sensors
Results highlighted vertical slide windows for providing the best NV performance.
Indoor airflow velocity and AT
The optimum streamwise distance reduced thermal cooling capacity by 10%.
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
2D Unsteady RANS (URANS), Finite-volume, OpenFOAM
Airflow & AT
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
AT, IAV & Related Humidity (RH)
3D-steady RANS, k-ε turbulence model & Fluent (ANSYS)
Sk-ε, RNG k-ε & SST k-ω CFX (ANSYS)
Agreement between building simulation & CFD was remarkable in the prediction of outlet temperature & airflow profile. Incident WA is the vital balcony’s feature. SSV was more sensitive than a CV to varying design features.
IAV & ACH
Increasing on Trace’s depth has significant impacts on IAV by 88%.
AV & Thermal comfort
The suitable void configuration suggested, and results may contribute to better NV performance over void at MCMSH.
[190]
[191]
Tropical
Tropical
Void
Finding voids’ potential for NV in residential MCMSH
Wind tunnel [156]+ CFX
Sk-ε & CFX (ANSYS)
Wind pressure distributions on façade in different WA (°)
Courtyard
Effects of internal courtyards on NV to find innovative strategies for urban houses
Full-scale experiment
NA
AT, RH, and air pressure
Windcatcher
Study the best airflow & thermal comfort in six design scenarios of wind catcher (width & height).
Chimney
Achieve optimum NV through solar chimney by finding the optimal geometry.
Balcony
Influences of façade shape and openings on wind-induced NV (MAA & ACH)
Hot & dry
Atrium
Impact of atrium’s wall angularity on NV performance & thermal comfort.
[199]
Tropical
Balcony & Window
[200]
Subtropical (humid)
[192]
[194]
[27]
[197]
Desert (hot & arid)
Desert (hot & arid)
Subtropical (humid)
Patio
Impacts of orientation & height of buildings’ on NV. Find NV pros & cons in Yinzi, traditional Chinese, house as well as the best NV strategy.
[201]
Mediterranean climate (hot & arid summer)
Windows & Loggia
Effect of loggia & window opening size & façade porosity on CV rate.
[202]
Not a specific climate
Windows
Finding an innovative design for windows to get
Wind tunnel + another simulation [193] + CFD (Thermal comfort PMV & PPD) Full-scale experiment (prototype) + CFD Optimisati on Wind tunnel [195]+ CFD (Subconfigurati on validation [196])
3D steady-state RANS, Sk-ε, Rk-ε, RNG k-ε, SST k-ω & Fluent (ANSYS)
AT, AV & RH
Varying width has significant effects on IAD & AV. It is suggested to use this method for optimising wind catcher in other climates.
3D-steady RANS, RNG k-ε & Software (NA)
Flow rate, AT & external AV, Solar radiation
A specific geometry including inclination angle, length, width & air gap, introduced as the optimal design.
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
IAV, ACH, outdoor wind speed & pressure distribution
Coupled CFD methods (finding indoor and outdoor flowrate at once) is useful to assess NV performance.
CFD + Previous analytical models [198]
3D-steady RANS, RNG k-ε & Software (NA)
No experiment
Full-scale experiment
No simulation
Indoor AT, RH, and air velocity
Full-scale orthogonal experiment + CFD
k-ε model & Fluent (NA)
Indoor & outdoor AT, humidity & AV
Full-scale experiment (tracer gas method) & empirical + CFD
3D-steady RANS, RNG k-ε & RSM & Fluent (ANSYS)
Wind speed, Flow rate & ACH
Wind tunnel (PIV) +
k-ε model & Fluent (ANSYS Airpack)
AV, ventilation Flow rate (m3/s)
8
Results highlighted the excellent potential of voids for MCMSH in the tropical climate. Close & CV courtyard can attain thermal comfort and avoid unnecessary humidity.
A mixture of vertical & tilted walls, respectively, at upper & lower floors, had the best NV performance. For investigating orientation, the unit layout should be considered. SV is the best NV strategy in Yinzi house based on the validated simulation results. Large windows on the façade enhance NV performance. Provision of loggia reduces ACH except for the direct airflow to opening. Rain penetration was dropped by 98%, while NV rate
the highest NV & lower dispersion of rain.
[203]
[205]
[171]
[207]
[208]
[133]
Not a specific climate
Hot & arid
Mediterranean climate (hot & arid summer)
Mediterranean (hot & arid summer)
Subtropical (humid)
Continental (humid)
Void & Lightwell
Windows
Patio
CFD
Impact of horizontal & vertical position of connected to lightwell void on the upward airflow.
Wind tunnel [204] + CFD
Focus on the indoor airflow & thermal comfort in a naturally ventilated room with a window opening.
Wind tunnel (open circuit) [206] + CFD & Network model + CFD & (PMV & PPD)
Explore aerodynamic features in a residential unit with a patio that connects indoor & outdoor. Effect of windows’ overhangs on thermal mass & night NV to provide a guideline for overhang’s length.
Wind tunnel + CFD
decreased by 4 & 9 % in defined scenarios.
3D-steady RANS, RNG k-ε, Rk-ε, SST k-ω & SST & Fluent (ANSYS)
k-ε model & Fluent (NA)
3D-steady RANS, k-ε model & Software (NA)
AT & Airflow rate & pattern
Void & lightwell had substantial effects on upward airflow in the interior of lightwell. Wind direction was the most crucial parameters that affect airflow pattern.
AT, AV & Pressure coefficient (Cp)
Window location is the most crucial factor in NV & thermal comfort as PMV & PPD improved up to 12% & 3.5% for the best location.
AV, Airflow profile
Enhancing the indoor airflow & modifying outdoor microclimate (around the building) can improve thermal comfort.
Full-scale experiment + Dynamic simulation
TRNSYS software
Wind speed & direction, indoor & outside AT, RH
Atrium
Optimum design of atrium for the NV usage using validated CFD, which was not well studied before.
Full-scale experiment + CFD
k-ε, RNG k-ε & Large Eddy Simulation (LES) & Fluent (NA)
AT, AV
Windows
Find the status of opening windows habit in winter via survey and the reflection of this habit on thermal comfort.
Full-scale experiment (Tracer gas) + Survey & Interview
Data analysis of survey by SPSS (Crosstab and Chisquare)
Windows & overhang
9
Air change rate, AT, feeling of IAQ (by survey)
NV integrated with horizontal shading devices, enhance thermal comfort & decrease cooling demand. Modelling shows bulk downward airflow that highlights the requirement of using precise simulation in atrium design. Effects of window opening size, wind direction & room size on the air change rate in winter were found based on results.
Table 5. A comparison between the most applied system simulation software Energy Plus
ESP-r
TRNSYS
IDA ICE
IES VE
CONTAM
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
NO NO
NO YES
NO NO
NO NO
YES YES YES YES YES YES YES
YES YES YES YES YES YES YES
YES YES NO NO YES YES YES
YES YES YES YES YES NO YES
YES YES NO YES YES YES NO
YES YES NO YES YES YES YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
NO
NO
NO
YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
YES YES
YES YES
YES NO
YES NO
YES NO
YES YES
YES NO YES NO YES NO
YES NO NO NO NO YES
YES YES NO NO NO NO
YES NO NO NO YES NO
YES NO NO NO YES NO
YES NO NO YES NO NO
Platform
Windows, Linux, and Mac
Windows, Linux, and Mac
Windows
Windows
Windows and Mac
Windows, Linux, and Mac
Pricing
Free
Open source
Reduced price for academic
Free Trial
Free Trial
Free
Features Simulation solution Iterative resolution of non-linear systems Simulation of loads, systems, & solutions Calculation time Variable time-step Dynamic variables (transient) Entire geometry description Surfaces including floors & walls Computation of thermal balance Import & export of geometry from CAD Import and export of models Thermal comfort of occupants General calculation of buildings Controllable windows for NV Airflow through the façade openings (i.e. balconies and windows) NV (Pressure and buoyancy driven) Mix-mode ventilation (NV & Mechanical) Multi-zone airflow (by pressure network) Implementation of occupants’ behaviour Control approach (Direct input) Co-simulation Major capabilities Energy simulation of entire building Detailed component simulation Load calculations Simulation of IAQ Code compliance Mixture of flow network & CFD domain General information
Relevant studies (Title-ABS-KEY (“software name” and “thermal comfort” and “natural ventil*”) AND Limit to (“ENGI” OR “ENER” OR “ENVI”) ) by August 2019 Total number of found articles 44 4 14 3 4 3 Number of articles over last 5 years 22 0 6 2 2 0 Most relevant studies (Title-ABS-KEY (“natural ventil*” and “thermal comfort” and “CFD” and “software name”)) Reference [214, 234] [235] -
10
Fig. 1. Schematic of natural ventilation (NV) strategies
Highlights • • • • •
The impacts of passive elements on natural ventilation (NV) are reviewed. Few studies characterise the impact of different balcony geometries on NV. The impact of balconies on NV needs to be quantified technically and socially. Research on the effectiveness of balconies in climates with prolonged summers is suggested. This review is a reference for future research of sustainable design.
S0360-1323(19)30826-1
DOI:
https://doi.org/10.1016/j.buildenv.2019.106613
Reference:
BAE 106613
To appear in:
Building and Environment
Received Date: 31 October 2019 Revised Date:
3 December 2019
Accepted Date: 18 December 2019
Please cite this article as: Izadyar N, W, B, Garcia-Hansen V, Impacts of façade openings’ geometry on natural ventilation and occupants’ perception: A review, Building and Environment, https:// doi.org/10.1016/j.buildenv.2019.106613. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Ltd. All rights reserved.
1
Impacts of façade openings’ geometry on natural ventilation and occupants’ perception:
2
A review
3
Nima Izadyar a, Wendy Miller a,*, Behzad Rismanchi b, Veronica Garcia-Hansen c a
4 5 b
6 7 c
Energy and Process Engineering, Science and Engineering Faculty, School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, Brisbane, QLD, Australia
Renewable Energy and Energy Efficiency Group, Department of Infrastructure Engineering, Melbourne School of Engineering, The University of Melbourne, Victoria, 3010, Australia
8 9 10 11 12 13 14
*Corresponding author email: School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, PO Box 2434, Brisbane, Queensland 4001, Australia. Phone and Fax: +61 7 3138 9126 Email: [email protected]
15
Abstract
16
For centuries, natural ventilation (NV) was the smartest technique for conditioning the built
17
environment. However, in modern design, NV has not been utilised to its full potential, especially in
18
high-rise and medium-rise buildings. One of the remaining options is the application of balconies to
19
guide the airflow into the space to moderate the indoor ambient, increase the thermal comfort, and
20
reduce the need for mechanical ventilation. This article investigates literature reporting the impacts of
21
façade openings, particularly balcony, geometry on NV performance and occupants’ perception. It
22
aims to identify to what extent balconies have been considered as an NV strategy and to identify
23
research gaps in this field. This review article compared and classified different geometries’ design
24
features based on their effects on NV performance. This review paper also scrutinised the socio-
25
technical impacts of designing façade opening via Post-occupancy Evaluation (POE) methods. The
26
authors believe the POE could be the missing links between designing for NV and occupants’
27
perception. The review outcome found that most of the available literature is carried out in case
28
studies and regions with warm or hot climates that are cooling dominant. The increasing occurrence
29
of heat waves or prolonged summer overheating in buildings in traditionally heating-dominated
30
climates, however, suggests the need for research to evaluate both the technical and socio-technical
31
parameters of balcony geometry for these climates as well.
32
Keywords: Balcony; Design; Façade opening; Geometry; Natural ventilation (NV)
School of Design, Creative Industries Faculty, Queensland University of Technology (QUT), Brisbane 4001, Australia
1
Abbreviations ACH ASHRAE BDS BUS CV D DSF FEM FM GHG H/D HSI HVAC IAD IAV IAQ IEQ IES-VE IDA ICE ISO L LES MAA
Air Change per Hour American Society of Heating, Refrigerating and Air-Conditioning Engineers Bio-climatic Design Strategies NL Natural Light Building Use Studies O Orientation Cross Ventilation OS Opening Size Depth of balcony MSV Mixed-Strategy Ventilation Double skin façade MV Mechanical Ventilation Finite Element Method NV Natural Ventilation Facilities Management PIV Particle image velocimetry Greenhouse gas PMV Predicted Mean Vote Height to Depth ratio of balcony POE Post-Occupancy Evaluation Heat stress index PPD Predicted Percent of Dissatisfied Heating Ventilation and Air Conditioning Indoor Air Distribution RANS Reynolds-Averaged Navier-Stokes Indoor Air Velocity RH Relative Humidity Indoor Air Quality RSM Reynolds Stress Model Indoor Environment Quality RNG Renormalization Group Single-Sided Ventilation Integrated Environmental SolutionsSSV Virtual Environment SV Stack Ventilation IDA Indoor Climate and Energy TSV Thermal Sensation Vote International Standards Organization TVP Transom Ventilation Panel Length of the attached room URANS Unsteady RANS Large Eddy Simulation UL Unit Level Mean Age of Air
33
34
Contents
35
Abstract ............................................................................................................................................................... 1
36
1. Introduction .................................................................................................................................................. 3
37
2. Natural Ventilation (NV) ............................................................................................................................. 6
38
2.1.
Natural Ventilation (NV) Strategies....................................................................................................... 6
39
2.2.
Passive Design Elements ......................................................................................................................... 8
40
3. Design Parameters of Balcony ..................................................................................................................... 9
41
4. Socio-technical parameters ........................................................................................................................ 13
42
4.1.
43
5. Methods for evaluation NV effectiveness.................................................................................................. 19
44
5.1.
Post-Occupancy Evaluation (POE) Methods ...................................................................................... 19
45
5.2.
Evaluation Methods of NV performance ............................................................................................. 20
Application of POE to NV..................................................................................................................... 14
2
46
6. Summary and Suggested Future Studies .................................................................................................. 29
47
7. Conclusion ................................................................................................................................................... 32
48 49
Reference ........................................................................................................................................................... 33
50 51
1. Introduction
52
Climate change as a result of greenhouse gas (GHG) emissions from human activities is one of
53
the critical issues in the current century. It is estimated that buildings consume around 40% of global
54
energy and contribute more than 30% (between 30 % and 40 %) of the GHG emissions [1]. Since a
55
large percentage of these harmful emissions comes from Heating Ventilation and Air Conditioning
56
(HVAC) [2, 3], finding low or zero-carbon alternatives to HVAC is a persuasive idea to reduce GHG
57
emissions. One of these alternatives is natural ventilation (NV) [4], which can be used for cooling as
58
an alternative for Mechanical Ventilation (MV) all around the world.
59
NV, in general, is a process whereby fresh air is introduced to indoor spaces without using any
60
mechanical system [5]. In most cases, NV employs natural forces such as wind and buoyancy, to
61
move fresh air into an indoor area that occurs as results of pressure and density differences [6].
62
These forces are usually affecting the NV simultaneously and can act in isolation, or opposition, or
63
reinforce each other and sometimes operate in synergy [7]; however, one of these forces is always
64
predominant, determined using Archimedes number (less than one is wind-induced) or Froude
65
number (less than one is buoyancy forces) [8, 9]. Applying the NV strategy to modern architecture
66
and quantifying its impact on modern expectations of comfort, could demonstrate a significant
67
potential to reduce Mechanical Ventilation (MV) usage and persuade occupants of its usefulness in
68
meeting their comfort needs. Numerous studies show the remarkable potential of NV strategies for
69
ventilation purposes [10-12] and the critical priorities of these strategies compared with MV.
70
In modern architecture, various architectural elements such as windows, ventilation grills, wind
71
catchers, solar chimneys, wing walls, and overall façade system are typically considered by designers
72
for NV purposes in buildings [13-15]. Among these elements, façade design such as the provision of
73
windows, overhangs and balconies remains one of the leading technologies for NV purpose to reduce 3
74
energy consumption [16-20]. A balcony, as private outdoor space, is perceived by residents as one the
75
most desired features for providing fresh air, particularly in cooling dominant climates such as
76
tropical and subtropical regions [21]. Furthermore, other typical applications of balconies such as
77
entertaining and drying laundry suggest balcony as an essential design element, particularly in
78
residential apartments [22]. Consequently, it seems necessary to investigate balconies’ impacts on NV
79
utilisation and performance in social and technical aspects.
80
The provision of balconies, in general, changes the pressure around building façades and
81
subsequently affects the NV driving forces, including wind and buoyancy [23, 24]. Balconies mostly
82
affect outdoor and indoor airflow profiles and Indoor Air Velocity (IAV) that lead to changing the
83
indoor thermal comfort. Over the last decade, results of some studies that focused on the influence of
84
the balconies on NV performance, reveal the critical role and importance of balconies features such
85
as depth size on the indoor NV and thermal comfort in its attached room [25-28]. Undeniably, the
86
design of balconies appears to be a determinant factor of the NV performance at the purely technical
87
view. Thus, an investigation and classification of the balconies’ geometric features and their impacts
88
of the related parameters to the NV performance, such as IAV, could extract critical information in
89
the sustainable design context.
90
On the other hand, since NV utilisation has a social nature that might be affected by technical
91
design decisions on designing, there is a need to address socio-technical factors (i.e. comfort and
92
satisfaction) and their effects on the quantity and quality of the NV utilisation through balconies to
93
improve design based upon these parameters [29]. For instance, an exploration of the literature on
94
Post-Occupancy Evaluation (POE) revealed some design-related disruptive impacts such as balcony
95
scale on NV utilisation [22, 30, 31]. Subsequently, there is a significant opportunity of design
96
improvement through investigation of socio-technical factors to firstly realise the critical design-
97
related factors that have been focused in previous studies, and then find the degree of effectiveness
98
through a detailed review of these POE studies in the concept of NV through balconies.
99
The design of balconies should also be carried out with consideration of vital standards of the
100
health and comfort of attached indoor spaces. Because, a conflict between occupant satisfaction,
101
comfort, and health on one side and energy saving on the other side is usually a critical issue, which 4
102
sometimes sparks controversy over the impacts of energy saving on occupants’ comfort and health.
103
The importance of efficient and sustainable design, as well as various standards, criteria, and rules
104
for designing, are attempting to reduce the gap between the occupants’ comfort and higher usage of
105
energy in buildings. One benefit of these national or international standards such as American
106
Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) [32] is to recommend
107
criteria of living spaces to satisfy residents’ health and comforts with regards to energy saving
108
matters. Occupants also play a crucial role since they carry out the act of energy-saving. A review on
109
buildings design, as well as users’ forgiveness factor, which depends on overall comfort and average
110
satisfaction scores of ventilation or air and temperature in summer [33-35], could determine the
111
interaction between these parameters.
112
This review article aims to explore the impacts of designing balconies’ geometry on NV
113
performance and perceptions and behaviour of users, as two vital technical and socio-technical
114
factors, respectively. For this, the current paper firstly summarises the application of the most
115
considered passive design elements, for NV utilisation in building. For this, the article explores the
116
number of studies that have focused on the application of balconies for NV utilisation, the principal
117
focus of the current research, compared to other elements for passive design in Section 2. Section 3
118
focuses on studies that have investigated the influence of design features of balconies on NV
119
performance and classified the crucial parameters based on the degree of impacts reported in the
120
literature. Socio-technical factors such as occupants’ comfort are considered through an exploration of
121
the application of POE on NV utilisation through different façade openings, and specifically through
122
balconies, to find the degree of comfort, critical obstacles, and incentives, under NV mode instead of
123
MV (Section 4). The most common methods that have been employed to identify the critical design
124
elements of balconies and impacts of geometry’s features on users are investigated in Section 5.
125
Results, including research gaps, are summarized and lead to a comprehensive discussion and
126
recommendations for possible future studies to fill the gaps (Section 6). Finally, the current article
127
draws an overall conclusion in Section 7.
128
5
2. Natural Ventilation (NV)
129 130
Ventilation is employed to supply fresh air, maintain comfort (temperature and humidity),
131
eliminate or dilute contamination [36]. There are two primary types of ventilation, MV and NV,
132
which are usually applied by occupants, particularly for cooling purposes. Energy consumption
133
concerns and Global warming due to the GHG emission are the critical reasons caused that NV has
134
been considered as an appropriate alternative for MV. NV uses outside air movement and buoyancy
135
pressure differences to refresh the air and ventilate a space instead of electricity consumption, which
136
is usually applied for MV. NV technologies have been shown a significant capability for the
137
adequate cooling and thermal comfort [37-39], so NV could be an attractive option for the building
138
designers and architects to design more energy-efficient and saleable apartments.
139
Various studies reported a range of advantages of NV, compared with MV, such as less required
140
space for NV [40, 41], lower cost [42], providing reasonable thermal comfort [43, 44], less GHG
141
emission [45], and fresh air that leads to improving Indoor Air Quality (IAQ) and healthier indoor
142
area [46, 47]. There is also evidence that NV could increase the adaptability of people to the outdoor
143
environment and contribute to a higher forgiveness factor reported in some NV buildings [43]. These
144
capabilities can be solutions for critical issues of ventilation systems in the new era. For example,
145
occupying less space through an innovative passive cooling design is a remarkable capability for the
146
gradually urbanised populations who are living in cramped and small apartments. Besides, the higher
147
adaptability of occupants can lead to better thermal comfort without using MV due to the higher
148
forgiveness factor of occupants. These benefits have attracted architects attention to NV as a useful
149
ventilation process for several types and applications of buildings [48, 49], mainly for the
150
increasingly urbanised society in cities that include a large number of towers and skyscrapers [50,
151
51].
152
2.1. Natural Ventilation (NV) Strategies
153
NV strategies are mainly categorised in four strategies: Cross Ventilation (CV) [52], Single-Sided
154
Ventilation (SSV) [53], Stack Ventilation (SV) [54], and Mixed-Strategy Ventilation (MSV) [55,
155
56], displayed in Fig.1. 6
Cross-Ventilation (CV)
Stack-Ventilation (SV)
Single-Sided Ventilation (SSV)
Mixed-Strategy Ventilation (MSV)
156 Fig. 1. Schematic of natural ventilation (NV) strategies
157 158
CV and SV are both unidirectional and at least two openings, an inlet and an outlet, are required
159
for these strategies. They differ, however, in that CV is a horizontal process, and SV is a vertical
160
process. In CV (wind effect or wind-induced), openings are mainly located on two sides of a
161
building, and the pressure difference between these two openings make indoor air flows, which
162
move from higher to lower pressure [14, 57]. SV is a thermal buoyancy-driven strategy and airflow
163
arises because of the temperature gradient between the inlet and outlet. The warm air rises due to the
164
lower density and is replaced by colder air from outside.
165
In contrast, SSV describes units or apartments with only one opening or only openings on one
166
side. Examination of SSV is perhaps more applicable than SV or CV in urban environments, given
167
the higher number of apartments with single-sided openings [58]. Wind, buoyancy, or a combination
168
of these forces can lead to SSV [59, 60]. The wind and buoyancy ventilation rate (m3/s) can be
169
calculated using Equation 1 and 2, respectively [61]. ( ( ) and (
)=
)=
2 (
=
2
− ) ℎ = +
(1) (
) ℎ
(2)
170
where (
171
pressure (
172
external air density (
173
the vertical interval between openings (ℎ[ ]), and gravitational acceleration ( [
[
), respectively, represent opening discharge and pressure coefficients. Mean static !
]), air density ( ["# ]), reference velocity ( and
"
[ $ ]), area ( [
%
]), internal and
), temperature differences between indoor and outdoor ( "& ]) $
7
=
−
),
are the other
174
variables that contribute to calculating the wind and buoyancy ventilation rate.
175
Among NV strategies, although most of the apartments rely on SSV due to the predominant use
176
of only one opening at an attached indoor area, CV usually provides more fresh air and IAV than
177
SSV [62, 63]. Both the location and the opening size of design elements such as windows, balconies,
178
chimneys, courtyards, and ventilation grills could be critical points in the success of these NV modes
179
[12] and the role that element features. Selection and location of architectural elements for passive
180
design in buildings are widely studied in the literature [50, 64]. 2.2. Passive Design Elements
181 182
The effectiveness of design elements such as windows [65-67], façade system like double-skin
183
façade [68] and balconies [69], ventilation grills, wing wall and Windcatcher [70, 71], solar chimney
184
[72, 73], and integration of these systems [71] was reported in scientific literature to varying degrees.
185
For example, the application of windows for NV utilisation in buildings is reported in [74], and a
186
Scopus database search (with the keywords of “windows” and “natural ventilation” in titles, abstract,
187
and keywords, in related subject areas) reveals 829 articles on the role of windows in NV. In
188
contrast, a similar search for “wind catcher” resulted in only 80 articles. Table 1 displays the results
189
of the same search strategy for the most considered passive ventilation elements, as reported in [48].
190
Table 1. Number of publications on NV thru passive design elements by August 2019 Rank Passive elements Period Number of studies* 1
Windows
2
Chimney
3
Atrium
4
Double skin façade (DSF)
5
Wind catcher
6
Courtyard
7
Wind tower
8
Balcony (or porch or veranda)
9
Void
10
Wing Wall
2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019
334 495 74 119 21 83 32
Before2015
77
2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015 2015 to 2019 Before2015
42 31 27 45 23 27 10 26 10 10 7 4
8
191
* These numbers are recorded with limitation to engineering or energy or environment sciences in Scopus
192
This literature search reveals that far fewer studies have been published relating to the role of
193
balconies for NV, compared with most other design elements, and compared to windows. It is
194
curious given that windows and balconies are two commonly used elements in medium and high-rise
195
residential buildings in multiple climate zones and cultures globally. The Scopus database reveals
196
around 1700 research articles relating to balconies in general, however only 2% of these investigated
197
NV through balconies. It suggests that designers and researchers have not actively considered a
198
balcony as a potential passive design element to enhance or drive NV, and reveals a research gap
199
that is worth investigating [75].
200
The construction of balconies significantly affects the wind velocity and pressure profile around
201
façades [23, 76] that can lead to changing the IAV and NV performance in the attached room. The
202
impacts of balcony geometry on the NV performance was explored as a critical hypothesis by
203
researchers in some literature [25-27]. These studies debunk the null hypothesis that the geometry of
204
balconies does not impact on NV and build the case for further research in this area. The next section
205
dedicates to the literature on the impact of balcony geometry on NV.
206 207
3. Design Parameters of Balcony
208
Studies on how balcony design features affect NV performance and thermal comfort inside the
209
apartments are limited in the literature, and these parameters have not been adequately explored,
210
unlike other openings such as windows. Among the limited number of publications, a few articles
211
focused on the impacts of balcony design on the NV performance. These studies mainly explored the
212
effects of the availability of the balcony and then investigated the impact of various balcony design
213
parameters on NV performance and thermal comfort. The design parameters examined include
214
Orientation (O) or Wind Angle (WA), Unit Level (UL) within the building, Depth of balcony (D),
215
Length of the attached room (L), Depth to Length ratio (D/L %), and Opening Size (OS). A
216
summary of these studies is presented in Table 2.
217
Table 2. Literature on the influence of balcony design parameters on NV performance 9
Balcony design parameters* Row
1
Ref
[77]
2
[78]
Ventilation mode &
Balcony Type
Studied Features
Open and semi-open
D/L (%) = 0, 10, 20, 30 & 40 WA(º)= 0, 45, 90 & 180
SSV
Open
Availability of balconies, upper & lower vents at balconies UL= 4, 5 & 6 (at the End (E) and Middle (M)) Availability of balconies & location D=1.5 and 3 m UL= 1 to 12 WA(º)= 0, 45, 90
CV & SSV
3
[25]
CV
Semi-open (balcony with wing wall)
4
[76]
CV & SSV
Open
5
[79]
CV & SSV
Open
6
[80]
CV & SSV
Open
7
[23]
CV & SSV
Open
Availability of balconies UL= 3 & 4, WA(º)= 0 & 45 OS (single & double) = 0.9 & 1.8 m Opening locations= 2 models (middle=1.8m, left & right= 0.9m) UL= 1 to 12 & WA(º)= 0 & 45 Availability of balconies UL= Ground to 5 WA(º)= 0, 22.5, 45, 67.5 & 90 Availability of balconies UL= Ground to 12 WA (º)= 0 & 45 Availability of balconies OS= 6 scenarios (with &without balconies, Small and Big opening at Middle & End), UL= Ground to 5
Best Scenario or Classification Open balcony, CV & D/L=10%, WA=0º Deeper balcony lead to lower NV performance Upper and lower vents at middle floors enhance the NV rate and make airflow recirculation UL=4E with balcony Available balcony (with regards to opening’s location), WA=0º & UL=10 Deeper balcony lead to lower NV performance Not Available (Best method is steady-state RANS) For CV, WA=0º & UL= 8 & 9 For SSV, with balcony, WA=45º & UL= 10 is the best Adding balconies increased NV rate intermediate levels (UL= 2, 3, 4), best UL= 3 & WA(º)= 0 1- Highest NV rate: CV without balcony, 2- SSV with balcony (WA=45º) was the best CV: Ground level with balcony & UL=G & 3 without balcony (small opening) SSV: UL=4 with balcony, UL= 4 (without balcony big opening) Based on the payback results, with balcony at SW
8
[81]
CV & SSV
Open
9
[82]
SSV
Open
10
[27]
SSV
Open
11
[83]
CV & SSV
Open
12
[84]
SSV
Open
Availability of openings or balconies, OS (33 models)
Different balcony & opening configurations significantly change airflows.
13
[85]
CV & SSV
Open
Availability of balconies UL= Ground to 5 WA(º)= 0 & 90
Available balcony at WA=90º& D=1.5m.
Availability of balconies O= N, S, E, W, NE, SE, SW Availability of balconies Opening: 2 vertical & 1 horizontal UL= Ground to 5 D= 0.75, 1.5, 3m, WA(º)= 45 & 90 Balustrade with & without solid Availability of balconies or/and wing wall or/and overhang WA(º)= 0, 45, 90 & 180
Best Scenario: with balcony, UL=5, vertical opening& WA=90º Best Scenario for the NV through balcony: Not Available
218
Table 2 shows the small number of studies investigated the impacts of balconies’ design
219
parameters on NV performance. Among the examined parameters, orientation (or WA) and UL were
220
studied by most of the articles, while features such as D, D/L ratio, and OS have not been
221
investigated thoroughly. Some unitless factors like Height to Depth (H/D) ratio and other
222
characteristics such as balustrade type (materials, shape, height) are not represented in the literature 10
223
at all. The following paragraphs report on four critical features containing present or absent of
224
balcony, unit level, depth, and orientation, which more considered in the literature based on Table 2.
225
First, some researchers investigated the availability of balconies on façades and explored the
226
effects of NV performance on indoor areas in the present or absents of balconies [76, 81]. The
227
availability of balconies as well as the impact of the location of a balcony opening on NV
228
performance was investigated using validated simulation and experimental data (at both full-scale and
229
small-scale) [25, 84]. Results of these studies show that adding a balcony can enhance NV
230
performance, but the improvement level depends on the NV strategy (i.e. SSV and CV) and balcony’s
231
geometry [26, 80-83].
232
It was found that although SSV performance can be enhanced with appropriate balcony design, the
233
highest CV rate occurred in a scenario without any balcony on the façade [23]. Furthermore, most of
234
the studies in Table 2; highlight the significant impacts of balconies’ design parameters on NV
235
performance, but Ai et al. [80] mentioned the negligible impact of balcony geometry on CV
236
performance. This difference might have occurred because of the different airflow pathway options
237
available in the CV that caused the impacts of changing geometry was lower on CV [23, 26, 79].
238
Table 2 reveals that the latest studies have focused on SSV more than other NV strategies and
239
investigated the geometry impacts on SSV performance. Besides, a substantial proportion of
240
apartments are now more reliant on SSV than CV; therefore, the geometry impacts seem to be critical
241
in most of the case studies.
242
Second, the literature review also revealed unit levels (balconies’ height above ground), as one of
243
the most investigated parameters, affected the NV performance at an indoor area [78, 80]. Although
244
there is not a specific conclusion regarding the impacts of unit levels on NV performance through
245
balconies, table 2 shows the significant difference between the unit level impacts on SSV and CV
246
strategies [23, 80, 81, 85]. For instance, a comparison between the impacts of different unit levels, in
247
a medium height building (5 levels), on NV performance for both SSV and CV shows that the
248
ground level had the best NV performance for CV, while the best SSV performance occurred in level
249
4 [86]. Therefore, there is not a clear conclusion on the impacts of the balcony’s height on NV
250
performance that could be considered as an essential gap in further studies. 11
251
Third, the results of the previous studies highlight the depth of balconies as an essential parameter
252
that crucially affects NV performance on both SSV and CV [28, 77]. These studies reveal a deeper
253
balcony could lead to a lower NV performance at an indoor area, but the authors have not explored
254
and compared the depth impacts with regards to other feature such as orientation. Finally,
255
concerning the orientation of balconies, literature shows in-case conclusions instead of clear trends
256
or relations between the impacts of orientation and other critical design-related parameters on NV
257
performance. For example, the impacts of depth on NV performance in different orientations have
258
not been investigated and compared yet. Therefore, there is a gap in this context to find the
259
interaction between these geometric factors.
260
Even though the authors investigated these four design-related parameters of balconies, the
261
review indicates there are no adequate studies on the classification of the most crucial geometric
262
factors, and the impacts of these factors on SSV and CV were not explored and compared with each
263
other. Omrani et al. [26] studied depth, type (open and semi-open balconies) and orientation (or
264
WA), on SSV and CV performance and thermal comfort in residential buildings. This study
265
classified the mentioned parameters based on their effect on NV performance, reporting that
266
changing WA can affect the NV performance and thermal comfort more than varying depth scales
267
and types of the balcony.
268
To conclude, the key findings of this section are as below:
269
•
Adding a well-designed balcony can improve the NV performance.
270
•
The effects of adding a balcony, as well as changes to balcony geometry were not identical for CV and SSV.
271 272
•
orientation did not have the same effects on CV and SSV performance.
273 274
•
The interaction between balcony depth with other geometric factors with heights and orientation have not been investigated.
275 276
All investigated parameters containing present or absent of balcony, unit level, depth, and
•
There is no precise classification of the impact of design parameters on NV.
277
12
278
4. Socio-technical parameters
279
Because the purpose of NV is to assist in occupant comfort, it is critical to investigate the impact
280
of balcony design features on occupant sensation, comfort, and behaviour due to the social nature of
281
NV utilisation [87]. Passive designers should always be aware of drawbacks, as well as incentives,
282
that could affect the utilisation of NV through balconies. For instance, violating thermal comfort and
283
privacy are crucial factors that sometimes stop users from utilising NV, while having access to a
284
breeze, refreshing air, and better Indoor Environment Quality (IEQ) due to a proper design of
285
balconies could encourage occupants to open balcony doors [22]. Occupant feedback can assist
286
architects and designers in developing more robust and acceptable solutions. POE is a standard
287
method for seeking feedback from buildings; however, it is not universally applied in practice by the
288
design and construction industry as part of quality assurance and a continuous-improvement process.
289
POE, in general, is a qualitative procedure of collecting feedback from occupants concerning their
290
behaviour, experiences, and expectations about the performance of buildings [88, 89]. POE is
291
designed to investigate results from social, spatial design, and planning through occupants’ feedback
292
[90]. It gathers the firsthand data from users that is crucial for designers, managers and planners to
293
understand and perhaps to enhance the current status of a building. Feedbacks from building
294
occupants can highlight obstacles, as well as motivations, that may lead to improving efficiency and
295
performance of the buildings regarding construction (i.e. costs), suitability (e.g. design and location),
296
utilisation (such as function, size, and capacity), performance (e.g. energetic and environmental
297
aspects), and other critical subjects [91, 92]. POE, then, can be an appropriate tool for seeking
298
occupant perceptions regarding NV as well as the geometry and utilisation of balconies.
299
POE as an evaluation method was proposed in the 1960s and 70s in the United Kingdom, and
300
then in Australia and the USA based on social science, architecture, and building planner concepts
301
[14, 93, 94]. The first generation of the POE focused on occupants’ feedbacks on the indoor
302
environment such as HVAC performance. The 1980s saw POE deployed in diverse areas within the
303
built environment [95-97]. As deployment increased, the tools used for POE also became more
304
refined and sophisticated [91]. Nowadays, researchers are broadly applying POE to evaluate a range
13
305
of criteria such as energy-saving, occupant comfort (e.g. thermal and luminance), and indoor
306
environment in diverse types of buildings (i.e. residential, commercial, educational, and so on) [98,
307
99].
308
Compared with technical building performance evaluation that can occur at any or all of the six
309
main phases of a building’s life cycle: planning, scoping, design, construction, occupancy and end-
310
of-life [90], POE occurs only in the occupancy stage. It seeks occupants’ feedback regarding their
311
experiences and perceptions and satisfaction with the building’s performance [100-102].
312
Furthermore, other issues that are related to the users’ satisfaction factors such as cultural, social,
313
and psychological parameters make POE a multidisciplinary approach that addresses socio-technical
314
aspects of a building. POE also has the benefit of time flexibility as it can be deployed at any time
315
during a building’s occupancy and evaluations can be short, medium or long-term, providing the
316
options for capturing ‘instant’ feedback, trends and changes over time.
317
4.1. Application of POE to NV
318
Some consider POE as the inevitable step toward sustainability [103] and a missing link for
319
designing energy-saving buildings [89, 104]. The strong global focus on energy efficiency in
320
buildings has resulted in a large number of studies on the application of POE for assessing NV
321
utilisation and performance in different residential, commercial, and working spaces [105-107].
322
Literature shows that researchers typically conducted POEs on apartment buildings, focusing on
323
environmental condition such as IAQ, temperature, humidity, noise, and light to finding the level of
324
comfort and occupants’ feedbacks regarding their discomfort sources to find perspective solutions
325
[108-110]. Researchers have also widely applied POE to evaluate health, feelings, and thermal
326
comfort through NV utilisation in buildings, and applying these findings to improve the design and
327
function of the buildings [105, 111].
328
NV performance and usage have mainly been an excellent source of information for researchers,
329
and they extracted this information from occupants’ feedbacks regarding thermal comfort and
330
behaviour to help architects and designers to improve their works [92]. There are numerous studies
331
regarding thermal comfort through POE to explore warm feelings of users [112-114]. These POE
332
have also contributed to the foundation of some standards in this context. For example, in the 1970s, 14
333
Fanger [115] created an optimal thermal comfort POE method on occupants’ perception that was
334
associated with some calculations, heat-balance equations, and empirical studies on the metabolism.
335
Fanger also developed two indices, Predicted Mean Vote (PMV) and Predicted Percent of Dissatisfied
336
(PPD) to evaluate thermal feelings and comfort [116]. This approach was further accepted by the
337
International Standards Organization (ISO) 7730 and ASHRAE as a standard to quantify thermal
338
comfort [116, 117].
339
Although Fanger approach (including PMV and PPD indexes) is considered by some to be an
340
appropriate tool to evaluate thermal sensation, it was highlighted in some studies [118-120] that these
341
indices are not always considered to be accurate in predicting thermal sensation in extreme climates
342
(such as tropical climates) due to different expectations of occupants. Some also indicated that the
343
Fanger approach is also not an excellent tool to evaluate thermal sensation in residential buildings due
344
to the unpredictable behavioural patterns [121]. Indeed, thermal environments in residential buildings
345
are quite different from the more predictable and ‘steady’ thermal environment of offices or the lab
346
conditions where Fanger developed PMV and PPD. Besides, it was found over the earlier studies that
347
PMV underestimate the thermal comfort of buildings under NV mode [122]. Because of these
348
compelling arguments against this approach, Fanger presented the modified approach with a
349
correction for indoor areas under NV modes and extended the first method by introducing the
350
expectation of occupants under NV and multiplying this factor on the basis PMV [123, 124]. The idea
351
of the Fanger approach then was complemented with an adaptive thermal comfort model that was also
352
introduced by some other researcher [125-127].
353
Application of POE in residential areas may also lead to outstanding results since these areas are
354
more undefined and less steady than office work or educational areas [121]. It means POE can
355
monitor residents with different cultures, behaviours, and adaptabilities that have the authority and
356
capacity to control their comfort by changing modes and types of their cooling or heating, or changing
357
their clothing or room location, while this authority is limited in other non-residential areas. For
358
example, NV is sometimes not a possible option in some office buildings due to the windows not
359
being operable. Consequently, the thermal comfort of occupants as well as NV utilisation is in
15
360
different ranges and patterns and POE may extract new understandings, especially for residential
361
buildings.
362
Researchers have employed POE to monitor the behaviour and comforts regarding NV utilisation
363
through different elements such as windows [128], balconies [106], and wind catchers [129, 130].
364
Balconies as private and adaptive outdoor areas are considered as one of the most desirable function
365
spaces, particularly in cooling dominant climates. The results of a technical guide by Wood and Salib
366
[131] reveals more than 40% of users of high-rise buildings, in general, identify access to the outside
367
by balconies or other openings are essential for them. Moreover, findings of a survey on thermal
368
comfort of apartment buildings in the tropical climate of Hyderabad in India indicates 60% of
369
occupants are not comfortable in summer because of reduced availability of adaptive opportunities
370
such as balconies and windows [132]. Additionally, NV utilisation through different passive elements,
371
including balconies being considered more in recent years [133, 134].
372
As POE is a proper tool to discover the gap among current performance and behaviour,
373
experiences and expectations of occupants through their feedbacks, hence it seems a useful procedure
374
to evaluate the current status of balconies and come out new ideas. Table 3 summarised POE projects
375
on NV utilisation based on critical characteristics.
376
Table 3. POE studies on the NV utilisation
Ref
Building Type
Climate
Green Feature (s)
Purposes of POE
Methods
NV
Subjective perceptions when sitting, walking & running under NV vs MV
Questionnaire (Likert Scale) & Physical measurement
T-test using SPSS
NV
Perceived IAQ & Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
PMV & Thermal Sensation Vote (TSV)
PMV & TSV
Thermal comfort vote & TSV
[135]
Workplace (office)
Subtropical (humid)
[38]
Learning places (classrooms)
Between semiarid & humid subtropical
[39]
Workplace (office)
Cold tropics
NV
Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
[136]
Learning places (High school)
Tropical
NV through windows
Thermal comfort
Questionnaire (Likert Scale)
16
Data Analysis
Critical Findings The decreasing magnitude of acceptable temperature was more extensive under AC compared to NV. Measured thermal comfort was less than the PMV. The occupants’ density affected perceived IAQ but not thermal sensation. ASHRAE adaptive model recommends comfort temperature less than TSV. Although most of students accepted the temperature, most of them preferred lower temperature.
[137]
[138]
[139]
Residential
Workplace (office)
Learning places (5 universities)
Five regions contain very cold, cold, hot summer & cold winter, mild, & hot summer and warm winter
NV through windows
Usage of NV vs MV in five different climate zones
Questionnaire (bipolar between NV & MV) & Physical measurement
Statistical analysis (Mean rating)
Subtropical (oceanic)
Natural Light (NL), NV& MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Likert Scale) based on Building Use Studies (BUS)
Statistical analysis (Mean rating)
Subtropical (humid)
NV & NL through windows
IEQ (air, noise, lighting & health), Building Design (BD) & Facilities Management (FM)
Questionnaire (BUS) - Likert Scale
T-test
IEQ (air, noise & lighting) & thermal comfort & Adaptive behaviour
Questionnaire (Likert Scale) & Physical measurement
ANOVA using SPSS TSV & Spearman correlation coefficient
[140]
Residential (dormitory)
Tropical
NV & MM through windows
[111]
Learning places (primary school)
Mediterranean climate
NV & NL
IEQ (air & lighting) & Thermal comfort
Questionnaire (Fanger approach)
PMV, TSV & PD using MATLAB
Tropical
NV & NL through balconies
Thermal and overall comfort under Bioclimatic Design Strategies (BDS) [141]
Questionnaire (Likert Scale)BUS & Experiment
Pearson correlation
NV
Thermal comfort & pleasant sleep environment in bedrooms & behaviour
Questionnaire (Likert Scale)
Statistical analysis (Mean rating)
Questionnaire (Likert Scale)
PMV, SET*, ET*, PPD, Mean radiant temperature & Heat stress index(HSI)
Questionnaire (Likert Scale)
PMV
[75]
[142]
Residential (college)
Residential
Tropical
[120]
Hospitals & Shopping centres
Tropical
NV
Thermal, humidity, air movement sensation & thermal comfort
[143]
Residential (dormitory)
Humid continental
NV through windows
Thermal comfort & IAQ
17
Thermal comfort has priority to IAQ for occupants. Health was the crucial factor that led to preferring MV. NV & MV periods, respectively, have direct & reverse trends with rising outdoor temperature. Office under NV mode slightly more satisfied than MM. NV provides more comfort than MM, as well. Although Green buildings’ occupants are more consistently satisfied than non-green for BD & FM, IEQ satisfaction is lower in non-green buildings. BD affects occupants’ behaviour. Occupants in tropical felt thermal comfort in higher temperature than ASHRAE. Clothing, Higher IAV & MM with NV & Fan were vital adjustments. Thermal satisfaction was significantly different for teachers & pupils. Application of BDS, which assimilates physiology, climatology & building physics, has significantly enhanced overall comfort except for NL. Older people & outdoor workers use more NV & fans instead of AC that may show the impact of users’ adaptability. Two comfortable temperature ranges were defined for hospitals & shopping centres that challenge the ASHRAE PMV thermal comfort. Results show NV & thermal comfort trends & the upsurge of the NV areas decrease the thermal comfort. Authors developed a model for a fair NV utilisation for adequate thermal
[35]
Workplace (office)
Subtropical (oceanic)
Advance d NV & MM
Thermal comfort (static & dynamic)
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
[144]
Learning places (university)
Temperate (Sheffield)
NV & NL
Thermal comfort & Energy efficiency
Questionnaire (Likert Scale)
PMV & t-test
semicontinental
NV through a balcony
IEQ, thermal comfort through different layouts & cooling types (MV & NV)
Domestic questionnaire (Likert Scale) based on (BUS)
Statistical analysis using NVivo software package
Subtropical & Tropical
NV, daylight & view, green space
Health perceptions (physical & psychological)
Cross-sectional questionnaire (Importance & Likert scale)
T-test
NV & NL
IEQ, overall satisfaction (thermal, air & lighting) & energy usage
Questionnaire (Likert Scale) from previous study [135]
T-test, ANOVA using SPSS V18.0
Subtropical
NV
Common usage of balcony & overall comfort & sensation of NV utilisation thro balconies
Questionnaire (Likert Scale) & Interview
Statistical analysis by SPSS
IAQ, Indoor thermal sensation, windows opening habit
Questionnaire (Likert Scale, importance & rating scale) & Interview
SPSS (Crosstab & Chi-square)
[106]
Residential
[145]
Workplace (office) morphology
[146]
[22]
Residential
Residential
Subtropical
[147]
Residential
Continental (humid)
NV through windows
[148]
Workplace (office)
Different climate in China
NV, NL & MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Importance & Likert scale)
ANOVA test
[149]
Workplace (office)
Subtropical
NV
Comfort & design satisfaction, needs, health & productivity
Questionnaire (BUS) - Likert Scale
T-test
[150]
Workplace (office)
Between semiarid & humid subtropical
NV through windows
Thermal comfort & IAQ
Questionnaire (Likert Scale & Bipolar) & Physical
PMV & TSV
18
comfort. Thermal comfort is satisfactory in summer, but dissatisfaction occurred in winter. Static & dynamic thermal comfort matched with POE results in summer & winter, respectively. Environmental control by users improved comfort perception. The Gap between energy performance & comfort can be field using POE results & prediction. Find challenges of designing & critical issues to help researchers, designers & managers for the future projects. There is an association between green features & health perceptions in offices. This article contributes to justify & optimise passive climateadaptive design strategies. A structural model was developed based on the relationship between IEQ, satisfaction & energy usage to enhance IEQ & satisfaction Residents significantly prefer NV to achieve thermal comfort compared with AC in the subtropical climate of Brisbane. People behaviour & habits of opening windows based on room & windows opening size in winter was cleared based on POE results. MM ventilation is very sensible picks for green buildings for high satisfaction. Recommend more awareness & forgiveness factors for green buildings’ users. IAQ has a significant impact on IEQ acceptance. Warm neutral temperature
measurement
[151]
Learning places (university)
[109]
Workplace (office building)
[152]
Workplace (university office)
377
Tropical
Subtropical (humid)
NA
IEQ (air, noise, lighting & cooling device & design) & overall comfort
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
NV
IEQ
Questionnaire (BUS) - Likert Scale & Physical measurement
Pearson correlation
NV & NL
IEQ (air, noise & lighting) & thermal comfort & forgiveness factor
Questionnaire (Likert Scale)
PPD for NV, AC & Mix based on CBE of Berkeley database
NV through windows
found 20 °C (good agreement with Chinese standard). Occupants could achieve thermal comfort without AC, but need for more information to get the optimum usage of NV. Around 90% was satisfied & most of the dissatisfactions occurred due to chiller (staffs work close to vent). Occupants who are usually using AC expressed more negative evaluations (low forgiveness factor); in contrast, the MM and NV buildings.
The key findings from the reviewed POE/NV literature include:
378
•
Workplaces have been studied much more than residential buildings.
379
•
Most studies were carried out in cooling dominated climates, with some studies challenging the ASHRAE thermal comfort standards.
380 381
•
instead of MV.
382 383 384
The literature seems to highlight the importance of occupants’ dedication to NV utilisation
•
Researchers have not discovered what the impacts of design feature on the quantity and quality of NV utilisation and how it could be improved based on POE results.
385 386
5. Methods for evaluation NV effectiveness
387
The literature reveals several methods or techniques used to evaluate the impact of balcony
388
geometries on NV performance and occupant perceptions [107]. This section aims to investigate the
389
most practical approaches through the literature and compare their advantages and limitations.
390
5.1. Post-Occupancy Evaluation (POE) Methods
391
POE typically investigates the building issues in three levels, including indicative that present an
392
indication of performance and find the issues, investigative that usually focuses on finding issues, and
393
finally diagnostic that displays deficiency and presents some actions as corrections [153-155]. In a
19
394
broader view, POE is categorised into two general steps, including planning and implementation
395
[156]. The planning phase is usually divided into four parts, including deciding to accomplish (why
396
POE?), selecting an approach, briefing or details of POE, and method selection. The implementation
397
phase is also clarified through three steps containing carryout, data gathering and analysing, and
398
providing an action plan [157, 158].
399
There are several standard methods used to conduct a POE: questionnaires, interviews, focus
400
groups (i.e. group meetings), workshops, and walk-through evaluations [90, 91, 159-161]. A
401
comparison of the methods, based on time, cost, perspective, results accuracy and quality, was
402
reported in [92, 162]. Although this study shows that individual interviews and questionnaires are the
403
best methods for POE, the reported barriers of these methods include the slow procedure of
404
interviews, the needs for a skilled interviewer, and the need for skilled survey design (to ensure
405
critical points are not omitted). The main advantage of the surveys is the simple distribution of a
406
survey to the targeted participants (i.e. online). Besides, the survey’s results can be analysed using
407
statistical tools to find possible patterns and relations that might be useful for future studies or
408
designs. In summary, the literature concludes that a well-designed, brief, subjective and qualitative
409
questionnaire remains the primary POE method utilised but designing such a survey remains
410
challenging.
411
5.2. Evaluation Methods of NV performance
412
NV performance is usually quantified based on airflow pattern and rate, IAV, Air Change per Hour
413
(ACH), Mean Age of Air (MAA), volumetric flow rate, and other derived quantities from these
414
parameters [163]. The evaluation methods are mainly categorised into analytical and empirical
415
methods [8], numerical or computational analysis [164], experimental methods (small and large scale)
416
[165]. Analytical approaches involve single zone, and multiple zones [60] are driven by the theory of
417
heat transfer and fundamental mathematical fluid dynamics, while the empirical methods are
418
established on measurements and observations. Both analytical and empirical methods are useful for
419
initial steps and estimation of simple geometries [166].
20
420
Researchers have employed these methods or a combination of them such as association of CFD
421
and empirical models [167-169], empirical model integrated to small and full-scale experiment [85,
422
170], coupled CFD simulation [171-173], and de-coupled CFD models [174-176] based on their
423
accuracy, cost and time consuming, and the objective of their studies. Omrani et al. [177] explored,
424
assessed, and categorised robustness and limits of each technique regarding the accuracy, application
425
for complex geometries, resolution of results, cost, and spending time. The authors highlighted the
426
related methods for various situations concerning drawbacks and constraints and suggested a design
427
model for NV in high-rise residential apartments that can be employed in the design and construction
428
phases.
429
Computational simulation methods such as CFD simulation or a combination of CFD and other
430
approaches (e.g. experimental) are introduced as the most applicable approaches to find details of NV
431
such as air velocity, pressure, and particle distribution both indoor and around the buildings [169,
432
178]. Although CFD simulation is usually time-consuming compared with analytical and empirical
433
techniques, it provides details information on NV such as air velocity and pressure. Authors have
434
usually validated the simulation results against real experimental data or outcomes of other evaluation
435
methods to approve the simulation procedure for the further analysis and possible scenarios. There are
436
several methods to validate simulations that CFD combined with network airflow models [60, 179,
437
180] and experimental methods (small and large scale) [165, 181-183] are possible combinations.
438
CFD simulation software numerically describes physics of air movement using Navier-Stokes
439
equations (i.e. Reynolds-Averaged Navier-Stokes (RANS)). The RANS equations are usually
440
calculated along with the governing equations such as k-ε and k-ω models. Three physical principles
441
including conservation of mass (continuity equation), energy conservation (first thermodynamic law),
442
and the second Newton law (momentum equation), in general, are basis of the governing equations
443
that are, respectively, shown in Equation 3, 4, and 5 for the steady incompressible flow [184]: '( ( ) = 0 (3) ')
'(', ( (- . ' ' '( 555555 =− + + ́2 (4́ 1 + 6 ( − /0 / 1− ( ') ')- ')')- ') 21
7)
(4)
'( ( ) 1 ' ' ' 55555 = ;< =+ (− ( 4́ ) (5) ') 9: ')- ') ')444
55555 where ( 7 ), (6), and (( 4́ ), correspondingly, represent the operation temperature, thermal expansion
445
coefficient, and turbulent heat flux. Therefore, the constant values of different governing equations
446
can be calculated based upon these equations [184, 185].
447
NV behaviour, unlike MV, is much less expectable, so modelling tools play an essential role to
448
discover more about the airflows’ motions. Hence, CFD was broadly employed by researchers to
449
simulate NV in buildings and find the airflow related parameters such as IAV, MAA, and ACH [69,
450
169, 178] to show the variation of NV performance due to changing design features of passive
451
elements. Although CFD simulation is a time-consuming procedure, high-accuracy, low cost, and
452
suitability of this simulation method caused CFD becomes a favourite tool to simulate airflow pattern
453
in naturally-ventilated buildings [169]. Besides, as CFD simulation mainly needs to be validated
454
using an auxiliary source, different validation tools, mainly experimental analyses, were suggested for
455
this purpose [169].
456
Experimental analyses, which are divided into small and full scales, are extensively employed to
457
calculate airflow characteristics (i.e. velocity, pressure, and temperature). In the context of NV
458
studies, researchers have usually applied experiments as a validation tool for numerical analysis,
459
which also helps to adjust the grids [69, 169]. Although the literature shows both small and full scales
460
of experiments are the highly accurate studies compared with other validation methods, these studies
461
are usually costly and time-consuming [105, 186, 187]. The magnitude of the cost and time
462
consumption directly depend on the amount of detailed data [169]. Therefore, designing an
463
experiment regarding cost, time, and the required amount of details data are a critical issue, and strong
464
knowledge of the previous studies can be helpful to design an optimum experiment based on the
465
mentioned criteria. Table 4 summarises the recently published articles (from 2014) in the context of
466
evaluation methods of NV to comprehend more details about the simulations and their applied
467
validation tools.
468
Table 4. Evaluation methods of NV through different passive elements 22
Ref
Climate types
[188]
Tropical
[130]
Not a specific climate
[189]
[190]
[191]
[192]
[193]
[195]
Subtropical (humid)
Tropical & Subtropical
Desert (hot & arid)
Tropical
Not Available (NA)
Tropical
[68]
Tropical
[196]
Subtropical (humid)
Passive Element
Purposes
Solver & Software details
Measured Parameters
3D-steady RANS, LB k-ε model FloEFD softwareMentor Graphics
Air velocity (AV) Air temperature (AT) & Relative Humidity (RH)
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
AV on spots indoor, opening & outdoor on diverse WA
Full-scale + System simulation (Thermal comfort PMV)
EnergyPlus
Indoor Average & radiant AT RH & IAV
AV, block ratio
Method
Transom Ventilation Panel (TVP)
Improving ACH through SSV & CV using TVP.
Full-scale experiment + CFD
Windcatcher
Effect of outdoor wind on flow behaviour inside wind catcher.
Wind tunnel (Closed loop) + CFD
DoubleWindow (parallel)
Save energy for the cooling purposes using double window.
Balcony (Vertical farming)
Effect of vertical farming on NV performance & thermal comfort in tropical regions.
Wind tunnel + CFD
3D-steady RANS, Reynolds Stress Model (RSM), Fluent (ANSYS)
Chimney
Maximising IAV by changing chimney’s geometry.
Full-scale experiment (prototype) + CFD Optimisation
3D quasi-steady RANS, RNG k-ε & Fluent (ANSYS)
AV, ACH, AT & solar intensity
Windows
Analysing the thermal & acoustic comfort through windows ventilation.
CFD (PMV Thermal comfort)
Standard (S)k-ε, Finite Element Method (FEM) & Fluent (NA)
No experiment
Windcatcher
Indoor Air Distribution (IAD), living area using (ACH & IAV)
Stereo Particle Image Velocimetry (SPIV) [194] + CFD
3D steady RANS, ST k-ω & SST k-ω, Sk-ε, Rk-ε, RNG kε & RSM& Fluent (ANSYS)
Flow rate (m3/s), IAV & ACH
Atrium
Thermal & airflow conditions of NV through atrium.
Full-scale experiment + CFD
SST k-ω, Sk-ε-, Realizable (R) k-ε & RNG k-ε & Fluent (ANSYS)
IAD (speed, direction & pressure) & temperature
Efficiency of NV based on heat convection and airflow over DSF Simulation of NV at the nonrectangular indoor area
Full-scale experiment (a Test cell) + CFX Wind tunnel database + coupled CFD
DSF
Windows
23
CFX (ANSYS) 3D steady RANS, Spalart Allmaras model, k-ω (ST k-ω & SST k-ω) and k-ε
Temperature on the façade (inner & outer), Air velocities Pressure coefficient (Cp), Temperature & ACH
Critical Findings The IAV could be improved by 400% through TVP depend on outdoor wind speed. ACH has also been improved by 27%. Evaluate NV over wind catchers needs more experimental methods than other elements. 60% of cooling energy was saved using NV. The Setpoint of cooling temperature has a significant effect on energy usage. NV was crucially affected by vertical farming block ratio, so vertical farming needs a suitable design concerning NV performance. Width, inclination angle & airgap, respectively, has the most sever impacts on NV performance. Night NV over windows due to less noise is active & provide sufficient fresh air & improve thermal comfort thru a specific season. Airspeed ratio, as well as ACH & Flow rate, should be considered to find IAD. RNG k-ε was the best prediction tools. Direct ventilation in the atrium improved indoor airflow. Indoor temperature reduced due to obstruction of solar radiation by DSF. NV can decrease around 65% of the cooling hours. Although NV
EnergyPlus
[197]
[70]
[198]
[200]
[201]
[26]
[202]
[204]
Desert (hot & arid)
Not a specific climate
Not a specific climate
Desert (hot & humid summer)
Temperate climate (cold)
Subtropical (humid)
Hot & humid region
Tropical
Effects of varying wind incidents angles on winddriven NV in a combination of 4sided wind catcher & courtyard. Exploring the integration of Windcatcher & Wing wall, its optimum angle & the best wing wall length on NV performance
family (Sk-ε, Rk-ε, & RNG k-ε)
Flow rate (m3/s), IAV
By neglecting stack impact, 4-sided wind catcher provides heat dissipation instead of breeze.
3D-steady RANS, Sk-ε, Rk-ε, RNG kε Fluent (ANSYS)
AV & air flow rate
The optimum length & angle provide the best NV performance considering AV, flow rate, ACH, MAA.
Full-scale experiment in test chamber [199] + CFD
3D-steady RANS, k-ω model, Fluent (ANSYS)
AT, Surface temperature, Airflow & CO2 sensors
Results highlighted vertical slide windows for providing the best NV performance.
Wind tunnel (Closed loop) + CFD (Fluent codes)
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
Indoor airflow velocity and AT
The optimum streamwise distance reduced thermal cooling capacity by 10%.
Wind tunnel (open circuit) + CFD
3D steady-state RANS, SST k-ω Fluent (ANSYS)
Wind tunnel results of [71] + CFD
Windows
Investigation of SSV performance thru typical windows types
Windcatcher with assisted heat pipes
Optimising of heat pipes that are used to improve NV performance through wind catchers
Wind Catcher & Courtyard
Windcatcher & Wing wall
DSF
Investigating NV through DSF
Balcony
Impact of balconies’ features on NV performance & thermal comfort.
Trace
Impacts of Trace’ depth (porous type building) on NV using mean AV & MAA.
Void
Impact of void provision on the wind-driven NV in residential Medium Cost Multi-Storey Housing (MCMSH)
affected ACH, thermal condition was not significantly affected.
Full-scale experiment (Velocity profile & Tracer gas) + CFD Full-scale experiment + CFD (Thermal comfort (SET*)) Wind tunnel (Particle Image Velocimetry (PIV)) [203] + CFD Full-scale experiment & Wind tunnel + CFX
24
2D Unsteady RANS (URANS), Finite-volume, OpenFOAM
Airflow & AT
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
AT, IAV & Related Humidity (RH)
3D-steady RANS, k-ε turbulence model & Fluent (ANSYS)
Sk-ε, RNG k-ε & SST k-ω CFX (ANSYS)
Agreement between building simulation & CFD was remarkable in the prediction of outlet temperature & airflow profile. Incident WA is the vital balcony’s feature. SSV was more sensitive than a CV to varying design features.
IAV & ACH
Increasing on Trace’s depth has significant impacts on IAV by 88%.
AV & Thermal comfort
The suitable void configuration suggested, and results may contribute to better NV performance over void at MCMSH.
[205]
[206]
[207]
[209]
[28]
[212]
[214]
[215]
[216]
Results highlighted the excellent potential of voids for MCMSH in the tropical climate. Close & CV courtyard can attain thermal comfort and avoid unnecessary humidity. Varying width has significant effects on IAD & AV. It is suggested to use this method for optimising wind catcher in other climates. A specific geometry including inclination angle, length, width & air gap, introduced as the optimal design. Coupled CFD methods (finding indoor and outdoor flowrate at once) is useful to assess NV performance. A mixture of vertical & tilted walls, respectively, at upper & lower floors, had the best NV performance. For investigating orientation, the unit layout should be considered.
Void
Finding voids’ potential for NV in residential MCMSH
Wind tunnel [170]+ CFX
Sk-ε & CFX (ANSYS)
Wind pressure distributions on façade in different WA (°)
Courtyard
Effects of internal courtyards on NV to find innovative strategies for urban houses
Full-scale experiment
NA
AT, RH, and air pressure
Windcatcher
Study the best airflow & thermal comfort in six design scenarios of wind catcher (width & height).
3D steady-state RANS, Sk-ε, Rk-ε, RNG k-ε, SST k-ω & Fluent (ANSYS)
AT, AV & RH
Chimney
Achieve optimum NV through solar chimney by finding the optimal geometry.
3D-steady RANS, RNG k-ε & Software (NA)
Flow rate, AT & external AV, Solar radiation
Balcony
Influences of façade shape and openings on wind-induced NV (MAA & ACH)
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
IAV, ACH, outdoor wind speed & pressure distribution
Hot & dry
Atrium
Impact of atrium’s wall angularity on NV performance & thermal comfort.
CFD + Previous analytical models [213]
3D-steady RANS, RNG k-ε & Software (NA)
No experiment
Tropical
Balcony & Window
Full-scale experiment
No simulation
Indoor AT, RH, and air velocity
k-ε model & Fluent (NA)
Indoor & outdoor AT, humidity & AV
SV is the best NV strategy in Yinzi house based on the validated simulation results.
Wind speed, Flow rate & ACH
Large windows on the façade enhance NV performance. Provision of loggia reduces ACH except for the direct airflow to opening.
Tropical
Tropical
Desert (hot & arid)
Desert (hot & arid)
Subtropical (humid)
Subtropical (humid)
Mediterranean climate (hot & arid summer)
Patio
Windows & Loggia
[217]
Not a specific climate
Windows
[218]
Not a specific climate
Void & Lightwell
Impacts of orientation & height of buildings on NV. Find NV pros & cons in Yinzi, traditional Chinese, house as well as the best NV strategy. Effect of loggia & window opening size & façade porosity on CV rate. Finding an innovative design for windows to get the highest NV & lower dispersion of rain. Impact of horizontal &
Wind tunnel + another simulation [208] + CFD (Thermal comfort PMV & PPD) Full-scale experiment (prototype) + CFD Optimisation Wind tunnel [210]+ CFD (Subconfiguratio n validation [211])
Full-scale orthogonal experiment + CFD Full-scale experiment (tracer gas method) & empirical + CFD
3D-steady RANS, RNG k-ε & RSM & Fluent (ANSYS)
Wind tunnel (PIV) + CFD
k-ε model & Fluent (ANSYS Airpack)
AV, ventilation Flow rate (m3/s)
Rain penetration was dropped by 98%, while NV rate decreased by 4 & 9 % in defined scenarios.
Wind tunnel [219] + CFD
3D-steady RANS, RNG k-ε, Rk-ε,
AT & Airflow rate & pattern
Void & lightwell had substantial effects on
25
vertical position of connected to lightwell void on the upward airflow.
[220]
[186]
[222]
[223]
[147]
Hot & arid
Windows
Mediterranean climate (hot & arid summer)
Mediterranean (hot & arid summer)
Subtropical (humid)
Continental (humid)
Patio
Windows & overhang
Atrium
Windows
Focus on the indoor airflow & thermal comfort in a naturally ventilated room with a window opening. Explore aerodynamic features in a residential unit with a patio that connects indoor & outdoor. Effect of windows’ overhangs on thermal mass & night NV to provide a guideline for overhang’s length. Optimum design of atrium for the NV utilisation using validated CFD, which was not well studied before. Find the status of opening windows habit in winter via survey and the reflection of this habit on thermal comfort.
SST k-ω & SST & Fluent (ANSYS)
Wind tunnel (open circuit) [221] + CFD & Network model + CFD & (PMV & PPD)
Wind tunnel + CFD
Full-scale experiment + Dynamic simulation
k-ε model & Fluent (NA)
3D-steady RANS, k-ε model & Software (NA)
TRNSYS software
Full-scale experiment + CFD
k-ε, RNG k-ε & Large Eddy Simulation (LES) & Fluent (NA)
Full-scale experiment (Tracer gas) + Survey & Interview
Data analysis of survey by SPSS (Crosstab and Chisquare)
upward airflow in the interior of lightwell. Wind direction was the most crucial parameters that affect airflow pattern.
AT, AV & Pressure coefficient (Cp)
Window location is the most crucial factor in NV & thermal comfort as PMV & PPD improved up to 12% & 3.5% for the best location.
AV, Airflow profile
Enhancing the indoor airflow & modifying outdoor microclimate (around the building) can improve thermal comfort.
Wind speed & direction, indoor & outside AT, RH
NV integrated with horizontal shading devices, enhance thermal comfort & decrease cooling demand.
AT, AV
Modelling shows bulk downward airflow that highlights the requirement of using precise simulation in atrium design.
Air change rate, AT, feeling of IAQ (by survey)
Effects of window opening size, wind direction & room size on the air change rate in winter were found based on results.
The main results of Table 4 can be summarised as below:
469 470
•
Most of the studies were carried out in climates that are recognised with hot summer.
471
•
A combination of CFD simulation and experimental analysis as a validation tool was the
472
standard method.
26
473
•
CFD was the standard method (via ANSYS) reported in literature review and k–ε models
474
were the most applied model for simulating airflows indoor and outdoor of the buildings,
475
which has also been highlighted in previous studies [28, 169, 224-226].
476
•
measured in most of the experimental studies.
477 478
Indoor air temperature and velocity, which directly affect indoor thermal comfort, was
•
There is a small number of full-scale in-situ experimental studies that highlight the needs for more in-situ measurement.
479 480
•
481
5.2.1.
The significant impacts of openings’ geometry were observed through critical findings. System Simulation
482
CFD is an excellent method that can be alternatively used for measuring the physical parameters in
483
the possible and vital scenarios [227-229]. While this simulation tool might not be a perfect tool for
484
the whole system parameters such as energy indexes in spaces under NV mode and it is better to
485
couple CFD with a whole building energy simulation model such as EnergyPlus [173]. Furthermore,
486
the enormous calculation time of 3D CFD analysis with a very satisfactory mesh can always be a time
487
constraint, so it is a rational solution to find appropriate tools for system simulation.
488
Energy modelling software, in general, predicts the energy consumption of buildings based on
489
various parameters such as cooling and heating load. These simulation tools are useful to design since
490
these tools predict thermal comfort and IAQ for the whole built environment. These are also excellent
491
facilities to determine the energy-saving potential for more accurate retrofitting of buildings (after
492
construction) or design of new structures based on the possible devices [230, 231]. Improved
493
solutions regarding passive design technics can also be determined using these tools [232], which is
494
the reason for applying this software in the current context. Energy simulation methods, overall, seek
495
optimum energy consumption and appropriate thermal comfort simultaneously.
496
There are various energy modelling software, EnergyPlus [233-235], ESP-r [65, 236, 237],
497
TRNSYS [238, 239], IDA Indoor Climate and Energy (IDA ICE) [240], Integrated Environmental
498
Solutions- Virtual Environment (IES-VE) [241, 242], CONTAM [243, 244], and COMIS [245] are
499
some of the most common software for energy simulation inside buildings [246]. These simulation
27
500
tools, as mentioned, typically employ input data, including the geometry of buildings, weather data,
501
internal load, HVAC data, and other required data to simulate required energetic factors [247]. The
502
current review investigates the characteristics, applications, and the capabilities of the available
503
software to find appropriate tools to assess NV performance in buildings. Hence, the suitability,
504
capabilities, advantages, and drawbacks of simulation software are compared and summarized in
505
Table 5 [232, 248-250].
506
Table 5. A comparison between the most applied system simulation software Energy Plus
ESP-r
TRNSYS
IDA ICE
IES VE
CONTAM
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
NO NO
NO YES
NO NO
NO NO
YES YES YES YES YES YES YES
YES YES YES YES YES YES YES
YES YES NO NO YES YES YES
YES YES YES YES YES NO YES
YES YES NO YES YES YES NO
YES YES NO YES YES YES YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
NO
NO
YES*
YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
YES YES
YES YES
YES NO
YES NO
YES NO
YES YES
YES NO YES NO YES NO
YES NO NO NO NO YES
YES YES NO NO NO NO
YES NO NO NO YES NO
YES NO NO NO YES NO
YES NO NO YES NO NO
Platform
Windows, Linux, and Mac
Windows, Linux, and Mac
Windows
Windows
Windows and Mac
Windows, Linux, and Mac
Pricing
Free
Open source
Reduced price for academic
Free Trial
Free Trial
Free
Features Simulation solution Iterative resolution of non-linear systems Simulation of loads, systems, & solutions Calculation time Variable time-step Dynamic variables (transient) Entire geometry description Surfaces including floors & walls Computation of thermal balance Import & export of geometry from CAD Import and export of models Thermal comfort of occupants General calculation of buildings Controllable windows for NV Airflow through the façade openings (i.e. balconies and windows) NV (Pressure and buoyancy driven) Mix-mode ventilation (NV & Mechanical) Multi-zone airflow (by pressure network) Implementation of occupants’ behaviour Control approach (Direct input) Co-simulation Major capabilities Energy simulation of entire building Detailed component simulation Load calculations Simulation of IAQ Code compliance Mixture of flow network & CFD domain General information
28
Relevant studies (Title-ABS-KEY (“software name” and “thermal comfort” and “natural ventil*”) AND Limit to (“ENGI” OR “ENER” OR “ENVI”) ) by August 2019 Total number of found articles 44 4 14 3 4 3 Number of articles over last 5 years 22 0 6 2 2 0 Most relevant studies (Title-ABS-KEY (“natural ventil*” and “thermal comfort” and “CFD” and “software name”)) Reference [173, 251] [252] 507 * Using the hybrid ventilation manager combined with an airflow network or co-simulation
508 509
The critical conclusions from Table 5 are as below: •
system and find the critical indexes.
510 511
EnergyPlus is standard software that has most of the required capabilities to evaluate a whole
•
EnergyPlus cannot directly predict IAQ, which was the most investigated parameter based on
512
the reviewed literature in Table 3 and Table 4. For solving this drawback, authors have
513
usually coupled EnergyPlus with CONTAM for finding IAQ [253].
514
•
ventilated space was remarkably higher than other software.
515 516
The number of articles used EnergyPlus to carry out energy modelling in a naturally-
•
EnergyPlus seems to be a standard tool for evaluating NV performance.
517 518
6. Summary and Suggested Future Studies
519
Although designers and researchers have increasingly considered NV to reduce GHG emissions
520
and energy consumption, there are not comprehensive review studies to investigate the impacts of
521
design-related parameters of passive elements on NV performance and occupations’ perception. The
522
current article, therefore, has comprehensively reviewed the articles on NV through façade openings,
523
particularly balconies that are the key focus of the current study. For this purpose, the current article
524
focuses on technical and socio-technical impacts of designing façade openings on NV, as two main
525
objectives of this review.
526
As a beginning step, a comparison between the numbers of studies on NV through several passive
527
elements using Scopus database indicated that many studies have focused on the balconies, while a
528
small proportion (around 2%) of them investigated the NV through balconies. Besides, very few
529
articles focused on the impacts of design-related parameters on the NV performance, reviewed in
29
530
Table 2. The literature shows that there is an essential need for studies to precisely investigate the
531
effects of some design-related parameters of balconies, such as the interaction between depth size and
532
orientation or H/D unitless factor, which has never been studied yet.
533
The review also revealed that SSV and CV were not identically affected by changing design
534
features of balconies, and SSV is more sensitive to these variations than CV and SV. Hence, the
535
impacts of designing geometries on SSV performance worth to investigate because most of the
536
apartments rely on SSV, as the only option for NV utilisation. The detailed review of the design
537
features of balconies, however, shows there is not any clear outcome regarding the impacts of
538
different geometric factors on NV performance.
539
For exploring the critical socio-technical factors, occupants’ perceptions and behaviour impacts on
540
the NV utilisation, as well as the effects of design-related factors, were reviewed using the literature
541
on POE studies. The current article, indeed, reviewed POE studies on NV utilisation through different
542
façade openings, specifically balconies. Table 3 summarised the recently published POE studies on
543
NV based on primary purposes, methods, case studies, findings, and other critical issues. Researchers
544
have usually selected workspaces for POE studies, which is easy to collect data, and they focused on
545
IEQ, and thermal comfort were the most common purposes of the POE studies.
546
Although the literature shows POE studies explored the logical relations among environmental
547
factors, satisfaction, behaviour, culture, and awareness of users regarding available ventilation
548
devices, the authors have not explicitly focused on the application of façade openings, particularly
549
balconies, for NV utilisation and not asked any questions regarding the geometry impact on NV
550
utilisation by occupants. Additionally, most of these POE studies were carried out in dominant
551
cooling areas such as tropical and subtropical climates, while the severe climate in summer,
552
nowadays, is happening in some other regions such as Mediterranean climate.
553
The present article reviewed the conventional methods for the evaluations of the socio-technical
554
and technical factors in section 5. This study comprehensively investigates the applied evaluation
555
methods of NV performance based on the physical parameters such as ACH, MAA, IAV, and flow
556
rate through literature. For predicting these parameters, applied methods are usually categorised into
557
empirical, analytical, and experimental methods. Table 4 shows the authors widely employed a 30
558
combination of analytical and experimental studies and suggested this approach as the most standard
559
and practical method. Although most of the recently published studies employed a combination of
560
simulation and experimental studies, a significant proportion of these studies employed the results of
561
experiments in literature such as wind tunnel outcomes. This issue highlights the need for
562
measurements, including both in-situ full-scale and small-scale experimental studies, specifically for
563
regions that have recently joined to regions with hot summer.
564
Regarding simulation details, 3D steady-state RANS and k-ε models follow by k-ω, were the most
565
applied solver and turbulence models and recruited in CFD simulations mostly through Fluent in
566
ANSYS software. Thermal comfort as one of the essential criteria for naturally-ventilated was also
567
evaluated mainly by PMV and PPD indexes [121]. Finally, although finding an optimum design of
568
passive elements, amongst balconies, were considered in the literature, there are not any
569
classifications of geometric factors impacts on NV performance and thermal comfort.
570
The next section of the current studies explored the system simulation tools to simulate the energy
571
indexes in spaces under NV mode. For finding the best software to simulate the whole system, Table
572
5 provides a comparison between the most well-known and applied software based on critical criteria.
573
Based on this comparison, EnergyPlus is standard software with the required capabilities to evaluate a
574
whole system and find the critical indexes. EnergyPlus and TRNSYS, as the first and second highest
575
employed software, were recruited in 60% and 20% of the published articles, respectively.
576 577
The following recommendations for the future studies are concluded from what has elaborated above and summarised as the following points:
578
Identification and classification of the different design features of balconies based on their
579
impacts on the NV performance and thermal comfort, specifically in high-rise multi-storey
580
residential buildings.
581
POE study on the impacts of façade openings design, specifically balconies’ geometry, on the
582
occupants’ perceptions, comfort, and behaviour, and analysing the collected feedbacks,
583
specifically in residential areas.
584
POE study in regions formerly recognised with a cool summer, but the GHG emission,
585
nowadays, changed the climate in this region. 31
586
There is a need for studies on thermal comfort standards in different climates, particularly the
587
regions with increasing occurrence of heat waves or prolonged summer overheating in
588
buildings.
589
The current review suggests a study that comprises a combination of POE, simulation, and
590
experimental study. This study could validate the ideas and feedbacks from POE studies by
591
using validated simulation.
592 593
7. Conclusion
594
The current article focuses on the technical and socio-technical impacts of designing façade
595
openings, specifically balconies, on NV performance and thermal comfort through a comprehensive
596
review. The early results show that the application of balconies for NV utilisation has not been
597
adequately investigated yet. The detailed review also recommends that more studies are required to
598
reveal the impacts of design-related parameters of balconies. Besides, the literature review revealed
599
that there is an insufficient number of small and full-scale experiments. Hence, this article strongly
600
suggests identification and classification of the most crucial design feature of balconies through a
601
study that comprises both simulation and experimental study, as a validation tool.
602
This article also explores the impacts of designing passive elements on socio-technical parameters,
603
which affected by different cooling devices. The review highlights that researchers mostly explored
604
the health and comfort factors at the indoor environmental areas without investigating the impacts of
605
the designing process. Therefore, this study suggests more POE studies that focus on the impacts of
606
designing façade openings on the occupants’ perception and comforts. Besides, this study
607
recommends residential buildings for these POE studies due to a limited number of POE studies on
608
the residential areas. Additionally, the residential spaces are unknown compared with workspaces and
609
residents have more freedom to use different cooling devices such as NV. On the other hand, this
610
review recommends POE studies in the climates that have been significantly impressed by climate
611
change. Finally, a combination of both technical and socio-technical parameters can be the title of
32
612
comprehensive research that investigates the design-related parameters as well as occupant’s
613
perception through a validated simulation and a POE study.
614 615
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25. 26. 27.
28.
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1169
42
Table 1. Number of publications on NV thru passive design elements by August 2019 Rank Passive elements Period Number of studies* 2015 to 2019 334 1 Windows Before2015 495 2015 to 2019 74 2 Chimney Before2015 119 2015 to 2019 21 3 Atrium Before2015 83 2015 to 2019 32 Double skin façade 4 (DSF) Before2015 77 2015 to 2019 42 5 Wind catcher Before2015 31 2015 to 2019 27 6 Courtyard Before2015 45 2015 to 2019 23 7 Wind tower Before2015 27 Balcony (or porch or 2015 to 2019 10 8 veranda) Before2015 26 2015 to 2019 10 9 Void Before2015 10 2015 to 2019 7 10 Wing Wall Before2015 4 * This numbers are recorded with limitation to engineering or energy or environment sciences in Scopus
1
Table 2. Literature on the influence of balcony design parameters on NV performance Balcony design parameters* Row
1
2
Ref
[25]
[69]
Ventilation mode &
Balcony Type
Studied Features
Open and semi-open
D/L (%) = 0, 10, 20, 30 & 40 WA(º)= 0, 45, 90 & 180
SSV
Open
Availability of balconies, upper & lower vents at balconies UL= 4, 5 & 6 (at the End (E) and Middle (M)) Availability of balconies & location D=1.5 and 3 m UL= 1 to 12 WA(º)= 0, 45, 90
CV & SSV
3
[24]
CV
Semi-open (balcony with wing wall)
4
[68]
CV & SSV
Open
5
[70]
CV & SSV
Open
6
[71]
CV & SSV
Open
7
[22]
CV & SSV
Open
Availability of balconies UL= 3 & 4, WA(º)= 0 & 45 OS (single & double)= 0.9 & 1.8 m Opening locations= 2 models (middle=1.8m, left & right= 0.9m) UL= 1 to 12 & WA(º)= 0 & 45 Availability of balconies UL= Ground to 5 WA(º)= 0, 22.5, 45, 67.5 & 90 Availability of balconies UL= Ground to 12 WA (º)= 0 & 45 Availability of balconies OS= 6 scenarios (with &without balconies, Small and Big opening at Middle & End), UL= Ground to 5
Best Scenario or Classification Open balcony, CV & D/L=10%, WA=0º Deeper balcony lead to lower NV performance Upper and lower vents at middle floors enhance the NV rate and make airflow recirculation UL=4E with balcony Available balcony (with regards to opening’s location), WA=0º & UL=10 Deeper balcony lead to lower NV performance Not Available (Best method is steady-state RANS) For CV, WA=0º & UL= 8 & 9 For SSV, with balcony, WA=45º & UL= 10 is the best Adding balconies increased NV rate intermediate levels (UL= 2, 3, 4), best UL= 3 & WA(º)= 0 1- Highest NV rate: CV without balcony, 2- SSV with balcony (WA=45º) was the best CV: Ground level with balcony & UL=G & 3 without balcony (small opening) SSV: UL=4 with balcony, UL= 4 (without balcony big opening) Based on the payback results, with balcony at SW
8
[72]
CV & SSV
Open
9
[73]
SSV
Open
10
[26]
SSV
Open
11
[74]
CV & SSV
Open
12
[75]
SSV
Open
Availability of openings or balconies, OS (33 models)
Different balcony & opening configurations significantly change airflows.
13
[76]
CV & SSV
Open
Availability of balconies UL= Ground to 5 WA(º)= 0 & 90
Available balcony at WA=90º& D=1.5m.
Availability of balconies O= N, S, E, W, NE, SE,SW Availability of balconies Opening: 2 vertical & 1 horizontal UL= Ground to 5 D= 0.75, 1.5, 3m, WA(º)= 45 & 90 Balustrade with & without solid Availability of balconies or/and wing wall or/and overhang WA(º)= 0, 45, 90 & 180
2
Best Scenario: with balcony, UL=5, vertical opening& WA=90º Best Scenario for the NV through balcony: Not Available
Table 3. POE studies on the NV usage Ref
Building Type
Climate
Green Feature (s)
Purposes of POE
Methods
NV
Subjective perceptions when sitting, walking & running under NV vs MV
Questionnaire (Likert Scale) & Physical measurement
T-test using SPSS
NV
Perceived IAQ & Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
PMV & Thermal Sensation Vote (TSV)
PMV & TSV
Data Analysis
[119]
Workplace (office)
Subtropical (humid)
[120]
Learning places (classrooms)
Between semiarid & humid subtropical
[121]
Workplace (office)
Cold tropics
NV
Thermal comfort
Questionnaire (Likert Scale) & Physical measurement
[122]
Learning places (High school)
Tropical
NV through windows
Thermal comfort
Questionnaire (Likert Scale)
Thermal comfort vote & TSV
Residential
Five regions contain very cold, cold, hot summer & cold winter, mild, & hot summer and warm winter
NV through windows
Usage of NV vs MV in five different climate zones
Questionnaire (bipolar between NV & MV) & Physical measurement
Statistical analysis (Mean rating)
Subtropical (oceanic)
Natural Light (NL), NV& MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Likert Scale) based on Building Use Studies (BUS)
Statistical analysis (Mean rating)
Subtropical (humid)
NV & NL through windows
IEQ (air, noise, lighting & health), Building Design (BD) & Facilities Management (FM)
Questionnaire (BUS) - Likert Scale
T-test
Tropical
NV & MM through windows
IEQ (air, noise & lighting) & thermal comfort & Adaptive behaviour
Questionnaire (Likert Scale) & Physical measurement
ANOVA using SPSS TSV & Spearman correlation coefficient
Mediterranean climate
NV & NL
Tropical
NV & NL
IEQ (air & lighting) & Thermal comfort Thermal and overall comfort
Questionnaire (Fanger approach) Questionnaire (Likert Scale)-
PMV, TSV & PD using MATLAB Pearson correlation
[123]
[124]
[125]
[126]
[101] [67]
Workplace (office)
Learning places (5 universities)
Residential (dormitory)
Learning places (primary school) Residential (college)
3
Critical Findings The decreasing magnitude of acceptable temperature was more extensive under AC compared to NV. Measured thermal comfort was less than the PMV. The occupants’ density affected perceived IAQ but not thermal sensation. ASHRAE adaptive model recommends comfort temperature less than TSV. Although the majority of students accepted the temperature, most of them preferred lower temperature. Thermal comfort has priority to IAQ for occupants. Health was the crucial factor that led to preferring MV. NV & MV periods, respectively, have direct & reverse trends with rising outdoor temperature. Office under NV mode slightly more satisfied than MM. NV provides more comfort than MM, as well. Although Green buildings’ occupants are more consistently satisfied than non-green for BD & FM, IEQ satisfaction is lower in non-green buildings. BD affects occupants’ behaviour. Occupants in tropical felt thermal comfort in higher temperature than ASHRAE. Clothing, Higher IAV & MM with NV & Fan were vital adjustments. Thermal satisfaction was significantly different for teachers & pupils. Application of BDS, which assimilates
through balconies
[128]
Residential
Tropical
under Bioclimatic Design Strategies (BDS) [127]
NV
Thermal comfort & pleasant sleep environment in bedrooms & behaviour
BUS & Experiment
Questionnaire (Likert Scale)
Statistical analysis (Mean rating)
Questionnaire (Likert Scale)
PMV, SET*, ET*, PPD, Mean radiant temperature & Heat stress index(HSI)
[100]
Hospitals & Shopping centres
Tropical
NV
Thermal, humidity, air movement sensation & thermal comfort
[129]
Residential (dormitory)
Humid continental
NV through windows
Thermal comfort & IAQ
Questionnaire (Likert Scale)
PMV
[34]
Workplace (office)
Subtropical (oceanic)
Advance d NV & MM
Thermal comfort (static & dynamic)
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
[130]
Learning places (university)
Temperate (Sheffield)
NV & NL
Thermal comfort & Energy efficiency
Questionnaire (Likert Scale)
PMV & t-test
semicontinental
NV through a balcony
IEQ, thermal comfort through different layouts & cooling types (MV & NV)
Domestic questionnaire (Likert Scale) based on (BUS)
Statistical analysis using NVivo software package
Subtropical & Tropical
NV, daylight & view, green space
Health perceptions (physical & psychological)
Cross-sectional questionnaire (Importance & Likert scale)
T-test
NV & NL
IEQ, overall satisfaction (thermal, air & lighting) & energy usage
Questionnaire (Likert Scale) from previous study [135]
T-test, ANOVA using SPSS V18.0
[95]
Residential
[131]
Workplace (office) morphology
[132]
Residential
Subtropical
4
physiology, climatology & building physics, has significantly enhanced overall comfort except for NL. Older people & outdoor workers use more NV & fans instead of AC that may show the impact of users’ adaptability. Two comfortable temperature ranges were defined for hospitals & shopping centres that challenge the ASHRAE PMV thermal comfort. Results show NV & thermal comfort trends & the upsurge of the NV areas decrease the thermal comfort. Authors developed a model for a fair NV usage for adequate thermal comfort. Thermal comfort is satisfactory in summer, but dissatisfaction occurred in winter. Static & dynamic thermal comfort matched with POE results in summer & winter, respectively. Environmental control by users improved comfort perception. The Gap between energy performance & comfort can be field using POE results & prediction. Find challenges of designing & critical issues to help researchers, designers & managers for the future projects. There is an association between green features & health perceptions in offices. This article contributes to justify & optimise passive climateadaptive design strategies. A structural model was developed based on the relationship between IEQ, satisfaction & energy usage to enhance IEQ & satisfaction
[21]
Residential
Subtropical
NV
Common usage of balcony & overall comfort & sensation of NV usage thro balconies IAQ, Indoor thermal sensation, windows opening habit
Questionnaire (Likert Scale, importance & rating scale) & Interview
SPSS (Crosstab & Chi-square)
Questionnaire (Likert Scale) & Interview
Statistical analysis by SPSS
[133]
Residential
Continental (humid)
NV through windows
[134]
Workplace (office)
Different climate in China
NV, NL & MM
IEQ (air, noise, lighting & health) & overall comfort
Questionnaire (Importance & Likert scale)
ANOVA test
[135]
Workplace (office)
Subtropical
NV
Comfort & design satisfaction, needs, health & productivity
Questionnaire (BUS) - Likert Scale
T-test
[136]
Workplace (office)
Between semiarid & humid subtropical
NV through windows
Thermal comfort & IAQ
Questionnaire (Likert Scale & Bipolar) & Physical measurement
PMV & TSV
[137]
Learning places (university)
Tropical
NV through windows
IEQ (air, noise, lighting & cooling device & design) & overall comfort
Questionnaire (BUS) - Likert Scale
Statistical analysis (Mean rating)
[98]
Workplace (office building)
NV
IEQ
Questionnaire (BUS) - Likert Scale & Physical measurement
Pearson correlation
[138]
Workplace (university office)
NV & NL
IEQ (air, noise & lighting) & thermal comfort & forgiveness factor
Questionnaire (Likert Scale)
PPD for NV, AC & Mix based on CBE of Berkeley database
Subtropical (humid)
NA
5
Residents significantly prefer NV to achieve thermal comfort compared with AC in the subtropical climate of Brisbane. People behaviour & habits of opening windows based on room & windows opening size in winter was cleared based on POE results. MM ventilation is very sensible picks for green buildings for high satisfaction. Recommend more awareness & forgiveness factors for green buildings’ users. IAQ has a significant impact on IEQ acceptance. Warm neutral temperature found 20 °C (good agreement with Chinese standard). Occupants could achieve thermal comfort without AC, but need for more information to get the optimum usage of NV. Around 90% was satisfied & most of the dissatisfactions occurred due to chiller (staffs work close to vent). Occupants who are usually using AC expressed more negative evaluations (low forgiveness factor); in contrast, the MM and NV buildings.
Ref
[173]
[174]
[175]
[176]
[177]
[178]
[179]
Table 4. Evaluation methods of NV through different passive elements Climate Passive Solver & Purposes Method types Element Software details
Tropical
Not a specific climate
Transom Ventilation Panel (TVP)
Improving ACH through SSV & CV using TVP.
Full-scale experiment + CFD
Windcatcher
Effect of outdoor wind on flow behaviour inside wind catcher.
Wind tunnel (Closedloop) + CFD
Measured Parameters
Critical Findings
3D-steady RANS, LB k-ε model FloEFD softwareMentor Graphics
Air velocity (AV) Air temperature (AT) & Relative Humidity (RH)
The IAV could be improved by 400% through TVP depend on outdoor wind speed. ACH has also been improved by 27%.
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
AV on spots indoor, opening & outdoor on diverse WA
Evaluate NV over wind catchers needs more experimental methods than other elements.
Subtropical (humid)
DoubleWindow (parallel)
Save energy for the cooling purposes using double window.
Full-scale + System simulation (Thermal comfort PMV)
Tropical & Subtropical
Balcony (Vertical farming)
Effect of vertical farming on NV performance & thermal comfort in tropical regions.
Wind tunnel + CFD
3D-steady RANS, Reynolds Stress Model (RSM), Fluent (ANSYS)
Chimney
Maximising IAV by changing chimney’s geometry.
Full-scale experiment (prototype) + CFD Optimisati on
3D quasi-steady RANS, RNG k-ε & Fluent (ANSYS)
Windows
Analysing the thermal & acoustic comfort through windows ventilation.
CFD (PMV Thermal comfort)
Desert (hot & arid)
Tropical
Not Available (NA)
EnergyPlus
Indoor Average & radiant AT RH & IAV
AV, block ratio
60% of cooling energy was saved using NV. The Setpoint of cooling temperature has a significant effect on energy usage. NV was crucially affected by vertical farming block ratio, so vertical farming needs a suitable design concerning NV performance.
AV, ACH, AT & solar intensity
Width, inclination angle & airgap, respectively, has the most sever impacts on NV performance.
Standard (S)k-ε, Finite Element Method (FEM) & Fluent (NA)
No experiment
Night NV over windows due to less noise is active & provide sufficient fresh air & improve thermal comfort thru a specific season.
Windcatcher
Indoor Air Distribution (IAD), living area using (ACH & IAV)
Stereo Particle Image Velocimetr y (SPIV) [180] + CFD
3D steady RANS, ST k-ω & SST k-ω, Sk-ε, Rk-ε, RNG kε & RSM& Fluent (ANSYS)
Flow rate (m3/s), IAV & ACH
Airspeed ratio, as well as ACH & Flow rate, should be considered to find IAD.
Full-scale experiment + CFD
SST k-ω, Sk-ε-, Realizable (R) k-ε & RNG k-ε & Fluent (ANSYS)
IAD (speed, direction & pressure) & temperature
Full-scale experiment (a Test
CFX (ANSYS)
Temperature on the façade (inner & outer),
[181]
Tropical
Atrium
Thermal & airflow conditions of NV through atrium.
[60]
Tropical
DSF
Efficiency of NV based on heat convection and
6
RNG k-ε was the best prediction tools. Direct ventilation in the atrium improved indoor airflow. Indoor temperature reduced due to obstruction of solar
airflow over DSF
[182]
[62]
[183]
[185]
Desert (hot & arid)
Not a specific climate
Not a specific climate
Desert (hot & humid summer)
[186]
Temperate climate (cold)
[25]
Subtropical (humid)
[187]
[189]
Hot & humid region
Tropical
Wind Catcher & Courtyard
Windcatcher & Wing wall
Effects of varying wind incidents angles on winddriven NV in a combination of 4sided wind catcher & courtyard. Exploring the integration of Windcatcher & Wing wall, its optimum angle & the best wing wall length on NV performance
Windows
Investigation of SSV performance thru typical windows types
Windcatcher with assisted heat pipes
Optimising of heat pipes that are used to improve NV performance through wind catchers
DSF
Investigating through DSF
NV
Balcony
Impact of balconies’ features on NV performance & thermal comfort.
Trace
Impacts of Trace’ depth (porous type building) on NV using mean AV & MAA.
Void
Impact of void provision on the wind-driven NV in residential Medium Cost Multi-Storey Housing (MCMSH)
cell) + CFX
Air velocities
Wind tunnel (open circuit) + CFD
3D steady-state RANS, SST k-ω Fluent (ANSYS)
Wind tunnel results of [63] + CFD Full-scale experiment in test chamber [184] + CFD Wind tunnel (Closedloop) + CFD (Fluent codes) Full-scale experiment (Velocity profile & Tracer gas) + CFD Full-scale experiment + CFD (Thermal comfort (SET*) ) Wind tunnel (Particle Image Velocimetr y (PIV)) [188] + CFD Full-scale experiment & Wind tunnel + CFX
7
radiation by DSF.
Flow rate (m3/s), IAV
By neglecting stack impact, 4-sided wind catcher provides heat dissipation instead of breeze.
3D-steady RANS, Sk-ε, Rk-ε, RNG kε Fluent (ANSYS)
AV & air flow rate
The optimum length & angle provide the best NV performance considering AV, flow rate, ACH, MAA.
3D-steady RANS, k-ω model, Fluent (ANSYS)
AT, Surface temperature, Airflow & CO2 sensors
Results highlighted vertical slide windows for providing the best NV performance.
Indoor airflow velocity and AT
The optimum streamwise distance reduced thermal cooling capacity by 10%.
3D-steady RANS, Standard k-ε & Fluent (ANSYS)
2D Unsteady RANS (URANS), Finite-volume, OpenFOAM
Airflow & AT
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
AT, IAV & Related Humidity (RH)
3D-steady RANS, k-ε turbulence model & Fluent (ANSYS)
Sk-ε, RNG k-ε & SST k-ω CFX (ANSYS)
Agreement between building simulation & CFD was remarkable in the prediction of outlet temperature & airflow profile. Incident WA is the vital balcony’s feature. SSV was more sensitive than a CV to varying design features.
IAV & ACH
Increasing on Trace’s depth has significant impacts on IAV by 88%.
AV & Thermal comfort
The suitable void configuration suggested, and results may contribute to better NV performance over void at MCMSH.
[190]
[191]
Tropical
Tropical
Void
Finding voids’ potential for NV in residential MCMSH
Wind tunnel [156]+ CFX
Sk-ε & CFX (ANSYS)
Wind pressure distributions on façade in different WA (°)
Courtyard
Effects of internal courtyards on NV to find innovative strategies for urban houses
Full-scale experiment
NA
AT, RH, and air pressure
Windcatcher
Study the best airflow & thermal comfort in six design scenarios of wind catcher (width & height).
Chimney
Achieve optimum NV through solar chimney by finding the optimal geometry.
Balcony
Influences of façade shape and openings on wind-induced NV (MAA & ACH)
Hot & dry
Atrium
Impact of atrium’s wall angularity on NV performance & thermal comfort.
[199]
Tropical
Balcony & Window
[200]
Subtropical (humid)
[192]
[194]
[27]
[197]
Desert (hot & arid)
Desert (hot & arid)
Subtropical (humid)
Patio
Impacts of orientation & height of buildings’ on NV. Find NV pros & cons in Yinzi, traditional Chinese, house as well as the best NV strategy.
[201]
Mediterranean climate (hot & arid summer)
Windows & Loggia
Effect of loggia & window opening size & façade porosity on CV rate.
[202]
Not a specific climate
Windows
Finding an innovative design for windows to get
Wind tunnel + another simulation [193] + CFD (Thermal comfort PMV & PPD) Full-scale experiment (prototype) + CFD Optimisati on Wind tunnel [195]+ CFD (Subconfigurati on validation [196])
3D steady-state RANS, Sk-ε, Rk-ε, RNG k-ε, SST k-ω & Fluent (ANSYS)
AT, AV & RH
Varying width has significant effects on IAD & AV. It is suggested to use this method for optimising wind catcher in other climates.
3D-steady RANS, RNG k-ε & Software (NA)
Flow rate, AT & external AV, Solar radiation
A specific geometry including inclination angle, length, width & air gap, introduced as the optimal design.
3D-steady RANS, RNG k-ε & Fluent (ANSYS)
IAV, ACH, outdoor wind speed & pressure distribution
Coupled CFD methods (finding indoor and outdoor flowrate at once) is useful to assess NV performance.
CFD + Previous analytical models [198]
3D-steady RANS, RNG k-ε & Software (NA)
No experiment
Full-scale experiment
No simulation
Indoor AT, RH, and air velocity
Full-scale orthogonal experiment + CFD
k-ε model & Fluent (NA)
Indoor & outdoor AT, humidity & AV
Full-scale experiment (tracer gas method) & empirical + CFD
3D-steady RANS, RNG k-ε & RSM & Fluent (ANSYS)
Wind speed, Flow rate & ACH
Wind tunnel (PIV) +
k-ε model & Fluent (ANSYS Airpack)
AV, ventilation Flow rate (m3/s)
8
Results highlighted the excellent potential of voids for MCMSH in the tropical climate. Close & CV courtyard can attain thermal comfort and avoid unnecessary humidity.
A mixture of vertical & tilted walls, respectively, at upper & lower floors, had the best NV performance. For investigating orientation, the unit layout should be considered. SV is the best NV strategy in Yinzi house based on the validated simulation results. Large windows on the façade enhance NV performance. Provision of loggia reduces ACH except for the direct airflow to opening. Rain penetration was dropped by 98%, while NV rate
the highest NV & lower dispersion of rain.
[203]
[205]
[171]
[207]
[208]
[133]
Not a specific climate
Hot & arid
Mediterranean climate (hot & arid summer)
Mediterranean (hot & arid summer)
Subtropical (humid)
Continental (humid)
Void & Lightwell
Windows
Patio
CFD
Impact of horizontal & vertical position of connected to lightwell void on the upward airflow.
Wind tunnel [204] + CFD
Focus on the indoor airflow & thermal comfort in a naturally ventilated room with a window opening.
Wind tunnel (open circuit) [206] + CFD & Network model + CFD & (PMV & PPD)
Explore aerodynamic features in a residential unit with a patio that connects indoor & outdoor. Effect of windows’ overhangs on thermal mass & night NV to provide a guideline for overhang’s length.
Wind tunnel + CFD
decreased by 4 & 9 % in defined scenarios.
3D-steady RANS, RNG k-ε, Rk-ε, SST k-ω & SST & Fluent (ANSYS)
k-ε model & Fluent (NA)
3D-steady RANS, k-ε model & Software (NA)
AT & Airflow rate & pattern
Void & lightwell had substantial effects on upward airflow in the interior of lightwell. Wind direction was the most crucial parameters that affect airflow pattern.
AT, AV & Pressure coefficient (Cp)
Window location is the most crucial factor in NV & thermal comfort as PMV & PPD improved up to 12% & 3.5% for the best location.
AV, Airflow profile
Enhancing the indoor airflow & modifying outdoor microclimate (around the building) can improve thermal comfort.
Full-scale experiment + Dynamic simulation
TRNSYS software
Wind speed & direction, indoor & outside AT, RH
Atrium
Optimum design of atrium for the NV usage using validated CFD, which was not well studied before.
Full-scale experiment + CFD
k-ε, RNG k-ε & Large Eddy Simulation (LES) & Fluent (NA)
AT, AV
Windows
Find the status of opening windows habit in winter via survey and the reflection of this habit on thermal comfort.
Full-scale experiment (Tracer gas) + Survey & Interview
Data analysis of survey by SPSS (Crosstab and Chisquare)
Windows & overhang
9
Air change rate, AT, feeling of IAQ (by survey)
NV integrated with horizontal shading devices, enhance thermal comfort & decrease cooling demand. Modelling shows bulk downward airflow that highlights the requirement of using precise simulation in atrium design. Effects of window opening size, wind direction & room size on the air change rate in winter were found based on results.
Table 5. A comparison between the most applied system simulation software Energy Plus
ESP-r
TRNSYS
IDA ICE
IES VE
CONTAM
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
YES YES
NO NO
NO YES
NO NO
NO NO
YES YES YES YES YES YES YES
YES YES YES YES YES YES YES
YES YES NO NO YES YES YES
YES YES YES YES YES NO YES
YES YES NO YES YES YES NO
YES YES NO YES YES YES YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
NO
NO
NO
YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
YES
YES YES
YES YES
YES NO
YES NO
YES NO
YES YES
YES NO YES NO YES NO
YES NO NO NO NO YES
YES YES NO NO NO NO
YES NO NO NO YES NO
YES NO NO NO YES NO
YES NO NO YES NO NO
Platform
Windows, Linux, and Mac
Windows, Linux, and Mac
Windows
Windows
Windows and Mac
Windows, Linux, and Mac
Pricing
Free
Open source
Reduced price for academic
Free Trial
Free Trial
Free
Features Simulation solution Iterative resolution of non-linear systems Simulation of loads, systems, & solutions Calculation time Variable time-step Dynamic variables (transient) Entire geometry description Surfaces including floors & walls Computation of thermal balance Import & export of geometry from CAD Import and export of models Thermal comfort of occupants General calculation of buildings Controllable windows for NV Airflow through the façade openings (i.e. balconies and windows) NV (Pressure and buoyancy driven) Mix-mode ventilation (NV & Mechanical) Multi-zone airflow (by pressure network) Implementation of occupants’ behaviour Control approach (Direct input) Co-simulation Major capabilities Energy simulation of entire building Detailed component simulation Load calculations Simulation of IAQ Code compliance Mixture of flow network & CFD domain General information
Relevant studies (Title-ABS-KEY (“software name” and “thermal comfort” and “natural ventil*”) AND Limit to (“ENGI” OR “ENER” OR “ENVI”) ) by August 2019 Total number of found articles 44 4 14 3 4 3 Number of articles over last 5 years 22 0 6 2 2 0 Most relevant studies (Title-ABS-KEY (“natural ventil*” and “thermal comfort” and “CFD” and “software name”)) Reference [214, 234] [235] -
10
Fig. 1. Schematic of natural ventilation (NV) strategies
Highlights • • • • •
The impacts of passive elements on natural ventilation (NV) are reviewed. Few studies characterise the impact of different balcony geometries on NV. The impact of balconies on NV needs to be quantified technically and socially. Research on the effectiveness of balconies in climates with prolonged summers is suggested. This review is a reference for future research of sustainable design.