The impact of thermal conductivity change of moist fibrous insulation on energy performance of buildings under hot–humid conditions

Energy and Buildings 60 (2013) 388–399

Contents lists available at SciVerse ScienceDirect

Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild

The impact of thermal conductivity change of moist fibrous insulation on energy performance of buildings under hot–humid conditions I. Budaiwi, A. Abdou ∗ Architectural Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia

a r t i c l e

i n f o

Article history: Received 26 July 2012 Received in revised form 4 January 2013 Accepted 23 January 2013 Keywords: Fibrous insulation material Thermal conductivity Moisture content Operating temperatures Building envelope Energy performance Hot–humid climate

a b s t r a c t The impact of the k-value change of fibrous insulation materials (i.e. fiberglass) in a typical wall–roof system due to moisture content levels on the thermal and energy performance of a typical residential building under hot–humid climatic conditions is investigated. Moisture performance is investigated utilizing theoretical long-term hygrothermal performance modeling and simulation techniques. Layer- and time-averaged levels of moisture content in the fibrous insulation are determined and the corresponding k-value change is evaluated from measured relationships. The impact of the k-value change due to moisture on the building thermal load and cooling energy performance of a residential building is then assessed utilizing detailed building energy simulation software. Limited change in the building cooling energy occurs as a result of the insulation k-value change due to moisture content occurring under moderate wetting conditions. When higher wetting conditions prevail the effect of k-value change on the building cooling energy continues to be limited although the impact of the roof on monthly cooling load is more pronounced especially during the summer months when as much as an 8% increase occurs. In general, the overall building energy performance is less affected by the k-value change of the moist fiberglass insulation under hot–humid conditions. © 2013 Elsevier B.V. All rights reserved.

1. Introduction As energy becomes more expensive and demand increases, the use of thermal insulation in buildings becomes more critical in new building constructions particularly in hot climates. Heat transfer by conduction through the building envelope represents a major component of the total thermal load of buildings. Reducing conductive heat gain through the walls and roof by using effective thermal insulation could lead to a significant reduction in thermal load and consequently reduce the overall electric energy consumption. The energy consumption index for an insulated typical detached singlefamily house in Dhahran, Saudi Arabia, characterized by hot–humid climate, was predicted to be around 153 kWh/m2 /year compared to 263 kWh/m2 /year for non-insulated residential buildings [1]. The reduction of annual energy index by around 42% proves the importance and effectiveness of thermal insulation in building envelope. The thermal performance of the building envelope depends to a great extent on the thermal effectiveness of the insulation layer which is mainly determined by its k-value. The k-value is dependent on the material density, porosity, moisture content and average temperature difference. Published k-values and those reported by manufacturers are normally evaluated at standard laboratory

∗ Corresponding author. Tel.: +966 3 860 2762; fax: +966 3 860 3785. E-mail address: [email protected] (A. Abdou). 0378-7788/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.enbuild.2013.01.035

conditions of temperature and humidity to allow a comparative evaluation of thermal performance. However, when placed in their locations in the building envelope, thermal insulation materials are exposed to different temperature and humidity levels depending on the prevailing climatic conditions, hence their actual thermal performance may substantially differ from that predicted under standard laboratory conditions. This may result in major deviations when predicting the thermal and the energy performance of the whole building. Cabeza et al. [2] compared experimentally the energy performance of three typical insulation materials, polyurethane, polystyrene, and mineral wool. Four house-like cubicles were constructed and their thermal performance throughout the time was measured under the prevailing climatic conditions. Energy reductions up to 64% in summer and up to 37% in winter were measured. The differences between insulation materials were found small but significant (less than 25% in most of the cases). Moreover, the impact of operating temperature on the thermal performance of insulation materials has been the subject of several studies. Abdou and Budaiwi [3] measured the thermal conductivity of various insulation materials at different operating mean temperatures. Their results indicated that higher temperature leads to higher k-values and that higher insulation density generally results in lower thermal conductivity. Budaiwi et al. [4] investigated the variation of k-value of insulation materials under different operating temperatures and its subsequent impact on envelope-induced cooling load. However, the equally paramount impact of potential

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

accumulation of moisture within the investigated thermal insulations and its subsequent reduction of the insulation actual thermal resistance were not considered. Bo-Ming et al. [5] measured the effective thermal conductivities of the fibrous insulation over a wide range of temperature (300–973 K) and reported that effective thermal conductivity increases non-linearly with increasing sample average temperature. However, the objective was to develop a 1D finite volume numerical model combined radiation and conduction heat transfer to predict the behavior of the effective thermal conductivity of the fibrous insulation at various temperatures and pressures. In addition to the operating temperature, the material moisture content is another major factor affecting the k-value of insulation materials. In buildings, insulation materials used in walls and roofs normally exhibit a higher moisture content when compared to test conditions. The ambient air humidity and indoor conditions, as well as the wall or roof system moisture characteristics, play an important role in determining the moisture status of the insulation material. When conditions are suitable (e.g. hot–humid climates), condensation can occur within the insulation material, raising its moisture content well above the hygroscopic level (i.e. unwetted at RH 98%). Higher thermal conductivity is obtained due to increased energy transfer by conduction and, under certain conditions, by the evaporation–condensation process, in which moisture moves from warm to cold regions. A good number of studies have dealt with heat transfer and thermal performance of insulation material in the presence of moisture. Unfortunately, little information is available on the variation of whole building thermal and energy performance under reduced k-value of building envelope insulation due to elevated moisture content levels. Ruut [6] studied comprehensively how a number of different porous insulation materials (mineral wool, cellulose fiber, etc.) performed hygrothermally under conditions similar to those in a typical building envelope. The initial water content and thickness of the fibrous insulation together with the environmental temperature were found to be the three most important factors influencing the heat flux [7,8]. Zheng et al. [9] analyzed the drying of an enclosure of a new building in its initial use period utilizing simulation. Insulation performance of the wall in the first winter was found the worst due to the high initial moisture content and freezing ice in porous insulation material. For the simulated enclosure, the maximum heat transfer coefficient in the first year was about 10% higher than that in the 10th year under the same outdoor climatic conditions. In order to reduce the energy consumption for air-conditioning buildings throughout their lifecycle, the thermal performance of insulation materials applied in buildings needs to be kept at the required value. Kondo et al. [10] examined the influences of moisture on thermal performance of various insulations based on first the relationship between equilibrium moisture content, second on the influence of gaseous moisture on fiber insulations and third on the reversibility of k-value after the internal dew condensation process and the dry process. Björk and Enochsson [11] studied experimentally the properties of condense formation. Drainage and moisture dependent heat transmittance were studied for three different thermal insulation materials: glass wool, melamine foam and corrugated sheets of cellulose plastic. The materials were quite different with respect to condense formation and maximal moisture accumulation at similar environmental conditions. They also showed considerable differences in moisture influence on thermal transmissivity. The higher the moisture accumulation, the greater the influence of moisture on thermal transmissivity at a steady state. Gawin et al. [12] quantified the effect of initial moisture on the hygrothermal and energy performance of autoclaved aerated concrete (AAC) used in a house located in Warsaw, Poland. Space- and time-averaged values of moisture content, thermal conductivity, apparent density, and

389

specific heat of the cellular concrete layer were calculated for each month of the analyzed period. These averaged material properties were then used in DOE-2.1 simulations of the energy performance of the whole building. Monthly values of energy released or absorbed on the internal surface of the wall, due to the condensation or evaporation of moisture, were calculated and used to approximate the total effect of initial moisture drying on energy performance of the whole building. Based on the above it is evident that little information is available on the variation of whole building thermal and energy performance under reduced k-value of building envelope insulation due to elevated moisture content levels. Given the potentially sufficient impact of moisture content on k-value and its subsequent consequences on the thermal and energy performance of buildings, it is important to investigate the moisture behavior of insulation materials and the k-value variation and the resulting effect on the thermal and energy performance of the building. The objective of this study is to investigate the impact of the k-value change of fiberglass due to moisture content on the thermal and energy performance of the whole building when subjected to hot–humid conditions. The results are expected to be of great help to material manufacturers, building owners and designers for proper building envelope design and to accurately predict the whole building thermal and energy performance under hot–humid climatic conditions.

2. The study methodology Wall and roof assemblies are designed to control heat, air, and moisture transfer between outdoor and indoor environments. The thermal insulation layer is a critical determinant of the exterior envelope thermal performance but can be greatly influenced by moisture content conditions. In order to assess the impact of thermal conductivity variations due to the moisture content level on building thermal and energy performance, the relationship between thermal conductivity and moisture content of the insulation material and moisture conditions of the insulation material within the wall–roof assembly are required. To help predict the moisture conditions of building envelope assembly when subjected to given climatic conditions a theoretical simulation model capable of predicting the long-term hygrothermal performance of the different assembly components is used. Typical wall–roof systems that are commonly constructed under the hot–humid climatic conditions represented by Dhahran, Saudi Arabia are modeled and simulated. The results of the simulation including the thermal insulation layer moisture content over the simulation period is used as the primary output for predicting the change of thermal conductivity due to moisture content. The impact of thermal conductivity change with moisture content on building thermal and energy performance is investigated by modeling the performance of a typical residential building under hot–humid climatic conditions. The range of magnitude of moisture content in the fibrous thermal insulation materials was determined based on the simulation results and the corresponding thermal conductivity were evaluated from the measured relationship at an operating temperature of 24 ◦ C. The building thermal and cooling energy performance under resulting different thermal conductivity values is determined utilizing the well-known energy simulation VisualDOE software tool. The impact of k-value change due to moisture accumulation, within the fibrous insulation material in the wall–roof system, on the cooling load was investigated by considering the contribution of the wet wall–roof system to the thermal load during the cooling periods. Fig. 1 depicts a flowchart showing components of the research methodology and approach as detailed in the above discussion.

390

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

Measurements

Modeling and Simulation of Heat and Moisture Transfer (WUFI)

Measure k-value of Fiberglass with Varying Moisture Content at Different Operating Temperatures

Assess Simultaneous Heat and Moisture Performance of Building Envelope System

Establish Relationship of kvalue vs. Moisture Content

Determine Magnitude of Moisture Accumulation in Insulation Material under Given Climatic Conditions

Modeling and Simulation of Thermal and Energy Performance (VisualDOE)

Investigate Impact of k-value Change on Thermal and Energy Performance of Whole Building

Fig. 1. Flowchart showing components of the methodology and approach followed by the study.

3. Measurements of thermal insulation k-values 3.1. Measurement procedure and apparatus In order to achieve Phase I: Measurements of the study (see Fig. 1), fibrous thermal insulation samples with a standard size of 300 mm × 300 mm and nominal thickness of 50 mm representing the most commonly used insulation materials in buildings were collected. The samples included (in addition to rock and mineral wool) fiberglass of five different mass densities (27, 47, 65, 70 and 84 kg/m3 ). These samples were conditioned and their k-values measured at different moisture content levels and variable operating temperatures. In order to account for variations in sample densities and to better assess the relative moisture content of different samples, the actual density of each test sample at the dry condition was determined using a sensitive digital weighing scale with 0.01 g accuracy. To increase the moisture content of the test sample, a bench-top stainless steel container with a controllable electric-coil which heats an adequate volume of de-ionized water was also used. The apparatus adds moisture to the test sample (mounted over a stainless mesh holder) by heating up the volume of de-ionized water. The sample was turned upside down every 15 min, to ensure a uniform exposure of the sample central part to the rising vapor over its thickness. The mass density of the sample was frequently monitored till a desired amount of moisture content percentage (by weight) was achieved but not necessarily a precise level of moisture content as this was difficult to precisely control. The sample was then removed from the container, immediately wrapped with a thin plastic film in order to maintain its moisture content and kept for a few hours at room temperature. The k-value of the test sample was then measured using the heat flow meter. To test the same sample at different and reduced levels of moisture content, the conditioned sample was unwrapped and kept at the room temperature with its weight frequently monitored until its moisture naturally decreased to a lower moisture content. During this process the sample was flipped over every 15 min to maintain uniform moisture distribution over its thickness. The process was repeated for a second lower level of moisture content. A state-of-the-art heat flow meter apparatus (i.e. Holometrix, Type Lambda 2300 V) [13] was utilized to measure the k-value. The measurement system is a complete PC-automated system designed to determine the thermal conductivity as per the ASTM C51891 (1991) [14] and ISO 8301:1991 [15] protocols. A specimen (300 mm × 300 mm) with a thickness ranging from 5 to 100 mm can be placed in the test section of the heat flow meter between

two plates, which are maintained at different temperatures during the test. Upon achieving thermal equilibrium and establishing a uniform temperature gradient throughout the sample, the k-value is determined. The temperature control system is thermoelectric. An external computer system with specialized software (i.e. Holometrix Q-LAB software) controls the measuring apparatus, records, and prints results. To minimize errors, the apparatus can be easily calibrated with a reference standard specimen (i.e. supplied by National Institute of Standard and Test (NIST)) to measure the response of the heat flow transducer at different temperatures. The most important features of this automated system are accuracy and reproducibility. Accuracy is the degree of variation for a measurement, taking into account the reproducibility and all physical aspects of the instrument and the test. The accuracy of the apparatus ranges from ±1.0 to ±3.0%, while repeatability is around ±0.3%. This means that the variation of the test results of the same specimen is around 0.3% from one test to another. Prior to the testing of the selected samples, the measuring instrument was calibrated using a reference sample as per a defined calibration procedure. In order to verify the accuracy and ensure reproducibility, the reference sample was tested 10 times over an extended period of time. The accuracy and repeatability of the k-value measurement were confirmed within a mean error of around ±0.2% and a standard deviation of ±0.1%. The area of the heat flow transducer (10 cm × 10 cm) is smaller than the cross-sectional area of the specimen. The part of the specimen surrounding the area over which the transducer monitors heat flow acts as an effective guard against lateral heat flow. 3.2. Measurement results Utilizing the test sample preparation and the standard thermal conductivity measurement procedure discussed above, the samples were tested at different levels of moisture content under three operating temperatures. Results of k-value variation with moisture content and operating temperatures for only fiberglass samples having densities of 65 and 66 kg/m3 are utilized for the purpose of the current study are shown in Fig. 2. Due to limitations in sample preparation and measurement techniques, it was difficult to precisely control the moisture content at specific constant levels. In order to compare thermal conductivity variations for the different samples at the same operating conditions the linear relationship between the measured k-value and the resulting operating temperature is established. This best-fit linear relationship is shown in Fig. 2(a) and (b) where parameters of the linear relationship are indicated. The relationship between thermal conductivity and

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

391

Fig. 2. Best-fit linear relationships of k-value measurement results of fiberglass vs. operating temperatures and different percentages of moisture content (MC, % by weight): (a) fiberglass density 65 kg/m3 , (b) fiberglass density 66 kg/m3 , (c) and (d) regression data of k-values vs. moisture content level at 14, 24, and 34 ◦ C operating temperatures.

moisture content at a specified operating temperature was then obtained for the same operating temperature. Fig. 2(c) and (d) illustrate the numerical interpolation of k-values at the operating temperatures of interest namely 14, 24 and 34 ◦ C. Utilizing the resulting relationships, the k-value of the fibrous insulation material at a specific moisture content and operating temperature can be obtained. These relationships are established as part of a comprehensive measurement study conducted by the authors to investigate the variations of thermal conductivity with moisture content. Results have indicated that thermal conductivity is not only variable with moisture content kevel but also with the history and initial level of exposure to moisture. To address the impact of these conditions, thermal conductivity variations with moisture content for two different initial moisture content levels for modeled fiberglass insulation material (shown in Fig. 2) are considered. 4. Modeling and simulation of wall–roof systems It is evident that knowledge of moisture content behavior of the insulation material within the exterior envelope system is required in order to predict the change in insulation k-value and its subsequent impact on the thermal and energy performance of the building. To help predict moisture performance of a given building envelope assembly subjected to certain climatic conditions over a given period of time, a suitable software tool capable of modeling and simulating the long-term hygrothermal performance of construction assemblies needs to be utilized. 4.1. Selection of the modeling software A variety of state-of-the-art tools have been developed for modeling and simulating the long-term hygrothermal performance of construction assemblies. One such tool is WUFI [16],

developed at the Fraunhofer-Institute for Building Physics, which allows realistic calculation of the transient hygrothermal behavior of multi-layer building components exposed to natural climate conditions. Another simulation tool is the hygIRC 1D, developed by the IRC [17]. A review conducted by Delgado et al. [18] presented the coupled thermal and moisture transfer for 1D or multidimensional cases. Fourteen hygrothermal modeling tools were considered in the analysis and the results of WUFI and hygIRC for the prediction of exterior superficial temperatures on facades were compared and analyzed. WUFI was found to be more precise in quantitative computation of night-time cooling. Furthermore, comparative measurements of five wood-based building elements were performed at the campus of the Fraunhofer Institute of Building Physics for thermal and moisture transfer using WUFI Pro. Simulation results were in agreement with the experimentally measured thermal conductivity values [19]. Another analysis described the hygrothermal behavior of stabilized rammed earth walls using WUFI Plus [20]. Antretter et al. [21] provided a validation study on the hygrothermal performance of WUFI Plus where the model was validated using existing standards and guidelines namely ASHRAE 140-2007 and VDI 6020 respectively. The model showed good results when compared to the ASHRAE standard and VDI guideline with the calculation results being comparable to the reference values. A small-scale laboratory experiment was also conducted for validation purposes where the model was successfully evaluated using the measurements of the hygric conditions of the laboratory. For the purpose of this study, the moisture performance simulation model WUFI PRO 5.0, which is a windows-based program for the hygrothermal (i.e. heat and moisture) analysis of building envelope constructions, is selected. The WUFI simulation model is a transient heat and mass transfer model which can be used to assess the heat and moisture distributions for a wide range of

392

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

Fig. 3. Cross sections of the modeled construction assemblies, i.e. (a) wall system and (b) roof system.

building material classes and climatic conditions. WUFI can provide customized solutions to moisture engineering and damage assessment problems for various building envelope systems and can estimate the drying times of masonry and lightweight structures with trapped or concealed construction moisture. It can also be used to investigate the danger of interstitial condensation or study the influence of driving rain on exterior building components. The software tool can also help to select repair and retrofit strategies with respect to the hygrothermal response of particular roof or wall assemblies subjected to various climates. This allows the comparison and ranking of different designs with respect to total hygrothermal performance.

is replaced by a layer of clay brick having the same thickness. The exterior surface solar absorptance and emissivity for both walls are assumed to be 0.4 and 0.9 respectively. The roof system is mainly composed of a 200-mm thick concrete slab with a 15-mm plaster layer from the interior; a waterproof membrane is placed above a 50-mm thick concrete sloping screed. A 75-mm fiberglass insulation layer is placed over the waterproof membrane covered with a weather resistive barrier and a layer of 30-mm sand stone. The total R-value of the roof assembly is 2.66 m2 C/W. Fig. 3(a) illustrates the main composition of the wall and roof systems. Their corresponding thermal and moisture characteristics are given in Tables 1 and 2.

4.2. Characteristics of the modeled construction assemblies

4.3. Preparation of weather data file

Moisture performance of the insulation layer in wall and roof construction systems under given climatic conditions is dependent on the system composition and thermal and moisture characteristics of comprising elements. In this study, moisture performance of a fiberglass insulation layer with a density of 65 kg/m3 as part of typical heavy wall and roof construction systems is investigated under hot–humid climatic conditions represented by Dhahran, Saudi Arabia. Two wall system assemblies are considered. The first wall, which will be referred to as Wall-1, is composed of a 200-mm thick concrete block layer (pumice aggregates), a 50-mm insulation layer, a 13-mm thick interior gypsum board and a 19-mm concrete stucco from the exterior with a total R-value of 3.14 m2 C/W. The second wall, which will be referred to as Wall-2, with a total R-value of 2.11 m2 C/W, has the same composition except that the main component (i.e. concrete block)

The WUFI simulation software requires hourly weather data for a full year including hourly dry-bulb temperature, solar radiation, humidity, and wind speed and direction. The weather data of Dhahran (Lat. 26◦ 27 N, Long. 50◦ 17 E, 17.0 m above sea level) in Saudi Arabia is used as representative of typical weather variations in the Eastern Province of Saudi Arabia. The hourly weather data for Dhahran, representing hot–humid climatic conditions was prepared for the year 2005 according to the required format. Dhahran’s climate is characterized by hot and humid summers. Temperatures can rise to more than 50 ◦ C (120 ◦ F) in the summer, coupled with extreme humidity (85–100%). The city holds the record for the highest temperature in the kingdom: 51.1 ◦ C (124 ◦ F), as recorded in August 1956. In winter, the temperature rarely falls below 2 ◦ C (35.6 ◦ F) or 3 ◦ C (37.4 ◦ F), with the lowest ever recorded −0.5 ◦ C in January 1964, with rain falling mostly between the months

Table 1 Thermal and moisture characteristics of the components of modeled walls.

Component Interior air film Gypsum board Fiberglass insulation Concrete Block (pumice aggregates) or [Clay Brick]* Stucco layer Exterior air film

Thickness (mm)

Density (kg/m3)

Thermal conductivity, (W/m.K) [Resistance, m2.K/W]*

Permeability (Kg/m.s.Pa)

13 50 200

625 65 664

[0.125]* 0.16 0.031 0.14

2.76. 10-11 1.078. 10-10 4.85. 10-11

[200] 19 -

[1935] 2000 -

[0.495]* 1.2 [0.059]*

[1.408. 10-12] 7.76. 10-12 -

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

393

Table 2 Thermal and moisture characteristics of the components of modeled roof system.

Component

Thickness (mm)

Density (kg/m3)

Thermal conductivity, (W/m.K) [Resistance, m2.K/W]*

Permeability (Kg/m.s.Pa)

Exterior air film Sandstone Weather resistive barrier Fiberglass insulation Roof membrane Concrete screed Concrete slab Interior plaster Interior air film

30 0.001 75 3 50 200 15 -

2224 130 65 2400 1990 2300 850 -

[0.059]* 1.68 2.3 .031 0.5 1.6 1.6 .2 [0.125]*

2.66 10-12 3.88 10-13 1.08 10-10 1.94 10-15 1.96 10-12 1.08 10-12 2.34 10-11 -

of November and May. Dominant northern winds usually blow across the city in the early months of the summer, bringing dust storms that can reduce visibility to a few meters. The cooling design conditions (at 1%) are 43.3 ◦ C dry-bulb (DB) temperature with 22.9 ◦ C mean coincident wet-bulb (MCWB) design temperature. The annual heating and cooling degree-days at 18.3 ◦ C base temperature are 205 and 3284 ◦ C-days respectively [22]. 4.4. Simulation results of long-term hygrothermal performance of wall–roof Using the selected simulation tool, moisture performance of the two modeled wall systems and the roof system is predicted over a period of one year under different indoor air temperatures (i.e. 18, 21 and 24 ◦ C). Additionally, the impact of wall orientations and interior surface treatments is simulated. Moisture performance can be assessed based on the wetting and drying events and the resulting moisture accumulation and distribution over a given period of time within the different components of the construction system. Considering the current research objectives, the monthly average moisture content of the insulation layer is calculated from the predicted hourly average values. These monthly average values are used for investigating and comparing wall and roof moisture performance under different conditions. As indicated in Table 1, the two modeled wall systems have similar secondary components but differ in the primary wall component. The primary component is concrete block with pumice aggregate in Wall-1 and clay brick in Wall-2. It must be noted that vapor permeability of the concrete block is 35 times more than the clay brick layer. Since the primary layer is located to the interior side of the insulation layer and the source of diffused moisture is mainly from the outside environment, the primary layer with higher permeability is expected to act as a moisture absorbing bed hence reducing the potential of moisture accumulation in the insulation layer. On the other hand, the low permeability of the primary layer will act as a vapor retarder consequently resulting in higher moisture accumulation potential. 4.4.1. Effect of boundary and exposure conditions Fig. 4 illustrates moisture accumulation variations in the insulation layer of Wall-1 and Wall-2 over a period of one year at different boundary and exposure conditions. Fig. 4(a) illustrates moisture accumulation variation in the insulation layer of Wall-1 [Part I] and Wall-2 [Part II] for different interior surface treatments when the construction assembly is facing north when indoor temperature is maintained at 21 ◦ C. It can be seen that for Wall-1 the highest moisture accumulation occurs during the winter months while the minimum moisture accumulation occurs during summer. Such behavior is indicative of the absence of condensation during the summer months and the resulting variation in moisture content is due to changes in material hygroscopic capacity in response

to local relative humidity conditions. By adding an oil paint layer to the interior surface, the yearly moisture accumulation profile exhibited an upward shift through out the year with a maximum increase of more than 20% occurring during the winter months. The presence of an oil-based paint layer on the interior surface added a relatively higher moisture resistance compared to the other wall components comprising Wall-1. This resulted in a reduced moisture transfer to the interior environment and consequently caused more moisture to be trapped within the various wall components including the insulation layer. It can be concluded that a different moisture behavior of the insulation layer is attained depending on the moisture characteristics of other wall components and surface treatment. Fig. 4[Part (II)] illustrates the insulation layer moisture behavior for Wall-2. It is evident that the presence of a high moisture resistance layer (the red brick) to the interior of the insulation layer has acted as a vapor retarder and resulted in a major shift in moisture accumulation throughout the year but in particular during the month of July and beyond. This moisture behavior is indicative of the occurrence of interstitial condensation within the insulation layer or at its interior boundary with the brick layer. The maximum moisture accumulation occurs in the month of November (about 5.5% by weight) when the outside temperature is low enough and the air humidity is high enough to initiate considerable condensation. It can also be noted that the interior paint has no impact on moisture accumulation behavior due to the moisture characteristics of the primary layer of the wall system. Fig. 5 compares the behavior of Wall-1 and Wall-2 (at north) in the presence and absence of an interior paint layer. It is clear that for both cases, Wall-2 has a higher potential for moisture accumulation with the highest difference occurring during the month of November. Moisture accumulation within the various wall system components depends to a great extent on the temperature profile across the different components as it is a major determinant of local relative humidity and hence the conditions necessary for the occurrence of interstitial condensation within the wall system. Changing the indoor temperature or the wall orientation, which impacts exposure to solar radiation, will result in different temperature profiles. Reducing the indoor air temperature results in lowering the temperature profile and consequently is expected to lead to increased moisture accumulation potential. Fig. 4(b) illustrates the impact of indoor temperature on moisture accumulation in the insulation layer for both modeled walls. It is apparent that lower indoor temperature results in higher moisture accumulation but the level of impact is highly variable depending on type and characteristics of construction elements composing the wall system. For Wall-1 (Fig. 4(b)[Part I]), it can be seen that in spite of some noticeable increase in moisture accumulation at the lower temperature particularly during the winter months, the change

394

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

Fig. 4. Average moisture content in the thermal insulation layer in Wall-1 and Wall-2: (a) comparison between the wall at north with and without interior paint (at 21 ◦ C indoor temperature), (b) at three different indoor temperatures, and (c) at different wall orientations (at indoor temperature of 21 ◦ C).

in moisture accumulation due to indoor temperature is generally limited. This can be explained by the fact that for the construction type of Wall-1, conditions are not suitable to introduce condensation within the insulation layer even at an indoor temperature of 18 ◦ C. On the other hand, Wall-2 exhibits major change in moisture behavior with indoor temperature as depicted in Fig. 4(b)[Part II]. The increase in moisture accumulation is indicative of the higher potential for the occurrence and frequency of interstitial condensation and is noticeable in all month except the month of June while the highest increase in moisture accumulation occurs during the month on November at all temperatures. The highest shift occurs at

an indoor temperature of 18 ◦ C where the average moisture content reaches about 11.5% compared to 3.5% at 24 ◦ C. From the above discussion, it is clear that the impact of the temperature profile across the wall system on the moisture behavior is significant. It must be noted, however, that besides the indoor and outdoor temperatures, the moisture profile across a given wall system is influenced by the amount of solar radiation received on its exterior surface. A different and variable amount of solar radiation is received on various wall orientations resulting in different temperature profiles and consequently different moisture behavior. Fig. 4(a)[Parts I and II] shows comparison of moisture

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399 Wall-1, With Interior Paint Wall-2, With Interior Paint

8.0

10.0 6.0

9.0 8.0

5.0

7.0 4.0

6.0 5.0

3.0

4.0 2.0

3.0 2.0

1.0

Average Moisture Content, % (by weight)

11.0

Average Moist ure Cont ent , kg/m 3

12.0

7.0 Average Moist ure Cont ent , kg/m 3

Without Roof Membrane (RM)

1.0 0.0

RM above

RM below

6.0

9.0 8.0

5.0

7.0 4.0

6.0 5.0

3.0

4.0 2.0

3.0 2.0

1.0

Average Moisture Content, % (by weight)

Wall-1, Without Interior Paint Wall-2, Wihtout Interior Paint

395

1.0 0.0

0.0

0.0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Month

Month

behavior of the two modeled walls for different orientations. It can be seen that differently oriented walls behave differently with the north wall having the highest moisture accumulation and the south wall having the least moisture accumulation throughout the year. Little variation in moisture accumulation can be observed during the summer months for both walls while the maximum variation occurs during the winter months. The magnitude of change in moisture accumulation due to wall orientation is more pronounced in Wall-2 with as much as 3% increase in average moisture content in the months of November and December. On the other hand, Wall1 has a more consistent response to orientation with a noticeable variation in moisture accumulation during most of the months. It is evident that the moisture behavior of the wall system is dependent on many factors related to its physical, thermal and moisture characteristics but additionally on the environmental factors such as air temperature and solar radiation. The roof is the most important component of the exterior envelope which determines the overall performance of the building. Moisture behavior of the roof depends to a larger extent on thermal and moisture characteristics of the comprising components but more significantly on the arrangement of the insulation layer relative to the roof membrane due to its high resistance to moisture transfer. Additionally, the roof receives the highest amount of solar radiation throughout the year compared to any building envelope surface. This will ultimately influence the temperature profile across the roof system and consequently the potential of condensation and moisture accumulation within the insulation layer.

Fig. 6. Comparison between average moisture content of roof system without roof membrane (RM), RM above, and RM below the insulation layer (at 21 ◦ C indoor temperature).

be deposited in the insulation layer. No major accumulation occurs during the month of June for all cases. This can be explained by the fact that the roof receives the highest amount of solar radiation during the month of June causing an elevated temperature profile across the insulation layer which leads to reduced condensation potential. The effect of indoor temperature on temperature profile and the subsequent impact on moisture accumulation in the roof insulation layer is shown in Fig. 7. It can be seen that more moisture is accumulated at a lower indoor temperature. The lowest accumulation occurs during the summer months at all indoor temperatures. Decreasing the indoor temperature from 24 ◦ C to 21 ◦ C resulted in a noticeable increase in moisture accumulation but with no change in the month of June. The highest change occurs on the months of November and December with about 30% increase in average moisture content. A more pronounced increase in moisture content occurs at an indoor temperature of 18 ◦ C with an almost 200% increase in moisture content in the month of December. It is also worth noticing that at 18 ◦ C the whole moisture accumulation curve is shifted up including in the month of June. In comparison with wall moisture behavior, it can be seen that when the roof membrane is placed below the insulation layer in hot–humid climate, the indoor temperature has generally more influence on the roof system moisture performance as it is a critical factor in dampening the effect of solar radiation and increasing the condensation potential

o

18 oC

o

24 oC

12.0 Average Moisture Content, kg/m 3

4.4.2. Impact of roof membrane location Fig. 6 compares moisture behavior of the insulation layer of the modeled roof system at 21 ◦ C for different arrangements of the roof membrane. Placing the roof membrane to the outside of the insulation layer results in minimum moisture accumulation throughout the year. In the absence of a roof membrane or when the membrane is placed below the insulation layer, major moisture accumulation occurs with the highest occurring during the month of December. As much as 500% increase in moisture content is obtained when no roof membrane is used and as much as 700% increase is obtained when the roof membrane is placed below the insulation layer. This level of moisture accumulation is indicative of the occurrence of condensation due to the high moisture resistance offered by the other components comprising the roof system particularly when the roof membrane is placed below the insulation layer. In this case, the roof membrane introduces additional moisture resistance and blocks moisture transfer across the roof system forcing it to

o

21 oC

18.0 16.0

10.0

14.0 8.0

12.0 10.0

6.0

8.0 4.0

6.0 4.0

2.0

Average Moisture Content, % (by weight)

Fig. 5. Comparison of moisture content in the insulation layer of Wall-1 and Wall-2 (at North) with and without interior paint (at indoor temperature of 21 ◦ C).

2.0 0.0

0.0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Month

Fig. 7. Comparison between average moisture content of the roof system with roof membrane (RM) below the insulation layer at 18, 21 and 24 ◦ C indoor temperatures.

396

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

Table 3 Summary of thermal and operational characteristics of the modeled house.

by lowering the temperature profile across the construction system. However, the placement of the roof membrane relative to the insulation layer is the critical factor in determining roof moisture performance regardless of the indoor temperature. 5. The impact of k-value change due to moisture content on the building thermal and energy performance 5.1. Formulation of the building energy model Accurate prediction of building thermal and energy performance including cooling load and HVAC equipment sizing requires an accurate account of heat gain and loss through envelope components. In buildings with envelope-dominated thermal loads the bulk of heat gain and loss occurs through conductive heat transfer through the exterior envelope components. Thermal insulation provides the greater part of the thermal resistive value offered by walls and roofs. However, the effectiveness of thermal insulation is dependent on moisture content as previously illustrated. In order to investigate the impact of k-value changes due to moisture content on building thermal and energy performance, envelope-induced cooling load and energy consumption of a typical residential building located in Dhahran Saudi Arabia is predicted. The building is a single-story (20 m × 20 m × 3.5 m) maintained at 21 ◦ C and is assumed to operate at residential load profiles with an air infiltration rate of 0.35 ACH (air change per hour). Windows are clear double-glazing shaded from the inside and distributed uniformly over 10% of the wall area. The wall system used for the purpose of this study is similar to that illustrated in Fig. 3(a) and described in Table 1 with the clay brick as the main component. The modeled

roof system is illustrated in Fig. 3(b) and described in Table 2. A summary of thermal and operational characteristics of the modeled house including occupancy, lighting and equipment profiles are illustrated in Table 3. The building energy simulation VisualDOE [23] program is utilized to predict building energy performance at different thermal insulation conductivities corresponding to dry and wet conditions. The dry and wet conditions refer to the level of moisture content in the insulation layer. The dry condition refers to the situation when no non-hygroscopic moisture exists within the material. The wet condition refers to the presence of nonhygroscopic moisture and is represented by the different moisture content levels as predicted by the moisture performance simulation tool under Dhahran climatic conditions. The amount and distribution of moisture accumulation within the insulation layer of a building construction system and consequently the corresponding k-values are variable with time and are dependent on construction orientation and position. For the purpose of this study, average monthly moisture content based on hourly average moisture content across the insulation layer is used to predict changes in thermal conductivity. The thermal conductivity value corresponding to particular moisture content is obtained from the experimental results corresponding to fiberglass insulation material shown in Fig. 1. The relationship between k-value and moisture content, however, is dependent on the wetting and drying history of the material and the resulting alteration of material matrix and its internal structure. Exposure to higher wetting conditions has been shown to result in a different relationship between k-value and moisture content. Table 4(a) illustrates the average moisture content within the fiberglass insulation layer and the corresponding k-value for differently oriented walls and the roof for

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

397

Table 4 Average moisture content within the fiberglass insulation layer (i.e. as a result of long-term hygrothermal simulations) and the corresponding determined k-value for differently oriented walls and the roof for four periods over the year (*k-value measured at high-initial moisture content, i.e. 29.0%. Percentage increase in average k-value in this case is indicated).

WALLS N. Wall Period DEC-JAN-FEB MAR-APR-MAY JUN-JUL-AUG SEP-OCT-NOV Average % increase in k-value

MC % 2.0 1.0 1.0 2.6

E. Wall

k-value

k-value*

0.03257 0.03237 0.03236 0.03269

0.03441 0.03337 0.03332 0.03499

0.03250

MC % 1.3 0.7 0.7 1.8

0.03402

S. Wall

k-value

k-value*

0.03244 0.03230 0.03231 0.03253

0.03371 0.03300 0.03307 0.03419

0.03239

0.03349 3.4

4.7

MC % 0.8 0.6 0.9 1.4

W. Wall

k-value

k-value*

0.03232 0.03229 0.03234 0.03245

0.03313 0.03295 0.03320 0.03375

0.03235

MC % 1.7 0.9 1.0 2.3

0.03326

k-value

k-value*

0.03250 0.03235 0.03236 0.03263

0.03402 0.03324 0.03331 0.03471

0.03246

2.8

0.03382 4.2

ROOF No RM**

DEC-JAN-FEB MAR-APR-MAY JUN-JUL-AUG SEP-OCT-NOV Average % increase in k-value

k-value

k-value *

0.03287 0.03244 0.03231 0.03257 0.03254

RM, on Top MC % 0.5 0.4 0.3 0.4

k-value

RM, on Bottom

k-value *

0.03590 0.03228 0.03289 0.03372 0.03224 0.03271 0.03304 0.03222 0.03261 0.03436 0.03224 0.03272 0.03425 0.03224 0.03273 5.3 1.5 ** RM = Roof Membrane

four periods over the year. The k-value for a given moisture content is derived based on experimental data for the 66 kg/m3 fiberglass sample shown in Fig. 1 where the initial conditioning moisture content (about 13.6%) is comparable to the maximum predicted moisture content of about 11.6% for the modeled wall in the month of November at an indoor temperature of 18 ◦ C and about 16.9% for the modeled roof in the month of December when a waterproof layer is placed below the insulation layer at an indoor temperature of 18 ◦ C. Table 4(b) illustrates similar results when the k-value change due to moisture content is evaluated based on k-value and moisture content relationship corresponding to initial conditioning moisture content of 29.0%. Given the level and pattern of predicted moisture accumulation within the insulation layer for the modeled wall and roof systems under Dhahran climatic conditions, it is justifiable to use the k-value change corresponding to the lower initial conditioning moisture content indicated in Table 4(a) for predicting building energy performance variations due to k-value change. Furthermore, due to the limited range of variation of k-value corresponding to the average moisture content over the year, the yearly average k-value is used. However, variations in k-value for differently oriented walls are accounted for in the model. The roof system type with waterproofing below the insulation layer being a common type of roof construction is considered in the model. 5.2. Simulation results of the building energy performance The impact of k-value variations due to moisture content on building energy performance is investigated by comparing monthly cooling load contribution of the dry and wet walls and roof to the thermal load. Additionally, monthly cooling energy is compared for the dry and wet wall–roof conditions. The dry and wet wall or roof refers to the moisture content status of the thermal insulation within the construction. Fig. 8 illustrates the monthly thermal load contribution of the walls and the roof under dry and wet conditions during the cooling periods. It can be depicted that no noticeable

MC % 4.6 2.3 0.9 3.1

k-value

k-value *

0.03310 0.03262 0.03234 0.03279 0.03271

0.03708 0.03464 0.03322 0.03552 0.03512 7.3

change occurs in the walls and roof contributions due to the change in insulation thermal conductivity. Similarly, no change is noticed in the monthly cooling energy for the whole building as shown in Fig. 9. This limited change in energy performance is expected given the fact that the increase in wall and roof thermal conductivities for the wet conditions as predicted under Dhahran climatic conditions is small. It can be observed from Fig. 9 that a need for cooling energy during winter months (i.e. December, January, and February) exists. This can be explained by the fact that the monthly average of outdoor temperatures ranging from 16.0 to 19.0 ◦ C under Dhahran’s weather conditions during the winter months, is not significantly lower than the maintained indoor temperature (21 ◦ C). Additionally, availability of solar radiation on horizontal surfaces (e.g. average of 285 w/m2 ) during the daytime of the winter months due to prevalence of clear sky is expected to induce positive thermal load during certain hours. Furthermore, in view of the relatively

Dry Wall

Wet Wall

Dry Roof

Wet Roof

3000 CoolingThermal Energy,Load, kWh kWh Monthly

Period

MC % 3.5 1.4 0.7 2.0

2500 2000 1500 1000 500

+

contributio0n

-

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

-500

Month Fig. 8. Monthly thermal load contributions of dry and wet walls and roof during cooling periods.

398

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

Dry Wal-Roof

Wet Wall-Roof

Dry Wal-Roof

12000

Total Increase = + 2.0 %

Total Increase = + 0.4 %

10000

Cooling Energy, kWh

Cooling Energy, kWh

10000 8000 6000 4000 2000

8000 6000 4000 2000 0

0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Month

Month Fig. 9. Monthly cooling energy for the whole building for dry and wet envelope.

assumed airtight enclosure of the house (i.e. 0.35 ACH) and the internal loads resulting from occupancy, lighting and equipment, it is likely for the cooling system to operate partially during winter months. 5.2.1. The effect of initial moisture content The relationship between the k-value and the moisture content has been shown to be dependent on the wetting history of the material. At extreme climatic and environmental conditions, the insulation layer can be exposed to a very high moisture content. The magnitude of change in k-value due to moisture content is likely to be more pronounced when the insulation material is exposed at a given time to high wetting conditions. In order to appreciate the impact of insulation k-value change due to moisture content when insulation layer is exposed to high initial wetting conditions, building energy performance is predicted for the thermal conductivities change corresponding to an initial moisture content of 29% as shown in Table 3. Fig. 10 illustrates the monthly cooling load contribution to the building load corresponding to wet wall and roof systems in comparison with dry conditions. It can be seen that the impact of k-value change due to moisture content on wall thermal performance continues to be limited even at higher initial wetting conditions. The impact is more noticeable for the roof contribution to the load especially during the summer months when as much as 8% change occurs. The overall energy performance represented by

Dry Wall

Wet Wall

Dry Roof

Wet Roof

CoolingThermal Energy,Load, kWh kWh Monthly

3000 2500 2000 1500 1000 500

+ 0

-

contribution

Wet Wall-Roof

12000

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

-500

Month Fig. 10. Monthly thermal load contributions of dry and wet wall and roof systems during cooling periods with k-value change corresponding to 29% initial moisture content.

Fig. 11. Monthly cooling energy for the whole building for dry and wet envelope, with k-value change corresponding to 29% initial moisture content.

the building monthly cooling energy, on the other hand, seems to be less affected by the k-value change of the insulation layer due to moisture content as can be depicted from Fig. 11. This limited change (around +2.0%) in building thermal and energy performance can be explained by the fact that the contribution of the roof (the most affected component of the building envelope by the k-value change of thermal insulation due to moisture content) to the overall building cooling energy is relatively smaller than the combined impact of other load components. 6. Conclusions The impact of thermal conductivity change due to moisture content on building thermal and energy performance under hot–humid climatic conditions is investigated using modeling and simulation and utilizing the experimental relationship between thermal conductivity and moisture content of fiberglass insulation material. From the modeling and simulation results of moisture performance of wall–roof systems the followings can be concluded: 1. The moisture behavior of the insulation layer is tangibly influenced by the moisture characteristics of other wall components. The presence of a high moisture resistance layer (i.e. red brick) to the interior of the insulation layer as compared to the low moisture resistive layer (i.e. pumice aggregate concrete block) has acted as a vapor retarder and resulted in a major shift in moisture accumulation throughout the year but in particular during the month of July and beyond. 2. The impact of the interior paint on moisture accumulation behavior decreases as the moisture resistance of the primary layer of the wall system increases. 3. Moisture accumulation within the various wall system components and the insulation layer to a greater extent depends on the temperature profile across the system components, which is influenced by the indoor temperature and the amount of solar radiation received on the different wall orientations. However, variation in behavior is dependent on the time of year and the type of wall construction. 4. Moisture behavior of the roof system is influenced by the environmental factors such as air temperature but to a larger extent by solar radiation as it receives the highest amount of solar radiation throughout the year compared to any building envelope surface. 5. Roof moisture performance is dependent on thermal and moisture characteristics of the comprising components and more significantly on the arrangement of the insulation layer relative

I. Budaiwi, A. Abdou / Energy and Buildings 60 (2013) 388–399

to the roof membrane. As much as 500% increase in moisture content is obtained when no roof membrane is used and as much as 700% increase is obtained when roof membrane is placed below the insulation layer. From simulation results of thermal and energy performance of the modeled building the following conclusions can be made on the impact of k-value variation due to moisture content on building energy performance. 1. No noticeable change occurs in the walls and roof contribution to the monthly cooling load due to the change in insulation thermal conductivity. Consequently, no change is noticed in the building monthly cooling energy. This limited change in energy performance can be explained by the fact that the increase in wall and roof thermal conductivities for the wet conditions as predicted under the modeled climatic conditions is small. 2. When higher wetting level at extreme climatic and environmental conditions is assumed, the magnitude of change in k-value due to moisture content is likely to be more pronounced. However, the impact of k-value change due to moisture content on wall thermal performance continues to be limited, but is more noticeable for the roof especially during the summer months when as much as 8% change in the monthly cooling load occurs. 3. The overall building thermal and energy performance, on the other hand, is less affected by the k-value change of the insulation layer due to moisture content. Acknowledgements This work is part of a research project grant (IN080390) funded by King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. The funding and the supporting facilities provided by KFUPM are highly appreciated. References [1] A. Ahmed, Energy simulation for a typical house built with different types of masonry building material, The Arabian Journal for Science and Engineering 29 (2004) 113–126. [2] L.F. Cabeza, A. Castell, M. Medrano, I. Martorell, G. Pe’ rez, I. Ferna’ndez, Experimental study on the performance of insulation materials in Mediterranean construction, Energy and Buildings 42 (2010) 630–636. [3] A. Abdou, I. Budaiwi, Comparison of thermal conductivity measurements of building insulation materials under various operating temperatures, Journal of Building Physics 29 (2005) 171–184.

399

[4] I. Budaiwi, A. Abdou, M. Al-Homoud, Variation of thermal conductivity of insulation materials under different operating temperatures: impact on envelope-induced cooling load, Journal of Architectural Engineering 8 (2002) 125–132. [5] Z. Bo-Ming, S. Zhao, X. He, Experimental and theoretical studies of hightemperature thermal properties of fibrous insulation, Journal of Quantitative Spectroscopy and Radiative Transfer 109 (2008) 1309–1324. [6] P. Ruut, Moisture dynamics in building envelopes. PhD thesis, Report R-071, Department of Civil Engineering, Technical University of Denmark, 2003. [7] J. Fan, W. Xinghuo, Modeling heat and moisture transfer through fibrous insulation with phase change and mobile condensates, International Journal of Heat and Mass Transfer 45 (2002) 4045–4055. [8] J. Fan, X. Cheng, X. Wen, W. Sun, An improved model of heat and moisture transfer with phase change and mobile condensates in fibrous insulation and comparison with experimental results, International Journal of Heat and Mass Transfer 47 (2004) 2343–2352. [9] M.Y. Zheng, F.H. Kong, Z.W. Han, Simulations on heat and mass coupling transfer in exterior insulated envelope of new building, Journal of Harbin Institute of Technology 41 (2009) 118–122. [10] Y. Kondo, A. Hvamac, Wc.L.Y. Nagasa, T. Fujimoto, Y. Kikuchi, T. Tasaka, Experiments on influence of moisture on thermal performance change of insulations: Long term thermal performance of building insulation materials Part 2, Journal of Environmental Engineering (Transactions of AIJ English Abstract) 75 (2010) 261–269. [11] F. Björk, T. Enochsson, Properties of thermal insulation materials during extreme environment changes, Construction and Building Materials 23 (2009) 2189–2195. [12] D.J. Gawin, M. Koniorczyk, A. Wieckowska, E. Kossecka, Effect of moisture on hygrothermal and energy performance of a building with cellular concrete walls in climatic conditions of Poland, ASHRAE Transactions 110 (Part II) (2004) 795–803. [13] Lambda 2000 Series, Heat Flow Meter Thermal Conductivity Instrumentation, Operation Manual, Holometrix Inc., USA, 1997. [14] ASTM: C518-91. Standard Test Method for Steady-State Heat Flux Measurements and Thermal Transmission Properties by Means of Heat Flow Meter Apparatus, 1991. [15] ISO 8301:1991. Thermal Insulation – Determination of Steady-State Thermal Resistance and Related Properties – Heat Flow Meter Apparatus. [16] Fraunhofer IBP Software, WUFI, Introduction, www.wufi.de/index e.html, February, 2012. [17] hygIRC 1-D, www.nrc-cnrc.gc.ca/eng/projects/irc/hygirc.html, February, 2012. [18] J. Delgado, N. Ramos, E. Barreira, V. de Freitas, A critical review of hygrothermal models used in porous building materials, Journal of Porous Media 13 (2010) 221–234. [19] M. Joscak, W. Sonderegger, P. Niemz, A. Holm, M. Krus, T. Großkinsky, K. Lengsfeld, J. Grunewald, R. Plagge, Comparative measurements of heat and moisture transfer in different wood-based building elements, Bauphysik 33 (2011) 287–298. [20] D. Allinson, M. Hall, Hygrothermal analysis of a stabilized rammed earth test building in the UK, Energy and Buildings 42 (2010) 845–852. [21] F. Antretter, F. Sauer, T. Schopfer, A. Holm, Validation of a hygrothermal whole building simulation software, in: Proc. of Building Simulation 2011, 12th Conference of International Building Performance Simulation Association, Sydney, 14–16 November, 2011, pp. 1694–1701. [22] The ASHRAE Handbook Fundamentals (SI edition), 2009. [23] VisualDOE 3.1 Software: www.eley.com/gdt/index.htm, December, 2011.