Thermal characterization of insulating materials

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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Thermal characterization of insulating materials ⁎

Roberto Ricciua, Luigi A. Besalducha, Alessandra Galatiotob, , Giuseppina Ciullab a b

Department of Civil and Environmental Engineering and Architecture, University of Cagliari, Italy Dipartimento dell’Energia dell’Ingegneria dell’Informazione e dei Modelli Matematici, University of Palermo, Italy

A R T I C L E I N F O

A BS T RAC T

Keywords: Lightweight walls Specific heat capacity Thermal flux Climatic chamber

The strict energy saving standards are based on the declared values of the materials, i.e. U-value, thermal conductivity or thermal capacity. To this end, proper knowledge of the thermophysical properties of the wall components is needed, especially with regard to new lightweight technologies that are being used in building construction/refurbishment, under the dynamic conditions of the Mediterranean climate, where one of most important parameters of building materials is their heat capacity because of the influence of solar radiation energy. With this regard, the actual heat capacity value, obtained in laboratory tests, is typically quite different from the nominal one. So, this paper reviews several methods of calculating the heat capacities of materials and several worldwide applications, with the aim of providing an overview of the thermal behaviour of lightweight insulation materials and their implications for energy and indoor comfort. Finally, the authors propose a simple method able to evaluate the specific heat capacity of real scale building materials with a ~5% of uncertainty.

1. Introduction At present, the worldwide trend of primary energy demand for the supply of heat, light, and industrial and transportation power is continuously rising [1]. In this context, buildings account for 30– 40% of the total global primary energy use and 24% of the global generation of greenhouse gasses [2,3]. In EU countries, several energy goals have been achieved by virtue of policies enacted to strive to meet targets set for 2020 [4–6], and considerable attention has been paid to the energy refurbishment of existing buildings to address their primary energy demand, which, in Europe, amounts to approximately 40% of the total [7]. Existing building stocks are the most difficult to make energy efficient, as users are induced to make incorrect use of HVAC systems [8], artificial lighting systems and shading devices [9–12] that often are not provided with smart control devices [13–16]. In Italy, recent research studies [17–19] have classified the residential building stock into several categories according to age, material and typology criteria, and these studies have highlighted the poor building envelope performances of many buildings (typically built before 1960), which are either completely devoid of insulation systems or are very difficult to retrofit for energy-related concerns [20–22]. These findings emphasize the problem facing the scientific community with regard to the achievement of nZEB targets for existing buildings [23,24], which, although the particular criteria depend on primary conversion weighting factors (which differ from country to country)

⁎

[25], is becoming increasingly necessary for the achievement of overall targets [26]. In this context and specifically in refurbishment field, the wall insulation (i.e. thermal coat system) is a fundamental action able to improve energy performance of buildings, through a detailed knowledge of envelope thermal inertia, U-values, hydrophobic properties, building insulation levels and insulation material parameters [27,28]. That being said, where this kind of retrofit action occurs, commonly, architects and engineers base their energy calculations on the declared values, given by manufacturers, that differs from the real one, with particular reference to the specific heat capacity. In this context, the objectives of this work are: a) to review several scientific methods that have been developed and experimentally applied throughout the world to calculate the heat capacities of materials while overcoming inaccuracies arising from general procedures; b) to present scientific experiences in the testing of innovative and traditional insulation materials and finally, c) to propose a method of experimental analysis in a climatic chamber. The authors believe that this paper can aid researchers and skilled people involved in the thermal characterization of insulation materials, thereby contributing to the improvement of building energy performance. Indeed, the determination of specific heat values for such materials is not a simple task because they are generally characterized by high porosity, low conductivity, low density and low thermal capacity. So, in the following section, several suitable calculation methods are collected and described.

Corresponding author. E-mail addresses: [email protected] (R. Ricciu), [email protected] (L.A. Besalduch), [email protected] (A. Galatioto), [email protected] (G. Ciulla).

http://dx.doi.org/10.1016/j.rser.2017.06.057 Received 21 December 2016; Received in revised form 6 June 2017; Accepted 18 June 2017 1364-0321/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Ricciu, R., Renewable and Sustainable Energy Reviews (2017), http://dx.doi.org/10.1016/j.rser.2017.06.057

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ΔTis φisf φesf Δqes Δqis P DF Ts,i Tsa,e Q′ TCHCM Rwall Q cv

Nomenclature Φ λ c Ks Kr α q Φs Φh ms KF(T) ΔTes

heat flux [W] thermal conductivity coefficient [W/mK] specific heat capacity [J/kgK] heat transfer coefficient [W/m2K] heat transfer coefficient [W/m2K] thermal diffusivity [m2/s] heat flux density [W/m2] blank-corrected net heat flow rate [W] blank-corrected net heat flow rate [W] mass [g] calibration factor [-] temperature changing on the ext surface [°C]

als, and other material properties of interest for building applications. Furthermore, Derbal et al. [44] proposed a theoretical analysis of measured data that enables the thermal characterization of materials and as stated by the authors, the experimental apparatus is very light, cheap and easy to set up. Furthermore, the proposed method allows the simultaneous determination of the thermal conductivity and volumetric heat capacity of a given material. The experimental set-up is based on the unidirectional heat transfer assumption, as expressed in Eq. (4) [45,46]:

2. Specific heat of building materials: calculation methods The heating process of a material begins with a phase of nonstationary conduction and then proceeds to a stationary phase in which the material achieves a certain heat capacity [29]. As is well known, in recent years, it has become increasingly important to describe the microstructures of materials using geometrical and mathematical approaches [30,31]. In general, a steady thermal flow is defined as a thermal flow that occurs at a constant temperature difference, and as is well known, the relationships between the physical parameters of the thermal conduction process can be described according to Fourier's law [32–34] (Eq. (1)):

Φ = −λ A

ΔT Δx

δT δ 2T =α 2 δt δx

where Φ is the heat flux [W], λ is the thermal conductivity coefficient [W/mK], ΔT is the temperature gradient [K], and Δx is the material thickness [m]. Given this description, in addition to the thermal conductivity λ and the density ρ, the specific heat capacity c [J/kgK] is another major physical property that is necessary for calculating the transient thermal behaviour of materials and building components [35]. In the UNI 10351:2015 standard [36] and the UNI EN ISO 10456:2008 standard [37,38], λ [W/mK] and ρ [kg/m3] values for many materials are tabulated for use in calculations. However, for material assessments performed under dynamic conditions, the effective values of the properties c, ρ and λ must typically be calculated differently. For this purpose, several researchers have used Differential Thermal Analysis (DTA) [39]. In detail, DTA is based on a comparison between results obtained by applying an identical thermal cycle to a certain material of interest and a reference sample. Such an analysis requires an apparatus consisting of three major components: a sample holder, a controlled source of heat, and a device for measuring the heats of reaction [40]. It analyses the transferred differential heating curve (inside and outside of the sample) according to the following Eq. (2) and Eq. (3): (2)

dqr = Kr (Tw − Tr ) + σ (Ts − Tr ) + αr (To − Tr ) dt

(3)

(4)

where α [m2/s] is the thermal diffusivity. The numerical model is based on a matrix with the form given by Eq. (5):

(1)

dqs = Ks (Tw − Ts ) + σ (Tr − Ts ) + αs (To − Ts ) dt

temperature changing on the int surface [°C] interior-surface phase shift [rad] exterior-surface phase shift [rad] heat flux density changing on the ext surface [W/m2] heat flux density changing on the int surface [W/m2] period [s] decrement factor [-] internal surface temperature [°C] outdoor sol–air temperature [°C] integral of the measured heat flux [Ws/m2] Temperature-Change Hot Chamber Method [-] thermal resistance of the wall system [K m2/W] thermal energy [J] volumetric heat capacity [J/m3K]

fi, j ( p ) =

Tmeas (i , j ) − Tsim (i , j , p ) max(Tmeas ) − min(Tmeas )

(5)

where fi,j is the weighted difference between the simulated and measured temperatures in iteration i = 1, …, n and at the interface j = 1, 2, whereas p is the vector of the parameters to be defined (λ and ρ). Therefore, the objective function is defined as shown in Eq. (6):

F ( p) =

∑ ( fi,j ( p )). i, j

(6)

The reported results indicate that with regular temperature measurements, this procedure is particularly suitable for materials that exhibit good homogeneity, for which it yields a calculation accuracy of approximately 7%. Another method of interest relies on a Differential Scanning Calorimetry (DSC) procedure [47,48]. DSC is a well-known technique that allows the heat flow rate to a sample to be monitored while the sample's own temperature is controlled [49]. One of the most important advantages of this method is the elimination of the need for a separate calibration run using a sample material with a known heat capacity. Because of the temperature and heat flux calibration requirements for static methods, such a separate run is usually necessary to properly establish the temperature calibration, whereas in the case of DSC, the calibration can be approximate. In this context, Ramakumar et al. [50] described a complete hybrid procedure for calculating the specific heat capacity c [J/kgK] according to Eq. (7), based on the assumption that the calibration factor KF(T) remains constant with time and temperature.

where dq/dt denotes the rate at which heat is received by the reference material (subscript r) or the sample material (subscript s), whereas Ks and Kr are the corresponding heat transfer coefficients between the materials and the furnace wall. DTA has been used by several authors [41–43] to investigate energy storage performances, the thermal properties of phase-change materi-

cs =

KΦ (T )(Φs − Φb ) βms

(7)

where (Φs-Φb) represents the blank-corrected net heat flow rate for the sample [W], β = ΔT/Δt is the heating rate, ms is the mass (g) of the sample, and KF(T) is the calibration factor. 2

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the authors studied the influence of thermal inertia on the dynamic performance of building envelopes using a double-box apparatus with a climatic chamber, in which a thermal stimulus was applied and the results were monitored using thermocouple flow metres. The obtained results demonstrate the need to normalize data with respect to the trend in the indoor air temperature induced by the solar radiation load, as described by Eq. (11).

Using an alternative approach, Cobîrzan et al. [51] applied a photothermal analysis technique to analyse the mineralogical content, thermo-technical and physico-mechanical characteristics of three types of masonry. In detail, the authors performed thermal effusivity measurements by means of photopyroelectric calorimetry and measured the thermal diffusivity via infrared lock-in thermography. Using this combined analysis, the authors demonstrated that when the porosity of a material is higher, it tends to have a lower thermal conductivity. In the same way, Al-Ajlan [52] affirmed that the thermal conductivity of a given material depends on its atomic and molecular structure, porosity, anisotropy, structural faults and defects. Hence, the specific heat of a material is determined by its composition. The same method has been applied by Danielski and Fröling [53] under nonsteady-state heat flow conditions, in which case a heat flux meter (HFM) was also used on an element of the complete building envelope. In another study, Leon [54] et al. investigated the thermal properties of three main plans using nine pine wood species by applying photoacoustic and photothermal techniques. The results showed that these techniques are the most suitable methods for the thermal characterization of wood panels in general. Abdelrahman et al. [55] measured the thermal conductivities of several common building materials using a guarded hot plate. The authors highlighted the difference between the measured values and those reported in the literature due to the effects of the mean temperature, the material density and the level of moisture content. As affirmed by Faye et al. [56], construction materials are heterogeneous, and their thermophysical properties are often poorly known and assessed. These authors proposed a procedure based on several experimental measurements of the effective heat capacity of a hollow clay brick wall, starting from an electrical analogy and using a π quadrupole consisting of three impedances denoted by Zin (input), Ztr (transfer) and Zout (output), as expressed in the following Eq. (8):

DF =

AT =

ρc

(ΔTes + ΔTis⋅ cos ϕisf )(Δqes⋅ sin ϕesf − Δqis⋅ sin ϕisf ) − ΔTis⋅ sin ϕist ⋅(Δqes⋅ cos ϕesf − Δqis⋅ sin ϕisf ) (9)

HCeff =

Δq 2 es − 2Δqes Δqis cos(ϕesf − ϕisf ) + Δq 2is (ΔTes + ΔTis⋅ cos ϕisf )(Δqes⋅ sin ϕesf − Δqis⋅ sin ϕisf ) − ΔTis⋅ sin ϕist

⋅

(12)

⎛ δ 2T δT δ 2T ⎞ = λ⎜ 2 + 2 ⎟ δt δy ⎠ ⎝ δx

(13)

where ρ is the density of the material, c is the specific heat capacity, λ is the thermal conductivity, T is the temperature, and t, x and y denote the time and the thickness and width directions with respect to the wall, respectively. Among the many results that have been reported, it should be noted that when the block thermal conductivity is constant, increasing the thermal capacity of the material provides a useful means of increasing both the decrement factor and the time lag of the wall. Generally, all previous presented scientific methods have the same aim: to quantify specific heat capacity of materials as precisely as possible. So, discussed models use different approaches, anyway, it is possible to affirm that does not exist a more common one among them, but the method that is able to give the lowest uncertainty value is the best one. At this stage, the authors would like to provide the reader an overview of the topic under discussion by presenting, in the following section, several worldwide experiences with regard to the application of traditional and innovative insulation materials, their performance potential, their energy-saving implications, and related comfort issues.

X

Δq 2 es − 2Δqes Δqis cos(ϕesf − ϕisf ) + Δq 2is

DF Ta, i, max − Ta, i, min

where Ta,i is the indoor air temperature [°C]. Finally, Zhang et al. [62] proposed an experimental method called the Temperature-Change Hot Chamber Method (TCHCM), in which the difference between experimental and calculated results for a hollow brick element sample is analysed using the thermal resistance, the decrement factor and the time lag as evaluation indices. The authors performed an in-depth analysis of the influence on the thermal performance of a hollow block wall and proposed suitable optimization measures. Using the finite difference method (FDM), the two-dimensional energy equation can be discretized according to several assumptions made to simplify the heat transfer model, as follows: the materials are considered to be thermally homogeneous, their thermal properties are considered to remain unchanged during the heat transfer phases, an equivalent thermal conductivity is applied for the internal air layers, and the net heat flow is considered to be equal to zero in the vertical direction (Eq. (13)).

where: R = Re(Z) is the resistance of the impedance and X = Im(Z) is the reactance. The authors performed a 5-day measurement campaign (12 h per day) during which they monitored the temperatures and heat fluxes on both the cold and hot surfaces. Finally, as affirmed by the authors, the imaginary part of Eq. (8), as described in Eq. (9), could be treated as the basis of the full procedure for calculating the “effective heat capacity” [J/m2K] (Eq. (9) and Eq. (10)).

=

(11)

where DF denotes the decrement factor, Ts,i is the internal surface temperature [°C], and Tsa,e is the outdoor sol–air temperature [°C]. Furthermore, the authors normalized the differences among the temperature trends observed during the tests using the amplitude transmission coefficient (AT) (Eq. (12)).

(8)

Z = R + j⋅X

Ts, i, max − Ts, i, min Tsa, e, max − Tsa, e, min

P 2π

⋅(Δqes⋅ cos ϕesf − Δqis⋅ sin ϕisf ) (10) where ΔTes is the change in the temperature on the exterior surface [°C], ΔTis is the change in the temperature on the interior surface [°C], φisf is the interior-surface phase shift [rad], φesf is the exterior-surface phase shift [rad], Δqes is the change in the heat flux density on the exterior surface [W/m2], Δqis is the change in the heat flux density on the interior surface [W/m2], and P is the period [s]. Similarly, Ferrari et al. [57] emphasized the need to overcome the inaccuracies in U-value calculations that arise when the influence of the heat capacity is neglected in the characterization of the thermal performance of building walls. Based on previous findings [58–61],

3. Building envelope insulation In this review section, several worldwide conducted experiences on test specimens are presented. In particular, the review is focused on thermal characterization of wall insulation or new materials, mainly performed in climatic chamber. Thermal insulation is a material or combination of materials that, when properly applied, retards the rate of heat flow via conduction, 3

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convection, and radiation [63]. In the field of building design, re-design and refurbishment, properly chosen insulation materials plays a keyrole in increasing the building energy performance and the indoor thermal comfort [64]. Indeed, in all climates, wall and roof insulation is strongly recommended to guarantee a more comfortable space and better energy performance [65,66]. To this end, a literature review shows that various thermal insulation materials and technical solutions with different purposes have been proposed to allow the problem of building refurbishment to be correctly addressed [67–70]. In greater detail, the most common practices involve the internal/external application of various plasters with high thermal insulation properties, whereas other approaches focus on the application of insulating materials to walls. Bianco et al. [71] tested two thermal plaster samples: A and B. The sample A has a higher density than sample B. The main parameters of the samples are: thickness 10 cm; size: 60×60 cm; ΔT: 20 °C, while λeq (W/mK) is calculated according to Eq. (14).

λeq =

s⋅q Δts

proposed by Garas and Allam [83], who demonstrated that this approach is especially suitable for internal applications (i.e., in historical buildings) by virtue of the high isolative value of straw bales. In another study, Guizzardi et al. [84] tested a masonry wall specimen exposed to controlled heavy weathering conditions. The results elucidated the effects of interfaces between material layers. De Berardinis [85] proposed another interesting field application of an insulation system in a study conducted after the 2009 earthquake in the Abruzzo region of Italy, where it was necessary to completely reconstruct many urban centres while carefully preserving their historical heritage. To this end, the authors analysed and classified several types of wall masonry, proposed different types of insulation on a “case-by-case” basis, and evaluated their corresponding energy implications. The results indicated that in some cases, an energy savings of 50% could be achieved. In this regard, it must be emphasized that climate conditions play a key role in determining building envelope performances and economic costs [86]. Therefore, insulation materials and techniques must be properly chosen for the intended building conditions, climate and use. At present, various lightweight materials are being increasingly studied and applied in building envelopes [87,88]. The advantages of such materials are that they enable prompt construction while exhibiting high quality, good thermal properties, good acoustic performance and high durability; consequently, they are particularly useful for application in temporary housing [89]. In addition, they can help to solve various construction-related problems and to reduce the production of waste during the erection of buildings, although their performance in some climates, such as the Mediterranean climate, is far from being completely established [90–92]. Indeed, their thermal behaviour in maintaining indoor thermal comfort [93–95] predominantly depends on three parameters: temperature, relative humidity and air speed. Therefore, under stationary conditions, the most critical property is the thermal resistance [96], whereas under dynamic conditions, the most critical properties are c, ρ and λ. In the Mediterranean climate, a more accurate dynamic analysis is required because of the significant contribution from the solar radiation load during both the summer and winter seasons [97–99], which gives rise to very different conditions compared to those to which building components are typically subjected in performance simulations [100]. In a related study, Nicolajsen [101] compared the performance of a cellulose insulation material with that of a stone wool material under actual Danish climate conditions. The test specimen was composed of two different facade elements, one consisting of 285 mm of cellulose and one consisting of 285 mm of stone wool. The authors found that the cellulose insulation material was particularly well suited to the Danish climate in terms of its thermal performance, which was significantly lower than that of the stone wool material, by virtue of the fact that it trapped a lower humidity content behind the wind barrier. Awad et al. [102] evaluated the thermal and structural performances of several potential energy-efficient wall systems for mid-rise wood-frame buildings. By means of field measurements, the authors compared several traditional stick-frame construction practices, with the aim of assessing the corresponding long-term thermal performances under actual outdoor climate conditions. Furthermore, they monitored indoor parameters to validate the findings obtained in laboratory tests and to characterize the temperature and hygrothermal behaviours of the samples. In particular, they calculated the thermal resistance (RSI) values of the panels according to Eq. (16).

(14)

where: λeq [W/mK] is the equivalent conductivity, s [m] is the thickness, q [W/m2] is the heat flux density and Δts [K] is the difference of temperature. More in detail, this kind of thermal plaster is produced by adding materials derived from corn production waste to a vegetal aggregate and measured a resultant reduction in the heat flux across the wall of approximately 20–40%. Häkkinen [72] explained several new solutions for the sustainable refurbishment of external walls developed within the framework of the European SUSREF project [73]. The author analysed European buildings built between 1940 and the 1970s and found that high-rise buildings (with eight or more storeys) represented 10% of the assessed buildings. Specifically, the proposed approach includes the optimization of material and structural choices, the comparison of solutions, feasibility investigation, risk avoidance, the assessment of long-term impacts, and the development of systems to support refurbishment targets. In another study, Jelle [74] compared several insulation materials based on the following Eq. (15).

λtot = λsolid + λgas + λrad + λconv + λcoupling + λleak

(15)

where λtot is the total overall thermal conductivity, λsolid is the solidstate thermal conductivity, λgas is the gas thermal conductivity, λrad is the radiation thermal conductivity, λconv is the convection thermal conductivity, λcoupling is a thermal conductivity term accounting for second-order effects among the various thermal conductivities, and λleak is the leakage thermal conductivity. The author assessed various state-of-the-art traditional insulation materials and collected their typical conductivity values as follows: mineral wool, 30–40 mW/mK; EPS, 30–40 mW/mK; XPS, 30– 40 mW/mK; cellulose, 40–50 mW/mK; cork, 40–50 mW/mK; and polyurethane, 20–30 mW/mK. Furthermore, in the same work, several new insulation materials were described, i.e., vacuum insulation panels [75,76] (3–4 mW/mK), gas-filled panels [77,78] (approximately 40 mW/mK for a prototype), and aerogels [79,80] (13–14 mW/mK). Also of interest are the results achieved by Johansson et al. [81,82], who tested the performance of vacuum insulation panels (VIPs) in a climatic chamber by measuring results for two configurations: walls with and without interior VIPs. The authors found that interior insulation significantly reduced the surface wall temperature, whereas the RH increased to approximately the 60–100% range, and some condensation occurred. However, the authors confirmed that the use of VIPs of proper thickness surrounding thermal break areas could reduce the increase in RH, thereby preserving wall quality and contributing to energy conservation. Among the various insulation practices and solutions that have been proposed, another notable example is the straw application

Rwall =

100% %Areastud / Rstud + %Areacavity / Rcavity

(16)

where Rwall is the thermal resistance of the wall system [Km2/W], % Areastud represents the area percentage of studs in the wall system, % 4

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surface temperature in the indoor chamber [K]; θext, the wall surface temperature in the outdoor chamber [K]; qint, the thermal flux at the wall surface in the indoor chamber [W/m2]; qext, the thermal flux at the wall surface in the outdoor chamber [W/m2]; RHint, the relative humidity in the indoor chamber [%]; RHext, the relative humidity in the outdoor chamber [%]; vint, the air velocity in the indoor chamber [m/s]; and vext, the air velocity in the outdoor chamber [m/s]. To minimize the effects of sideways heat dispersion in the measurements, the specimen was inserted into an extruded polystyrene (XPS) frame. The instrumentation scheme is shown in Fig. 2; the probes were placed far from the edges to permit the assumption of a monodimensional heat flux. For verification, the differences between the values measured by different probes were checked and confirmed to be lower than their nominal precision. The applied method required the measurement of the surface temperatures and of the heat fluxes through the specimen using the heat-flux measurement method described in [105].

Areacavity represents the area percentage of cavities in the wall system, Rstud denotes the thermal resistance at a stud, and Rcavity denotes the thermal resistance at a cavity. By analysing the results thus obtained, the authors demonstrated the need for further study of the structural and energy behaviours of contemporary innovative materials. To this end, a more in-depth study involving detailed calculations of hourly heat flows and thermal inertia could be very useful for historical building refurbishment as well as for the assessment and prediction of seasonal thermal loads to enable a reduction in building energy consumption [103]. Based on the previous reviewed topics, an experimental procedure involving the application of several of the discussed methods is presented in the following section. 4. Experimental analysis of the specific heat value of a test specimen This section discusses the thermal testing of an extremely porous material characterized by low conductivity, low density and a low thermal capacity, such as a cellulose fibre panel. The objective is to provide a facile method of characterizing the heat capacity of such a building material using a full-scale sample. For the insulation of buildings, the use of blown-in cellulose material is particularly useful because it can eliminate the need for moulds and permits the regulation of the hygrometric comfort inside the building by reducing peaks in air humidity. This dry construction method permits rapid construction and the maximization of thermal properties for a wide range of building projects. In Table 1, the main parameters describing the tested sample are reported. This study was performed under the following assumptions: the materials composing the wall are unknown; only the geometry is known. For this study, the transient method applied in [57] was adopted, in which a heat flow meter apparatus is used in the climatic chamber to measure the λ value of the tested material in order to determine the cvalue. Fig. 1 depicts the climatic simulation chamber used to test the full-scale wall samples, with indoor and outdoor climatic conditions imposed on the walls in accordance with [104–107]. The apparatus consists of two chambers that allow full control of the temperature, relative humidity and air velocity parameters and a frame to hold the specimen. A thermal flow forms across the two wall faces because of the difference in the environmental air temperature between the two sections of the climatic chamber.

4.2. Experimental results 4.2.1. Steady-state experimental analysis A test to determine the steady-state thermal conductivity was conducted under winter operating conditions by maintaining a mean surface temperature difference between the indoor and outdoor chambers of approximately 20 °C (see Fig. 3). Furthermore, the following environmental parameters in the indoor and outdoor chambers were set as follows: a) air temperature was set to 2 °C in the indoor chamber and 22 °C in the outdoor chamber, b) relative humidity was set to 40% in both chambers, and c) air velocity was set to 0.1 m/s in the indoor chamber and 1.0 m/s in the outdoor chamber. As the surface wall temperature difference became constant (after ~20 h), the heat flux density converged to a value of ~3.5 W/m2. The thermal conductivity λ was determined following [105] (see Fig. 4), using the progressive mean method. In Fig. 4, the trend of the obtained conductance is shown as an instantaneous indirect measure of the flow variation and the temperature difference between the two rooms. The assumed average value is approximately 0.145 W/m2K. This value was used to determine the thermal conductivity of the cellulose (0.054 W/mK), and the result was similar to the value of 0.050 W/mK found in [100], where the nominal value for the OSB (0.130 W/mK) was also considered. 4.2.2. Experimental dynamic analysis A test to determine the thermal lag and the attenuation factor was conducted by simulating several sinusoidal waves while maintaining a mean internal and external surface temperature of 25 °C and a wave amplitude of 10 °C on the external surface. As shown in Fig. 5, the time lag between the wave peaks was 5.33 h, but the attenuation factor was particularly high (~95%).

4.1. Applied method The test wall was instrumented with resistance temperature detector (RTD)-type PT1000 1/3 DIN sensors for the surface temperature measurements. The indoor air temperature was measured using negative temperature coefficient (NTC) thermistors. Heat-flux sensors were fixed to the wall to measure the surface temperature and heat flux. To obtain sufficient data, fourteen RTD sensors, four heat-flux sensors (including two thermopile temperature sensors), and two relative humidity probes were fixed to each facade of the wall. A sample measurement rate of 10 Hz was chosen. The output data on the surface temperatures and heat fluxes were collected by a National Instruments data acquisition system (DAQ), whereas the air temperatures in the two chambers were recorded by TGU2 data loggers. Subsequently, the data were transferred and processed. The HFM consisted of a cylindrical thermopile comprising a composite ceramic-plastic material with a thermal conductivity of 6.25×10−3 W/mK. The contact surface had an 80 mm radius and a thickness of 5.50 mm. The main metrological characteristics were as follows: span (measurement field), −2000–2000 W/m2; resolution, 0.01 W/m2; bias, ± 5%. The most important acquired data were the following: θint, the wall

5. Determination of the heat capacity of the specimen Consider the general Eq. (17) [108]:

Aq (ti ) dt = M c (Θi ) dΘ

(17)

where q is the heat flux density [W/m2] through the area A [m2], t is Table 1 Parameters of the tested sample. (OSB) Oriented Strand Board panel density Specific heat capacity conductivity Conductivity OSB Specific heat capacity OSB density

5

2240 × 1250x 395 mm 60 kg/m3 2544 J/kgK 0.038 W/mK 0.13 W/mK 1700 J/kgK 600 kg/m3.

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0.16

Conductance [ W/m 2 K ]

0.15 0.14 0.13 0.12 0.11 Fig. 1. Climatic chamber, vertical cross section. (A) Indoor chamber. (C) Outdoor chamber. The specimen is contained in a frame (B) between the two chambers. (1) is the compartment for the electrical control system, which contains the heat, cold and humidity generators. (2) is the compartment for the air handling system. The two chambers, A and C, move on rails.

0.1 0

10

20

30 40 Time [Hour]

50

60

70

Fig. 4. Measured conductance.

2

Temperature. [°C] , Thermal Flux [W/m ]

35 30 25 20 15

5 0 -5

0

10

20

30 40 Time [hour]

50

60

70

Fig. 5. Surface wall temperatures in the indoor (red line) and outdoor (blue line) chambers and thermal flux (black line). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 2. Positions of the heat flux sensors and the RTDs on the indoor facade.

A

25 2

Temperature. [°C] , Thermal Flux [W/m ]

Int. Wall Surface Temp. Ext. Wall Surface Temp. Thermal Flux

10

∫t

t

q (ti ) dt = Q′ = 0

M A

∫T

Tt

c (Θi ) dΘ

0

(18)

where Q′ [Ws/m ] is the integral of the measured specific heat flux with respect to time. Under the assumption that the heat capacity is independent of the temperature [108]), Eq. (17) can be written as follows (Eq. (19)): 2

20

Int. Wall Surface Temp. Ext. Wall Surface Temp. Thermal Flux

15

Q′ = 10

Θt

∫Θ

dΘ =

0

M M c⋅(Θt − Θ0 ) = c⋅ΔΘ A A

(19)

Therefore, the heat capacity can be defined as shown in Eq. (20):

c=

5

0

M c A

A⋅Q M . ΔΘ

(20)

Solving the integral in Eq. (19) using the finite-difference method yields the following Eq. (21) [109]: 0

20

40

60 Time [hour]

80

100

120

t

c=

Fig. 3. Surface wall temperatures in the indoor (red line) and outdoor (blue line) chambers and the thermal flux (black line). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

A ∑m = t 0+1 qmi⋅Δt MΔΘ

(21)

Where:

qm =

the time [s], M is the mass of the test wall [kg], c is the specific heat capacity [J/kgK], and Θ is the surface temperature of the test wall [K]. If the initial temperature is Θ0(at t = t0, when the specimen is in the equilibrium state), then at time t, it is possible to write the following (18):

qi + qi−1 2

(22)

and Δt [s] is the inverse of the acquisition frequency [Hz]. To allow the evaporation of the residual humidity and the formation of an isotropic thermal distribution inside the specimen, the two chambers were maintained for 30 h under the following environmental 6

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been presented, with particular attention to the related implications regarding energy and indoor thermal comfort. Finally, a procedure for calculating the conductivity, specific heat, time lag and attenuation factor for a lightweight material has been proposed, and related experimental results obtained from experimental measurements performed using two climatic chambers have been discussed. In particular, the proposed method is applicable to any wall layout with an uncertainty of ~5%. However, several issues that must be solved have been highlighted, e.g., the need to improve the density of cellulose in order to increase thermal lag.

Temperature [ °C ]

Thermal Flux [ W/m 2 ]

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40 20 0 -20

Ind.Outdoor Wall Surface Thermal Flux Relative Humidity

-40 -60 0

20

40 60 Time [Hour]

80

References [1] Available at: 〈http://www.bp.com/en/global/corporate/sustainability/the-energychallenge-and-climate-change/the-climate-challenge.html〉. [Accessed on 6 December 2016]. [2] Dodoo A, Gustavsson L, Sathre R. Building energy-efficiency standards in a lifecycle primary energy perspective. Energy Build 2011;43:1589–97. [3] IEA, Towards net zero energy solar buildings, in: ECBCS/SHC Project Factsheet, Energy Conservation in Buildings and Community Systems Programme, United Kingdom, 2011, p. 1–2. [4] Decision n. 406/2009/EC of the European Parliament and of the Council of 23April 2009 on the effort of Member States to reduce their greenhouse gas emissions to meet the community’s greenhouse gas emission reduction commitments up to 2020. Official J. Eur. Union L 140/136 (5 June; 2009. [5] Directive. 2009/28/EC of the European Parliament and of the Council of 23April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and2003/30/EC. Official J. Eur. Union L 140/16 (5 June; 2009. [6] Directive 2012/27/EU of the European Parliament and of the Council of 25October 2012 on energy efficiency, amending Directives 2009/125/EC and2010/30/EU and repealing Directives 2004/8/EC and 2006/32/EC. Official J. Eur. Union L 315/1 (14 November 2012). [7] Statistical BP. Review of World Energy. [accessed on Dec 06th 2016]; 2016. [8] Deuble MP, de Dear RJ. Green occupants for green buildings: the missing link?. Build Environ 2012;56:21–7. [9] Galatioto A, Beccali M. Aspects and issues of daylighting assessment: a review study. Renew Sustain Energy Rev 2016;66:852–60. [10] Galatioto A, Beccali M. Assessment of the entropy of spatial and time distributions of rooms daylighting: a possible tool for a sustainable design. J Sustain Dev Energy, Water Environ Syst 2015;3(4):425–35. [11] Aries MBC, Newsham GR. Effect of daylight saving time on lighting energy use: a literature review. Energy Policy 2008;36(6):1858–66. [12] Hee WJ, Alghoul MA, Bakhtyar B,O, mKalthum E, Shameri MA, Alrubaih MS, Sopian K. The role of window glazing on daylighting and energy saving in buildings. Renew Sustain Energy Rev 2015;42:323–43. [13] Osello A, Acquaviva A, Aghemo C, Blaso L, Dalmasso D, Erba D, Fracastoro G, Gondre D, Jahn M, Macii E, Patti E, Pellegrino A, Piumatti P, Pramudianto F, Savoyat J, Spirito M, Tomasi R, Virgone J. energy saving in existing buildings by an intelligent use of interoperable ICTs. energy efficiency 2013;6(4):707–23. [14] Aghemo C, Virgone J, Fracastoro GV, Pellegrino A, Blaso L, Savoyat J, Johannes K. Management and monitoring of public buildings through ICT based systems: control rules for energy saving with lighting and HVAC services. Front Archit Res 2013;2(2):147–61. [15] Beccali M, Bonomolo M, Galatioto A, Ippolito MG, Zizzo G. A laboratory setup for the evaluation of the effects of BACS and TBM systems on lighting. In: Proceedings of the International Conference on Renewable Energy Research and Applications, ICRERA; 2015. [16] Ippolito MG, Riva Sanseverino E, Zizzo G. Impact of building automation control systems and technical building management systems on the energy performance class of residential buildings: an Italian case study. Energy Build 2014;69:33–40. [17] Available at: 〈http://episcope.eu/index.php?Id=97〉 [accessed on Dec 06th, 2016]. [18] Ballarini I, Corgnati SP, Corrado V. Use of reference buildings to assess the energy saving potentials of the residential building stock: the experience of TABULA project. Energy Policy 2014;68:273–84. [19] Available at: 〈http://webtool.building-typology.eu/〉. [accessed on Dec 06, 2016]. [20] Ciulla G, Galatioto A, Ricciu R. Energy and economic analysis and feasibility of retrofit actions in Italian residential historical buildings. Energy Build 2016;128:649–59. [21] Galatioto A, Ciulla G, Ricciu R An overview of energy retrofit actions feasibility on Italian historical buildings. Energy DOI: http://dx.doi.org/10.1016/j.energy. 2016.12.103. In press. [22] Pagliaro F, Cellucci L, Burattini C, Bisegna F, Gugliermetti F, de Lieto Vollaro A, Salata F, Golasi I. A methodological comparison between energy and environmental performance evaluation. Sustainability 2015;7(8):10324–42. [23] Ardente F, Beccali M, Cellura M, Mistretta M. Energy and environmental benefits in public buildings as a result of retrofit actions. Renew Sustain Energy Rev 2011;15:460–70. [24] Kurnitski J, Saari A, Kalamees T, Vuolle M, Niemelä J, Tark T. Cost optimal and nearly zero (nZEB) energy performance calculations for residential buildings with REHVA definition for nZEB national implementation. Energy Build 2011;43:3279–88.

100

Fig. 6. Surface wall temperatures in the indoor and outdoor chambers (red line), the thermal flux (black line) and the relative humidity (green line). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

conditions: air temperature, ~40 °C; relative humidity, ~22%; air velocity, 1.0 m/s. Once the specimen reached thermal equilibrium (the heat flux was approximately equal to zero, meaning that the variation among the data points was of the same order of magnitude as the uncertainty of the measuring instruments), the chambers were adjusted to the following environmental conditions: air temperature, ~25 °C; relative humidity: ~50% (to maintain the same vapour pressure between the two temperatures, 22 → 50 °C); air velocity, 1 m/s. Thus, as the air temperature of both chambers was adjusted from 40 °C to 25 °C, the wall transferred some of its accumulated heat to the air. In Fig. 6, it is apparent that none of the heat was used in condensing water contributed by the relative humidity conditions (i.e., latent heat of condensation) because the humidity remained approximately constant, far from the limit of RH = 100%. By applying Eq. (21), the average c-value was found to be 1387 J/ kgK. Furthermore, by applying the uncertainty propagation method described in [110] to Eq. (18), a final c-value result of 1387 ± 69 J/ kgK was obtained. Notably, because of the inhomogeneous composition of the building materials, the real mass of a wall is not always precisely known; therefore, an appropriate parameter to use is the volumetric heat capacity (Eq. (23)):

cv =

Q V ⋅ΔT

(23)

Thus, in the considered case, the average value of cv is found to be 1720 J/m3K, and by applying the uncertainty propagation method [111], a final result of as cv = 1720 ± 86 J/m3K is obtained. Therefore, it is possible to confirm that lightweight components, which generally have a very high thermal resistance, are very useful during the winter (when conditions are closer to a theoretical steady-state regime), whereas it is more difficult to determine their summer behaviour under the transient effect of the sun. 6. Conclusion In this paper, a broad overview of the methods used to calculate the specific heats of building materials, effective heat capacities and general thermal flux trends across building materials has been provided. Indeed, deep knowledge of the stationary and dynamic thermal properties and behaviours of building envelopes is fundamental to properly choice i.e. insulation materials and generally to reach good building energy performances. Furthermore, a collection of experiences from around the world with regard to the application of innovative insulation materials has 7

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