Healthy Buildings 2017 Europe July 2-5, 2017, Lublin, Poland

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1 Healthy Buildings 2017 Europe July 2-5, 2017, Lublin, Poland Paper ID 0113 ISBN: Measurements of local clothing resistances and local area factors under various conditions Stephanie Veselá 1,*, Agnes Psikuta 2, Boris RM Kingma 1,3, Arjan JH Frijns 1 1 Dept. of Mechanical Engineering, Eindhoven University of Technology, The Netherlands. 2 Empa, Swiss Federal Laboratories for Materials Science and Technology, St. Gallen, Switzerland. 3 Dept. of Human Biology and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism of Maastricht University Medical Center+, The Netherlands. * Corresponding s.vesela@tue.nl SUMMARY The local dry thermal resistances of typical office ensembles was measured according to EN- ISO on a sweating agile manikin for different air speeds and body movement. Also, the local clothing area factors were estimated based on 3D scans. The results of five representative office outfits are discussed in this paper. Measured local insulation values and estimated local area factors differ from data in other studies. Since literature data are mostly between values obtained for regular and loose fit in this study, this difference is likely due to the garment fit on the manikin and reveals the necessity of reporting clothing fit parameters (e.g. ease allowance) in the publications. The increased air speed and body movement mostly decrease the local dry thermal insulation. We emphasize the need for well documented garment parameters and measurements to get reproducible results and to choose accurate clothing parameters for thermo-physiological and thermal sensation modelling. KEYWORDS Local clothing insulation, local area factor, thermal modelling, office ensembles 1 INTRODUCTION An accurate local thermal sensation model is indispensable for the effective development of personalized and locally applied heating and cooling systems in office environments. The output of such a model relies on the accurate prediction of local skin temperatures, which in turn depend on reliable input data of the local clothing dry and evaporative thermal resistance and clothing area factor. However, for typical office clothing ensembles only few local datasets are available in the literature (Veselá et al., 2016). Moreover, limited research was done on the local effect of increased air speeds and body movement on the dry thermal resistance. To close this gap, we measured the local dry and evaporative thermal resistance of eight body parts at three different air speeds and including body movement of a large variety of typical office clothing ensembles using a sweating agile manikin (SAM) at EMPA, Switzerland. Additionally, the local clothing area factors were estimated based on 3D scans of all clothing items (Frackiewicz-Kaczmarek et al., 2015; Mert et al., 2016). In this conference paper, the

2 preliminary results of the local area factors and local dry thermal resistance of 5 clothing ensembles are shown and discussed for one air speed and the addition of body movement. 2 METHODS The local dry thermal resistance was measured using the sweating agile manikin (SAM) at EMPA, Switzerland as described in (Richards and Mattle, 2001). Measurement procedure and calculations For the measurements of the local dry thermal insulation, the skin temperature was set to 34 C, the operative temperature of the environment to 21 C and the relative humidity to 40%, which is in accordance to standard EN-ISO (ISO, 2004). For the standing manikin, the air speed was set to 0.2 and to 1.0 (test cases C1 and C2). The air was directed from the front of the manikin. For body movement, the walking speed of the movement simulator was set to 2.5 with an air speed of 0.2 (test case C3). During the experiments, the dry heat loss of all body parts was recorded. The thermal resistance of the air layer was determined as the thermal insulation of the nude manikin. The measurements on the clothed manikin were repeated at least twice with redressing the manikin in between measurements. Each measurement lasted 45 minutes and the results were computed from the average of the last 20 minutes, where steady state was reached. The total dry thermal insulation, and intrinsic clothing insulation, of a specific body part was then calculated using the local area factors, described below and equation (1) as well as (2).,,,! " $ % & (1),,,! " $ % & (2) Estimation of local clothing area factor The area factor is defined as the ratio of the outer area of a dressed surface ' ()**( to the area of a nude surface ' +(*. For local area factors, this definition is applied to all body parts. In the present case, the nude and dressed areas were obtained by 3D scans of a manikin without and with clothing as described in (Psikuta et al., 2015). Figure 1a shows the nude manikin with the defined local body parts. a) with marked body parts b) with marked locations of circumferences Figure 1 Nude manikin for obtaining local area factors

3 In order to relate the results for the local area factors to other manikins (e.g. SAM) or real persons, the circumferences of the manikin were measured at various body locations (Figure 1b). The clothing items were marked and measured at the same positions. The difference between the circumferences of a clothing item at a specific body landmark and the manikin (or person) is called ease allowance, which was calculated for all items at the relevant positions. The ease allowance and the local area factors had a high correlation for all body parts (e.g. upper arm, Figure 2). With these correlations, we were able to obtain the local area factors for SAM by measuring the respective circumferences and calculating the ease allowance, accordingly. For body parts with more than one clothing layer, the clothing area factor of the outer most layer was considered. Area factor y = x R² = Ease allowance [cm] Figure 2. Correlation between local area factor and ease allowance of the upper arm Clothing ensembles The clothing ensembles were chosen to represent typical office outfits. The ensembles described in this paper are summarized in Table 1. Table 1. Clothing ensembles t-shirt (reg.) jeans (reg.) t-shirt (loose) jeans (reg.) long-sleeved smart shirt (reg., in) pants reg.:= regular fit, loose:= loose fit; in:= tucked in trousers/ skirt undershirt long-sleeved smart shirt (reg., in) business jacket pants long-sleeved smart shirt (reg., in) skirt (with tights)

4 3 RESULTS and DISCUSSION Local area factors The results for the local area factors at SAM body landmarks are shown in Table 2. It can be noted that the variance of the area factor is higher for considering the body part than for its location in the front or the back. For example, the difference between upper and lower leg is at least 0.19 whereas the difference between hip front and back is 0.06 at most. Considering all clothing ensembles, body parts with higher variance in the local area factor (e.g. hip) or lower variance (e.g. chest) can be identified. When considered strictly, the local area factors depend on the garment fit on the body identified as ease allowance and should be adjusted correspondingly for a specific clothing item and person or manikin. However, depending on the slope of the function between local area factor and ease allowance, the need for adjustment differs for different body parts (see example in Figure 2). Table 2. Estimated local area factors (f_cl) of clothing ensembles for SAM Local area factor Upper Lower Chest Back Hip Hip Upper Lower arm arm front back leg leg / / Outfit Dry thermal resistance and the influence of clothing fit, air speed and body movement The results for the local air layer insulation and local dry thermal clothing insulation are summarized in Table 3. The influence of the fit of a clothing item on the local dry thermal insulation is shown by comparing outfit number 1 and 4. Both clothing ensembles consist of a t-shirt/ jeans, but the t- shirt of outfit 4 fits looser than the one of outfit 1. As a result, the local clothing insulation of all upper body parts including the hip, are larger for outfit 4 than for outfit 1. The difference is smaller for the chest and back, where the garment is generally closer to the body (Frackiewicz- Kaczmarek et al., 2015). When increasing the air speed from 0.2 to 1.0 or adding body movement, a reduction in the dry local clothing insulation can be observed for nearly all body parts as shown for outfit 14. For the body movement, the reduction in the dry thermal insulation is mostly larger than for the increase in air speed, especially at the extremities. In outfit 22 a skirt is used instead of the pants of outfit 14. Surprisingly, the change leads to almost the same local dry thermal resistance apart from the lower leg, which is only covered by a thin tights in outfit 22. Also, the local dry thermal resistance of the back is higher in outfit 14 than in outfit 22, because the pants waist line is higher up.

5 The results for the local clothing insulation show that it is important to know the fit and exact body coverage of a clothing item as well as the environmental conditions of the measurement, before using the values in simulation programs. Table 3. Results for local air layer insulation in all three test cases (C1 C3) and for the local clothing insulation of outfits 1, 4, 14, 21 and 22 Test case/ Outfit Posture Airspeed [m/s] Upper arm Lower arm Chest Back Hip front Hip back Upper leg Lower leg Air layer insulation [m²k/w] C1 standing C2 standing C3 moving Local clothing insulation [m²k/w] 1 standing standing standing standing moving standing standing Comparison to data available in the literature Other measured local dry clothing resistance values for a clothing ensemble consisting of a t- shirt and jeans are published in studies by Lee et al. (2013) and Lu et al. (2015). Furthermore, Nelson & Curlee (2005) recomputed the overall clothing insulation and area factors published by McCullough (1985, 1989) to local values. The local clothing insulation and area factors of a clothing combination consisting of a t-shirt and jeans found in these studies are compared to the ones of our experiments (outfit 1 and 4) in Table 4. The local dry thermal resistances of our studied outfits are in the same order of magnitude as in the literature. However, local differences can be identified. For example, the local clothing insulation of the upper arm found in (Lee et al., 2013) and (Lu et al., 2015) are close to outfit 1, whereas the value in (Nelson et al., 2005) is about the same as for outfit 4. For the chest, all data of the literature gives higher values for the local clothing insulation. The local area factors found in the literature varies from our estimation. For the upper arm, it is in between the values of our study, but for the chest and back the literature provides higher values. Table 4. Comparison between measured data and literature value of dry local clothing resistances and local area factors for the upper body wearing a t-shirt/ jeans combination Local clothing insulation (m²k/w) Local area factors Body part Literature Measured Literature Measured Lee Lu Curlee Outfit 1 Outfit 4 Curlee Outfit 1 Outfit 4 Upper arm Chest Back

6 The differences between the data of this study and the literature might be caused by the distinct material and fit of the garments, the differences in the construction, set-up and posture of the used manikins or the use of slightly different environmental conditions (e.g. air speed). However, not all of this necessary information is provided in the published studies. Hence, there is an uncertainty for the users of thermophysiological or thermal sensation models, if the values are suitable for a specific simulation case. In (Veselá et al., 2016) it is shown that the differences in local clothing insulation affect the outcome of simulated local skin temperatures up to 4.4 degrees and local thermal sensation up to 1 point on the sensation scale. Hence, it is important to know as much information as possible on the used garment and measurement conditions, to apply the most fitting results in a thermophysiological model. 5 CONCLUSIONS All in all, this study increases the database on local clothing dry insulation values for typical office clothing ensembles including the effect of air speed and body movement. Furthermore, it is emphasized that the garment parameters and measurements need to be well documented to get reproducible results and to choose accurate clothing parameters for thermo-physiological and thermal sensation modelling cases. Literature Frackiewicz-Kaczmarek, J., Psikuta, A., Bueno, M.-A. and Rossi, R.M. (2015) Effect of garment properties on air gap thickness and the contact area distribution, Text. Res. J. ISO (2004) EN-ISO Clothing - Physiological effects - Measurement of thermal insulation by means of a thermal manikin., Geneva, International Standards Organization. Lee, J., Zhang, H. and Arens, E. (2013) Typical Clothing Ensemble Insulation Levels for Sixteen Body Parts. In: CLIMA Conference 2013, 1 9. Lu, Y., Wang, F., Wan, X., Song, G., Zhang, C. and Shi, W. (2015) Clothing resultant thermal insulation determined on a movable thermal manikin. Part II: effects of wind and body movement on local insulation, Int. J. Biometeorol., McCullough, E.A., Jones, B.W. and Huck, J. (1985) A comprehensive data base for estimating clothing insulation, ASHRAE Trans., 91, McCullough, E.A., Jones, B.W. and Tamura, T. (1989) A Data Base for Determining the Evaporative Resistance of Clothing, ASHRAE Trans., 95, Mert, E., Böhnisch, S., Psikuta, A., Bueno, M.A. and Rossi, R.M. (2016) Contribution of garment fit and style to thermal comfort at the lower body, Int. J. Biometeorol., International Journal of Biometeorology, 60, Nelson, D.A., Curlee, J.S., Curran, A.R., Ziriax, J.M. and Mason, P.A. (2005) Determining localized garment insulation values from manikin studies: Computational method and results, Eur. J. Appl. Physiol., 95, Psikuta, A., Frackiewicz-Kaczmarek, J., Mert, E., Bueno, M.-A. and Rossi, R.M. (2015) Validation of a novel 3D scanning method for determination of the air gap in clothing, Measurement, Elsevier Ltd, 67, Richards, M. and Mattle, N. (2001) A Sweating Agile Thermal Manikin (SAM) Developed to Test Complete Clothing Systems Under Normal and Extreme Conditions. In: Human factors and medicine panel symposium - blowing hot and cold: protecting against climatic extremes, Dresden, Germany, 1 7. Veselá, S., Kingma, B.R.M. and Frijns, A.J.H. (2016) Local thermal sensation modeling-a review on the necessity and availability of local clothing properties and local metabolic heat production, Indoor Air, 1 12.