Straw bale based constructions: Measurement of effective thermal transport properties

Construction and Building Materials 198 (2019) 182–194

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Straw bale based constructions: Measurement of effective thermal transport properties Karthik A. Sabapathy, Sateesh Gedupudi ⇑ Heat Transfer and Thermal Power Lab, Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai, India

h i g h l i g h t s
Thermal conductivity and thermal diffusivity of straw bale samples have been measured.
Parameters considered are the temperature, packing density and moisture content of the sample.
Parallel, perpendicular and random orientations of the fiber have been studied.
Multiple variable correlations have been proposed for the thermal transport properties.

a r t i c l e

i n f o

Article history: Received 14 August 2018 Received in revised form 15 November 2018 Accepted 26 November 2018

Keywords: Straw bale based construction Energy efficiency Sustainability Thermal transport properties Transient thermal analysis

a b s t r a c t The use of eco-friendly thermal insulations in the building envelope is one of the passive and also sustainable means of achieving indoor thermal comfort. There are possibilities for significant improvements in energy efficiency over the life of a building with the prospect of reduced use of energy intensive spaceconditioning technologies. Straw, an agricultural residue, with potential for utilization as an insulation material, is the focus of the current work. Reliable transient analysis of straw based construction requires knowledge of its thermal transport properties – effective thermal conductivity and thermal diffusivity. Variability in thermal conductivity owing to several factors and lack of thermal diffusivity values are the main takeaways from the comprehensive literature review undertaken and therefore, the current work attempts to address these issues. The measurements of these thermal transport properties of rice straw bale sample are carried out using transient plane source technique. The ranges of the influencing parameters considered are: temperature from 25 °C to 45 °C, packing density from around 50–90 kg m3 for dry samples as well as samples conditioned at 40%, 60% and 80% RH. The experiments are performed for three different orientations with respect to heat flow: parallel, random and perpendicular. The effective thermal conductivity values obtained in the case of perpendicular/random orientation are approximately 1.7 times lower compared to parallel case. A significantly greater increase, as much as 130% and 60%, in thermal conductivity is found in parallel oriented case than perpendicular/random cases with increase in relative humidity and density, respectively. The thermal diffusivity values also show significant variation only in the parallel case. Correlations are proposed for both thermal conductivity and thermal diffusivity for all orientations. Ó 2018 Published by Elsevier Ltd.

1. Introduction On the path to the future of a sustainable world, humanity faces challenges on various fronts that include technological, economic, political and social. Building science is one of many fields in which researchers are striving to overcome technological obstacles. The contribution of construction and usage of buildings to greenhouse gas emissions is well-documented. ⇑ Corresponding author. E-mail address: [email protected] (S. Gedupudi). https://doi.org/10.1016/j.conbuildmat.2018.11.256 0950-0618/Ó 2018 Published by Elsevier Ltd.

If we were to propose a Maslow’s hierarchy of needs for a dwelling, we would have protection, security and privacy at the base and aesthetics at the top with comfort in between. It is high time that sustainability be inserted into this pyramid of needs. As to its position in the pyramid, sustainability should be placed beside comfort – not above or below it. The reason being that a green but uncomfortable home would drive its residents to seek and implement active and energy intensive means of achieving comfort thus partially or fully defeating the purpose of a home built with sustainable materials. With the passive techniques gaining attention as alternatives to active means of space conditioning, several

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Nomenclature F L T Ti W c k kexp kpred q t t0 t i ; t iþi0 t max x

function representing thermal conductivity or thermal diffusivity thickness of sample (m) temperature of the sample (°C) initial temperature of the sample (°C) side length of sample (m) specific heat (J kg1 K1) thermal conductivity (W m1 K1) experimentally measured value of thermal conductivity (W m1 K1) thermal conductivity value obtained from correlation (W m1 K1) heat flux (W m1 K1) time of measurement (s) start time of the window during which the temperature data obtained is used in curve fit (s) end times of the windows during which the temperature data obtained is used in curve fit (s) maximum duration of the experiment (s) distance between the heat source and the point of temperature measurement (position of temperature sensor) (m)

Greek symbols a thermal diffusivity (W m1 K1)

methods have been developed and continue to be researched [1]. Here we focus on one such method: thermal insulations made from sustainable construction materials as part of the building envelope. Eco-friendly construction materials especially when manufactured from locally available raw materials, have lesser impact on the environment over their entire life cycle when compared to conventional construction material like concrete and mortar [2]. Utilization of sustainable materials, when implemented properly, can go hand in hand with energy efficiency in buildings. In particular, the use of agricultural residue based non-conventional construction materials such as reeds, bagasse, etc. has been reviewed by Asdrubali et al.[3]. Straw – one of the agricultural residues derived during the harvest of cereal crops – is the focus of the current study. The concept of straw bale construction and its various aspects was the subject of discussion in the chapter authored by Walker et al. [4]. In India, large swathes of paddy straw is burnt in open grounds causing widespread air pollution of toxic levels. The issue of stubble burning is described in detail by P. Kumar et al.[5] in which the authors, based on previous studies, note that around two-thirds to three-fourths of paddy residue are burnt. A spectroradiometric image [6] captured by NASA’s Aqua satellite on the 12th November 2013 showed locations of active burning of paddy stubble in the state of Punjab in Northern India. The importance of need for alternative applications of the straw cannot be understated since it could potentially prove to be doubly beneficial – curbing pollution owing to the burning of straw and utilizing an eco-friendly material. The fact that straw can be thermally insulating makes it a worthwhile effort to investigate the use of straw as a construction material further. Straw, processed and fabricated in the form of boards or panels, can be used as the primary construction material. Buildings constructed using straw and similar materials around the world mentioned by Youngquist et al. [7] stand as examples. Moreover, retrofitting existing conventional buildings with straw insulation boards is another option worth exploring. Along with insulating ability (decided by the thermal

aexp amax apred

r
r r
r;a r
r;k q rr;a

rr;k Fo

experimentally measured value of thermal diffusivity (m2 s1) maximum thermal diffusivity (m2 s1) thermal diffusivity value obtained from correlation (m2 s1) overall mean of repeatability standard deviations mean of repeatability standard deviations of thermal diffusivity measurements mean of repeatability standard deviations of thermal conductivity measurements density (kg m3) repeatability standard deviation of thermal diffusivity measurement repeatability standard deviation of thermal conductivity measurement Fourier number

Abbreviations EMC Equilibrium Moisture Content PMMA Polymethyl methacrylate PTFE Polytetrafluoroethylene RH Relative Humidity TPS Transient Plane Source XPS Extruded Polystyrene

conductivity of the material), thermal diffusivity of the material is needed to perform dynamic thermal comfort analysis of buildings. Straw can be considered as a fibrous porous material in bulk quantities for which effective thermal conductivity and thermal diffusivity can be measured. Also, straw being organic and hygroscopic in nature, its effective thermal property values are influenced by an array of factors including type of crop, local climatic conditions, composition, bulk density, moisture content, etc. 1.1. State of the art The earliest study on the measurement of thermal properties of straw bales (wheat and rice) was conducted by McCabe [8] in 1993 using guarded hot plate steady state technique. Commins and Stone [13], in a 1998 report, summarizes the results of R-values from tests conducted by various researchers. Noting the limitations in some of the earlier measurements, including the first attempt by McCabe, the authors conclude that the R-value per inch of 1.45 (k = 0.0996 W m1 K1) resulting from the guarded hot box chamber performed at Oak Ridge National Laboratory (ORNL) as the most accurate value until then. Again in a 2003 report by Stone [14], the various techniques used by researchers to measure thermal resistance and their issues are discussed. The results of the tests until 2001 as seen in Fig. 1 were focused on determining a single value of thermal resistance which can be incorporated in building standards. Although it was known that factors like temperature and moisture affected thermal properties significantly, no systematic parametric studies were performed until 2003. Ashour [17], as part of his master’s work, analyzed the effect of temperature and density on thermal properties. The author then proposed thermal conductivity correlations as a function of sample temperature and density for two types of straw: wheat and barley. The works of both McCabe and Ashour indicate that thermal conductivity does not vary much with the type of straw. Between

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Fig. 1. Timeline of thermal conductivity measurements of straw carried out with various orientations and packing densities depicted.Other factors – temperature and relative humidity – when considered are indicated in the note below the plot along with the key. (see above-mentioned references for further information.)

2004 and 2011, there were several works ([18–23]) measuring straw thermal conductivity for specific/narrow range of parameter(s). The next extensive work was performed by Ve˙jeliene˙ [24], in which four variations of the same type of straw were studied for different temperatures and densities. Two of the variations had to do with the orientation of the fibers with respect to heat flow –perpendicular and parallel; the other two had to do with macro-structure – chopped straw and defibered straw. For all four variations, the author proposed correlations for thermal conductivity as a function of density. Effect of moisture content on thermal conductivity of straw was studied only twice: first by Grelat [19] in 2004, in which only a small increase in thermal conductivity with increase in moisture content was observed for straw sample of unspecified orientation. Later in 2016, Palumbo et al. [27] proposed a positive linear correlation for thermal conductivity with respect to ambient Relative Humidity (RH). In this work, the sample (again of unspecified orientation) was a mixture of Barley straw (81%) and Corn starch (19%).The dependence of moisture content in straw on relative humidity and hygroscopic performance of straw-based constructions were studied in detail by Carfrae [28].

In some of the recent works by Douzane et al. [30], Costes et al. [31] and Lebed and Augaitis [32], efforts were made to further study the effect of variation of temperature and density on thermal conductivity with correlations being developed in all the cases (listed in Table 1). Another method of determining effective thermal conductivity or resistance is through energy balance performed on existing straw bale buildings making use of ambient weather data and indoor temperatures [35,36]. Apart from using the raw straw as construction material, it can also be processed or mixed with other material. For example, Wei et al. [37] developed straw thermal insulation through high frequency hot-pressing which exhibited low thermal conductivity values (0.051–0.053 W m1 K1) and straw mixed with other construction materials (cement, gypsum in [38] and cement, sand in [39]) have also been studied. Goodhew and Griffiths [20] measured thermal diffusivity of straw to be 1.82 106 m2 s1 while Chaussinand [35] specified a range of 0.1 106 to 3.6 106 m2 s1 for thermal diffusivity of straw, based on previous reports. Ashour [17] studied the effect of bale density on thermal diffusivity of wheat and barley varieties

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Table 1 Summary of literature in which the correlations for thermal conductivity of straw have been proposed. Author(s)

Straw type

T(°C)

%RH

q (kg m3)

Orientation with respect to heat flow

Proposed correlation for k (W m1 K1)

Lebed and Augaitis [32]

N.I.

10

50%

80–190

N.I.

0:00155þ 0:000357qþð3:381=qÞ

Costes et al. [31]

N.I.

10

N.I.

68.1– 122.7

N.I.

0:0481 þ 0:00029q 0:0113t; t:thickness of sample 0:0444 þ 0:000272q

Douzane et al. [30]

N.I.

10 – 40

N.I.

80

perpendicular parallel

0:046ð1 þ 0:009TÞ 0:067ð1 þ 0:0078TÞ

Palumbo et al. [27]

Barley(81%)+Corn Starch (19%)

20

10– 90%

107.5

N.I.

0:037 þ 0:019ð%RHÞ

Ve˙jeliene˙ [24]

N.I.

10

50%

50–120

perpendicular parallel

0:09637  0:00146q þ0:0000107q2 0:10312  0:00036q þ0:0000175q2

Ashour [17]

Wheat Barley

N.I.

N.I.

82–138 68–98

N.I.

0:0399  0:00023q þ0:00269T 0:0625  0:0005q þ0:002237T

N.I. – Not Indicated.

of straw. He observed a decrease in thermal diffusivity with increase in density for both varieties. 1.2. Methods of measuring thermal properties For the measurement of thermal properties, transient techniques, although not as accurate as steady-state methods such as the Guarded Hot Plate apparatus, offer important advantages. These include simultaneous measurement of thermal conductivity and thermal diffusivity, significantly shorter duration of experiments and capability of studying moisture effects on thermal properties of the sample under study. Moreover, transient measurement setups are generally simpler and could be built at a lower cost compared to steady-state counterparts. The transient measurement methods [40] are distinguished by the type (wire, strip or plane) and thermal profile (pulse or step) of heat source. Also, the point of temperature measurement may be at heat source or at predefined distance away from the heat source. In the current work, transient plane source method ([41,42]) is used. 1.3. Objectives of current work Though multiple measurement studies have been conducted on straw, it is observed from the literature review that the thermal conductivity studies either consider one specific parameter or a narrow range of two or three parameters that include temperature, packing density, relative humidity, orientation of fiber and type of crop. There are no correlations for thermal conductivity that takes into account more than two parameters. Moreover, the studies on thermal diffusivity, which is very important for the transient analysis of the thermal comfort in buildings, are very limited and consider only one parameter (density). To the best of the authors’ knowledge, there are no correlations to estimate the thermal diffusivity of straw taking into account the influence of different parameters. The current work is aimed at measuring the thermal conductivity and thermal diffusivity of rice straw considering the effects of temperature, packing density, relative humidity and orientation of the straw, and proposing multiple variable correlations for the two properties.

2.1. Measurement theory The experimental setup is designed to replicate the 1-D semiinfinite transient model illustrated in Fig. 2 during the duration of the experiment. The analytical solution for the model is given by,

2q Tðx; tÞ  T i ¼ k

"rffiffiffiffiffi at

p

 # x2 x x  erfc pffiffiffiffiffi exp 4at 2 2 at

ð1Þ

where T i is the initial temperature of the sample, q is the heat flux and x is the distance between the sensor and the heat source. The sample can be approximated as a semi-infinite solid to a satisfactory degree of accuracy [43] if the following criterion is satisfied:

Fourier number Fo ¼

at ðL=2Þ2

6 0:2

ð2Þ

where, t max is the measurement time and L is the thickness of the sample. An approximate maximum value of thermal diffusivity, amax (obtained from literature or other sources) for the material of the sample or similar material shall be used in the above condition. By setting a practical value of sample thickness, the maximum duration of the experiment is obtained as follows.

tmax ¼

0:2ðL=2Þ2

amax

ð3Þ

2. Methodology Transient Plane Source (TPS) method is employed for the measurement of thermal conductivity and thermal diffusivity. The temperature profile is captured by a sensor positioned at a fixed distance away from the heat source. .

Fig. 2. Semi-infinite model with constant heat flux conditions at the surface. Temperature sensor positioned at a distance of x from the surface.

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The side length W of the square shaped sample is fixed to be at least five times the distance x between the heat source and the temperature sensor as suggested by Tye et al. [44].

Polymethyl methacrylate (PMMA), Polytetrafluoroethylene (PTFE) and Extruded Polystyrene (XPS) are the reference samples considered for validating the experimental method while the

Table 2 Summary of sample dimensions and property values used for the experiment design for the three reference samples and straw.

L (set)[m] W [m] q (measured) [kg m3] k [W m1 K1] 1

c [J kg

1

K

a [m2 s1]

]

PMMA

PTFE

XPS

Straw

0.03 0.10 1172.97 0.21 [45] 0.18 [45] – –

0.04 0.11 2179.59 0.325 [46] 0.255 [46] – –

0.081 0.15 39.51 0.042 [25] 0.032 [25] 1280 [47] –

0.1 0.18 (50 – 95) 0.12 [17] 0.03 [17] 2000 [35] 1338 [35]

max. min. max. min. max.

1:15  107 [45]

1:4  107 [46]

8:31  107

1:82  106  [20]

min.

9:0  108 [45]

1:15  107 [46]

6:33  107

1:5  107 [17]

Fig. 3. Flowchart illustrating the methodology adopted for selecting sample dimensions and time window for transient measurement experiments.

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Fig. 4. Plain wooden support (top), wooden support with groove (middle) and wooden support with the thermocouple nestled within the groove (bottom).

187

material under study is rice paddy straw. For set dimensions of the sample and the maximum values of thermal diffusivity of samples (Table 2), tmax is calculated to be about 390–400 s for all the samples on applying the semi-infinite condition. In the case of straw sample, since the maximum thermal diffusivity is variable owing to several factors, the maximum time may need to be modified depending upon initial experiment results. The temperature profile obtained from the experiment is curve fit to the analytical solution to get k and a using non-linear parameter estimation procedure. The selection of the time window to be used for the curve fitting procedure depends on the sensitivity of the parameters to the change in temperature as well as the linear dependence of the parameters to each other [48]. The procedure adopted to ensure proper estimation of thermal conductivity and thermal diffusivity is shown as a flowchart in Fig. 3. Based on sensitivity coefficient analysis [42] carried out for the samples considered, a minimum time window of 100 s is determined to be sufficient for proper estimation by the curve fitting procedure for all the samples. For all samples, the final value of thermal conductivity or diffusivity is obtained by averaging the estimations resulting from curve fitting the data over a range of time windows (say,

Fig. 5. Experimental setup for transient technique based thermal properties measurement consisting of A. DC power supply in constant current condition, B. Thermocouple array, C. Acrylic container with samples inside, D. Stability chamber, E. Support mechanism, F. Heating foil G. Multimeter for voltage measurement, H. Agilent Data logger, I. Arduino controller for logging RH sensor data and J. Desktop PC.

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from (t0 ; ti ) to (t 0 ; t ðiþi0Þ ), wheret0 is the time at the start of the experiment and ti ; t iþi0 < t max ) during which the results are consistent). For calculating the standard deviation of the estimated parameters, the uncertainty analysis method described in Beck and Arnold [48] and implemented in [42] is followed here. 2.2. Experimental setup The heating element consisting of a Nickel foil (25 micron thickness), having a square shape and spiral structure with thin layers of Kapton on either sides acts as the plane heat source. It is heated by a DC power source supplying constant current. Two identical samples are placed sandwiching the heat source and held through a support mechanism to ensure good contact between the samples and heating element. Heat conducting paste is also applied on the element to minimize contact resistance existing because of the presence of air gaps. Temperature is measured using bare wire K-type thermocouples with exposed beads of diameter of about 0.5 mm. For the case of solid samples, a hole is drilled in the radial direction in such a way that the thermocouple fits snugly in the desired position. In the case of fibrous materials, the positioning is more difficult. Specifically, there are two aspects of concern while placing the thermocouple. One, the position needs to remain unchanged for all experimental trials and two, proper contact between the thermocouple bead and the straw fiber is necessary. The former is ensured by use of thin cylindrical wooden supports with the thermocouples inserted within a groove (as seen in Fig. 4) and held taut through holes drilled in the front face of the acrylic container (as seen in the inset photo of the front face of the acrylic container in Fig. 5). The additional thickness of the front cover of the con-

Table 3 Technical characteristics of equipment and instrumentation used in transient measurement experiments. Description

Details

Tolerance/Accuracy

OSWORLD OSC Stability Chamber

Operating Range: 10 °C to 60 °C, 25% to 95% RH

1 °C, 3% RH

Thermocouple

K-type

0:16 °C (over 20 °C to 50 °C)

HTU21D RH Sensor

0% to 85%

For RH conditions,[50] 20% to 80% : 2%, < 20% and > 80% : ð3  4Þ%

Digital Weighing Balance

up to 3 kg

0:2 g

tainer ensures that there is no unwanted movement of the wooden support. To ensure proper contact, heat conducting paste is used to reduce the contact resistance existing between the tip of the sensor and the contact area in the sample. For all the samples considered for study here, the thermocouples are positioned 1 cm away from the source on both sides. The schematic and the photograph of experimental setup are shown in Fig. 5. The acrylic container (C) housing the samples with the thermocouple array (B) attached is held in place using a support mechanism (E). The setup is placed inside a stability chamber (D) in order to study the effects of temperature and relative humidity on the thermal properties of the sample. Two HTU21D temperature-humidity sensors interfaced with Arduino controller (H) are used to monitor the chamber humidity and temperature. Additionally, two thermocouples also monitor the chamber temperature. The temperature data is logged in a desktop computer (J) through the Agilent 34970A data acquisition system (H). The thermocouples are calibrated using Fluke 5520A Multiproduct Calibrator traceable to Indian National Standards. The two relative humidity sensors were calibrated using saturated salt solutions [49]. The technical characteristics of the various equipment and instrumentation used during the experiments are listed in Table 3.

2.3. Sample preparation and experimental procedure Three different orientations of the straw sample are prepared and a section of the photographs as viewed from top is shown in Fig. 6. The straw fibers are arranged in an inner cardboard box with about 2.5 cm thick polystyrene foam insulation surrounding it which is then placed in an outer acrylic container. Thermocouples with the wooden support are inserted through holes drilled in the acrylic box. In the case of measurement of properties of dry straw, the samples are initially placed in a hot air oven at 105 °C to remove the moisture. The mass of the sample is noted at regular intervals in a digital balance. The drying process is continued until the decrease in mass is insignificant. After the drying process, the samples are cooled down in the stability chamber to the level of the preset temperature. It is to be noted that during the cooling period, small amount of moisture adsorption by the sample is inevitable in spite of the low humid conditions in the chamber as well as the non-hygroscopic foam layer surrounding the sample. To measure the properties of straw samples at a certain moisture content, the samples are placed in the stability chamber at a fixed Relative Humidity (RH) over several hours. A similar weighing procedure as mentioned above is adopted to ascertain whether the sample has reached Equilibrium Moisture Condition (EMC) or not.

Fig. 6. Photographs of a section of the prepared samples of straw bale of different orientations viewed from top: Fibers oriented (a) parallel, (b) random and (c) perpendicular to heat flow.

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3. Results and discussion Experimental setup and the method have been validated using the measurements of thermal conductivity and thermal diffusivity of three reference samples – PMMA, XPS and PTFE and the results are shown in Figs. 7 and 8, respectively. There is good agreement for PMMA and PTFE when compared to reference literature. XPS exhibits some variability in thermal conductivity due to differences in density and manufacturing process. There is not much literature references available to compare thermal diffusivity of XPS which once again shown variability owing to density and other factors. Overall, the experiments produce property values to a good degree of accuracy and repeatability. To investigate the effect of temperature and relative humidity on effective thermal conductivity and thermal diffusivity, straw samples of all three orientations are prepared at approximately

k (Wm-1K-1)

0.22

the same packing density of 68 kg m3. Samples in dried state are used when they are tested over a temperature range of 25 °C to 50 °C. The corresponding results of the thermal conductivity and thermal diffusivity measurements are shown in Figures (a) of 9(i) and (ii) respectively. The lack of significant increase in thermal conductivity with temperature observed in the case of perpendicular orientation could be the result of increased movement of low density air at higher temperature. The air movement in the parallel case is along the direction of heat flow aiding the transport of heat. However, in the perpendicular case, tendency of air is to move in the lateral direction in between the straw fibers acting as a deterrent to transport of heat in the direction of heat flow. Apart from the dried samples, three cases of constant relative humidity conditions (40%, 60% and 80%) are considered to study the effect of relative humidity. The temperature is set at around

(a) Current Measurement Rides et al. - Hot Disk L1 [45] Rides et al. - Heat flux L4 [45] Rides et al. - Line Source L4 [45] Dos Santos - Hot Wire [51]

0.2 0.18 0.16

k (Wm-1K-1)

0.04

k (Wm-1K-1)

(b)

0.035

Current Measurement Al-Ajlan [47] Dubois and Lebeau - Spec. A [25] Dubois and Lebeau - Spec. B [25]

0.03

0.35

189

(c)

0.3 Current Measurement Blumm et al. [46]

0.25 10

20

30

T (°C)

40

50

60

Fig. 7. Comparison of results of thermal conductivity of reference samples between current measurements and those obtained from literature: (a) PMMA, (b) XPS and (c) PTFE.

α (mm2s-1)

α (mm2s-1)

0.15

(a) Current Measurement Rides et al. - Hot Disk L1 [45] Rides et al. - Heat flux L4 [45] Rides et al. - Laser FLash L3 [45] Dos Santos - Hot Wire [51]

0.125 0.1

(b) 0.5 Current Measurement Cifuentes et al. - XPS Blue [52] Cifuentes et al.- XPS Pink [52] Cifuentes et al.- XPS Yellow [52]

0.4

α (mm2s-1)

0.3 0.15

(c)

0.125 0.1

Current Measurement Blumm et al. [46] 10

20

30

T (°C)

40

50

60

Fig. 8. Comparison of results of thermal diffusivity of reference samples between current measurements and those obtained from literature: (a) PMMA, (b) XPS and (c) PTFE. (see above-mentioned references for further information.)

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Fig. 9. (i) Thermal conductivity and (ii) thermal diffusivity variation with respect to (a) sample temperature (b) relative humidity and (c) sample packing density.

humidity, we cannot make any conclusions on the possible effects of hysteresis on the measured thermal conductivity and thermal diffusivity. As reported by Promis et al. [54], over a longer time– scale (more than 300 h) of straw being subjected to periodically varying relative humidity conditions a steady-state is reached in which the effect of hysteresis is observed to be negligible. How-

25

σr,k

σr,α

σr,k σr,α

20

15

Count

30 °C for all three relative humidity states. Based on mass loss measurements, the equilibrium moisture content of the straw samples during sorption were estimated to be around 10%, 13.5% and 16% for the relative humidities considered, respectively. Here, a 10% of the moisture content of the sample implies 10 g of moisture per 100 g of dry straw bale sample. The results are shown in Figures (b) of 9(i) and (ii) in which each data point is an average of three trials conducted for each respective condition. The results of the measurements on the dry sample are also included in the plot as those obtained under low humid conditions (<15%). The increase in effective thermal conductivity with relative humidity is found to be relatively steeper in the parallel oriented case compared to the other two orientations. In some of the early studies, the authors reasoned high thermal conductivity values of straw obtained could be due to the presence of moisture in the sample. The moisture effect has been quantized in the current work. The increase in thermal conductivity was about 1.5 times when sample was conditioned at 80% RH than when tested in dry state for random and perpendicular oriented samples. In the same way, the increase was nearly 2.5 times for the parallel case. This indicates strong influence of unhindered moisture transport of heat in the parallel case. There is more moisture present in the straw samples at higher humid conditions resulting in higher densities. As a result, thermal diffusivity remains relatively constant for the perpendicular and random oriented samples. It has been shown that the procedure followed (drying in oven and placing in a climate chamber) to make the straw samples attain EMC is subject to hysteresis effects. Due to hysteresis, straw samples are found to have higher moisture content during desorption than during sorption [53]. As the measurement experiments were carried out only after the sample had reached EMC following sorption at set relative

10

5

0

0

2

4

6

8

10

12

14

σr (%) Fig. 10. Repeatability standard deviation calculations for thermal conductivity and thermal diffusivity measurements.

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ever, for a more accurate transient hygrothermal analysis of materials like straw, the role of moisture hysteresis on thermal properties needs to be investigated. Finally, samples of four different packing densities in the range of around 50–95 kg m3 are prepared and tested. The results of variation in effective thermal conductivity and thermal diffusivity with density are shown in Figures (c) of 9(i) and (ii), respectively. Dry samples at about 25 °C are the conditions maintained for all the cases. The closely packed nature at higher densities causes

Table 4 Ranges of parameters considered for the current measurement experiments on straw. Orientation

Parameter

q [kg m3]

T½ C

RH [%]

Parallel

60.1 68.5 81.3 93.4

 ð25–45Þ  ð25–45Þ  25;  35;  45  ð25–45Þ

Dry Dry, 40, 60, 80 Dry Dry

Random

48.6 60.6 69.4 81.0

 ð25–45Þ  ð25–45Þ  ð25–45Þ  25;  40

Dry Dry Dry, 40, 60, 80 Dry

Perpendicular

56.1 67.8 78.0 87.2

 25;  45  ð25–45Þ  25;  45  ð25–45Þ

Dry Dry, 40, 60, 80 Dry Dry

191

the thermal conductivity to rise in all three orientations more so in the parallel oriented case. In certain cases, as seen in higher density random oriented sample, the increase in effective thermal conductivity is counteracted by the increased density causing a slight decrease in effective thermal diffusivity values. As to the interface between the thermocouple bead dipped in heat sink paste and the straw fiber, it is impossible to guarantee proper contact. Therefore, efforts had been made to eliminate erroneous temperature data collected from those thermocouples having poor contact with the straw fiber: firstly, three thermocouples on either side of the heating element has been used and secondly, for each experimental case (of particular sample temperature, packing density and relative humidity conditions), three trials have been undertaken. The results of repeatability calculations are depicted in Fig. 10. Each count in the graph represents the standard deviation in the measured value over three trials. Despite such efforts, the standard deviation is as high as 12% is observed in a few cases of thermal diffusivity measurement. The overall mean of repeatability standard deviation, r
r , is estimated to be 3.87% and 4.85% for thermal conductivity and thermal diffusivity measurements respectively. Using all the data collected for different conditions (Supplementary Tables S1, S2 and S3) over the range of parameters listed in Table 4, development of correlations for effective thermal conductivity and thermal diffusivity is attempted for each type of orientation. The number of data points utilized amounted to 70, 68 and 59 for parallel, random and perpendicular oriented samples, respec-

Fig. 11. Parity plots for the proposed correlations for (i) thermal conductivity and (ii) thermal diffusivity using current data for the three orientations considered: (a) parallel, (b) random and (c) perpendicular.

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Table 5 Coefficient values obtained for the proposed correlation for each orientation and corresponding coefficient of multiple determination (R2 ). R2

Orient -ation

Property a

b

c

d

e

Parallel

k [mW m1 K1] a [mm2 s1]

0:065

9:077

1:688

0:361

9:75  104

1:52  101

1:09  102

8:76  103

370:179 6:20

0:93 0:83

81:578 1:01

0:85 0:66

41:893 0:96

0:81 0:68

Random

Perpen -dicular

Coefficients

k [mW m1 K1]

0:014

1:605

0:364

0:338

a [mm2 s1]

1:29  106

9:44  103

8:32  104

4:30  104

k [mW m1 K1]

0:013

2:302

0:378

0:091

3:28  104

4:29  102

8:21  104

8:96  104

a [mm2 s1]

0.2

(a)

0.09

0.175

+15%

0.08 -15%

0.15 0.125 0.1

kpred (Wm-1K-1)

kpred (Wm-1K-1)

(b)

+15%

0.07

-15%

0.06 0.05

0.075 0.04

0.05 0.05 0.075 0.1 0.125 0.15 0.175 0.2 kexp (Wm-1K-1)

0.04

0.05

0.06 0.07 kexp (Wm-1K-1)

0.08

0.09

Fig. 12. Parity plots for the proposed correlations using current and old data for (a) parallel and (b) random/perpendicular orientations.

tively. The correlation is a function of sample temperature, relative humidity and packing density. Since it is generally observed in earlier, as well as, in the current works that the thermal properties vary non–linearly with density and linearly with temperature and relative humidity the following form is used for the correlation:

F ¼ aq þ bq þ cð%RHÞ þ dT þ e 2

ð4Þ

where, F can be k or a. This model was found to perform well overall for all orientations and for both effective thermal conductivity and thermal diffusivity as seen from parity plots shown in Fig. 11. The coefficients calculated are listed in Table 5. Two more models with density in the denominator of the first term were also considered but the proposed correlation above fared slightly better. It can be observed that random and perpendicular has similar magnitude of thermal property values and follows similar trends with variation in parameters to some extent. Further, thermal conductivity data available in the literature with all conditions of the experiment clearly specified were combined with the current data to arrive at correlations based on a larger dataset and greater range of parameters. Thus, we propose correlations of similar form as above for parallel and random/perpendicular orientations making using of 99 and 206 data points respectively. Although the experiments carried out in the current work considers a temperature range between 25 °C and 50 °C and a maximum density of about 93 kg m3, the following correlatons making use of both the current experimental results and the previously reported data in literature is applicable to wider ranges of temperature and density as detailed below.

Parallel Orientation applicable for ( 10 °C) 6T 6( 50 °C), ( 60 kg m3) 6 q 6( 120 kg m3) and samples in dry state and when conditioned in relative humidities of up to 80%:

k ¼  0:0103q2 þ 2:196q þ 1:573ð%RHÞ þ 0:478T  46:072½mWm1 K1 ; R2 ¼ 0:83

ð5Þ

Random/Perpendicular Orientation applicable for ( 10 °C) 6T 6( 50 °C), ( 45 kg m3) 6 q 6( 200 kg m3) and samples in dry state and when conditioned in relative humidities of up to 90%:

k ¼  0:0002q2 þ 0:317q þ 0:315ð%RHÞ  0:042T þ 30:794½mWm1 K1 ; R2 ¼ 0:69

ð6Þ

The parity plots for the correlations above is depicted in Fig. 12. Due to lack of sufficient experimental data in the literature, only one set of correlations has been developed for thermal diffusivity based on the present experimental data. 4. Conclusions 1. A comprehensive review of the measured thermal transport properties of straw has been done and the need for a detailed investigation has been identified. In the present work, extensive experiments have been carried out to investigate the influence of temperature, packing density, relative humidity and the orientation of straw bale sample on thermal transport properties. Two sets of correlations have also been proposed for thermal conductivity, one based on the measurements from the present experimental work and the other considering the present data and also the data available in the literature. One set of correlation has been proposed for the thermal diffusivity.

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2. The thermal transport properties of straw measured need to be viewed from the perspective of indoor thermal comfort when the material is used as a part of the building envelope. From the present experimental work, it is clear that the orientation of the fibers has the biggest impact with random and perpendicular oriented straw samples (0.040–0.084 W m1 K1) acting as better insulators than parallel oriented straw sample (0.069– 0.194 W m1 K1). The difference in thermal conductivity of approximately 1.7–1.8 times between parallel and perpendicular oriented samples is consistent with earlier works. Although substantial rise in thermal conductivity (about 130% in the case of parallel oriented and about 50% in the case of random/perpendicular) with respect to relative humidity conditions (sample at 80% RH compared to the dry sample) is found, it is to be noted that straw when used as a building material is unlikely to attain equilibrium with ambient relative humidity conditions because of the dynamic nature of prevailing weather conditions. Therefore, the measured values of the properties under high humid cases are to be treated as extreme values which could be useful during energy calculations in the design stage of a building construction. 3. Thermal inertia decides the time lag between peak indoor and outdoor temperatures for a building. In warm and humid climate zones, the use of construction materials with only their insulating nature taken into account, simply shifts the peak temperature from day time to evening time. This leads to uncomfortable evening hours when the relative humidity is also quite high and increased load on air-conditioners, if installed, eventually worsening the performance of the building in terms of thermal comfort and energy efficiency. Straw, along with similar materials, has the potential to behave as suitable thermal and moisture buffers. As such, the evaluation of thermal diffusivity under different conditions paves the way for improved transient thermal analysis of straw based buildings. The thermal diffusivity measured range from 0.24 106 to 1.53 106 m2 s1. Using thermal conductivity and thermal diffusivity, one can determine the heat capacity of the straw bale sample. 4. The different types of straw such as rice, wheat and barley differ slightly in their chemical composition. Although a couple of earlier studies have indicated insignificant variation in thermal properties among the different types of straw, it is still necessary to further analyze their possible effects at different conditions, especially relative humidity. Owing to difficulties in procuring other types of straw, the current work has been restricted to studying rice straw only. The current experiments have considered a temperature range of 25 °C to 45 °C which is also typical in tropical climatic zones prevalent in central and southern India. If straw is to be used as a construction material in those regions where temperatures can drop to 0 °C or below, effect of phenomena such as ice formation on thermal properties of straw needs to be explored further. The operating range of the equipment used in the current study limited the temperature range considered. As to density of straw bales, when used as load-bearing construction material, it is essential to adhere to minimum requirements, around 100–110 kg m3 [4,55], in order to ensure structural integrity. From a thermal comfort perspective, conclusions on the suitable straw bale density can only be drawn after transient thermal comfort analysis based on extensive simulations supported by experimental validation. The current work does not consider possible effects of moisture hysteresis on thermal properties of straw. Dedicated experiments over the course of weeks are required to draw a solid conclusion on the role of moisture hysteresis so that transient hygrothermal performance of straw based constructions can be more accurately analyzed.

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