Prediction of Clothing Thermal Insulation and Moisture Vapour Resistance of the Clothed Body Walking in Wind

Ann. Occup. Hyg., Vol. 50, No. 8, pp. 833 842, 2006 # 2006 The Author 2006. Published by Oxford University Press on behalf of the British Occupational Hygiene Society doi:10.1093/annhyg/mel050 Prediction of Clothing Thermal Insulation and Moisture Vapour Resistance of the Clothed Body Walking in Wind XIAOMING QIAN 1,2 and JINTU FAN 1 * 1 Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; 2 School of Textiles, The Tianjin Polytechnic University, Tianjin, China Received 2 June 2005; in final form 30 May 2006; published online 20 July 2006 Clothing thermal insulation and moisture vapour resistance are the two most important parameters in thermal environmental engineering, functional clothing design and end use of clothing ensembles. In this study, clothing thermal insulation and moisture vapour resistance of various types of clothing ensembles were measured using the walking-able sweating manikin, Walter, under various environmental conditions and walking speeds. Based on an extensive experimental investigation and an improved understanding of the effects of body activities and environmental conditions, a simple but effective direct regression model has been established, for predicting the clothing thermal insulation and moisture vapour resistance under wind and walking motion, from those when the manikin was standing in still air. The model has been validated by using experimental data reported in the previous literature. It has shown that the new models have advantages and provide very accurate prediction. Keywords: clothing physical characteristics; moisture vapour resistance; prediction model; thermal insulation; walking-able sweating manikin INTRODUCTION Clothing thermal insulation and moisture vapour resistance are two most important parameters in thermal environmental engineering, functional clothing design and end use of clothing ensembles. They are intrinsic properties of clothing depending on the fabric properties, garment(s) style and fitting, and are affected by body posture, body motion and environmental conditions. The thermal insulation and moisture vapour resistance can be measured by taking measurements on human subjects. This method gives realistic results, but requires sophisticated equipment and is time consuming, and the measured values may also have large variability. Human-shaped thermal manikins which can simulate the heat and mass transfer between human body and environment have therefore been developed for the purpose. Measurements on thermal manikins are more reproducible, but the manikins are generally very expensive and very few can simulate *Author to whom correspondence should be addressed. E-mail: tcfanjt@inet.polyu.edu.hk perspiration effectively. So it is desirable to predict the clothing thermal insulation I t and moisture vapour resistance R t, not only because of the limitations of measuring these parameters on human subjects and thermal manikins, but also because of the fact that it is practically impossible to measure I t and R t for endless clothing ensembles under the different body movement and various environment conditions. Although considerable work has been carried out so far for predicting the clothing thermal insulation and moisture vapour resistance under various conditions (Spencer-Smith, 1977a,b; Lotens and Havenith, 1991; ISO,1995; Holmer et al., 1999; Nilssion et al., 2000), the reduction of thermal insulation or moisture vapour resistance induced by wind in the existing models was considered in very different forms. Heat and mass transfer and its interaction in clothing system are very complex processes. In order to predict or achieve the optimum performance with regards to clothing thermal comfort, knowledge of the effects of body motion and environmental parameters, especially wind velocity and walking speed, is essential. In this study, clothing thermal insulation and moisture vapour resistance of various types of clothing 833

834 X. Qian and J. Fan ensembles were measured using the walking-able sweating manikin, Walter (Fan and Qian, 2004) under various environmental conditions and walking speeds. Based on an extensive experimental investigation and an improved understanding of the effects of body activities and environmental conditions, a simple but effective direct regression model has been established for predicting the clothing thermal insulation and moisture vapour resistance under wind and walking motion from those when the manikin was standing in still air. 0ms 1 (standing) to 2.7 km h 1 by adjusting AC frequency of the power supply to the motor that drives the motion. Unlike most existing manikins, Walter has thermal insulation and moisture vapour resistance measured simultaneously. With this manikin, the total thermal insulation I t and moisture vapour resistance R t of clothing can be measured and calculated by the following equations: I t ¼ A s ðt s T a Þ ð1þ H d EXPERIMENTAL DESIGN AND RESULTS H d ¼ H s þ H p H a H e ð2þ Description of clothing ensembles In the present study 32 sets of clothing ensembles were tested. The clothing ensembles consisted of the same pair of pants, but vary in the top garments. The pants were a casual pair from Giordano, made of a fabric with a composition of 98% cotton and 2% lycra. The top garments of the clothing ensembles are described in Tables 1 and 2. In Table 2, Jacket 1 and Jacket 2 represent a leisure jacket and a jacket in which two layers of fabric are combined, respectively. The thickness and the air permeability apply to the shell fabric, measured using the FAST system (SiroFAST, 1989) and ASTM D737-96 method (ASTM Book of Standards, 2004). The garment fit index is defined as the areaweighted average of the percentage difference between the inner circumferences of different parts of the garment and the corresponding circumferences of body. Experimental conditions and results Figure 1 shows a picture of the sweating fabric manikin, Walter (Fan and Chen, 2002; Fan and Qian, 2004) used for the investigation. Walter has a man s body; its size and configurations are similar to a typical Chinese man. Walter simulates perspiration using a waterproof, but moisture-permeable, fabric skin, which holds the water inside the body, but allows moisture vapour to pass through the skin. Walter achieves a body temperature distribution similar to a real person by having warm water at the body temperature (37 C) pumped from its centre to its extremities. The mean skin temperature of Walter can be adjusted by regulating the pumping rate of the pumps inside the manikin. The regulation is performed by altering the frequency of the power supply to the pumps. Walter s skin can be unzipped and interchanged with different versions to simulate different rates of perspiration. Water is supplied automatically and water loss by perspiration is measured in real time. Walter s arms and legs can be motorized to simulate walking motion. The walking speed may be changed from R t ¼ A s ðp ss p sa RH a =100Þ R es ð3þ H e H e ¼ lq ð4þ where, I t and R t are, respectively, the total thermal insulation (m 2 CW 1 ) and the total moisture vapour resistance (Pa m 2 W 1 ) of clothing ensembles, respectively. H d is the dry heat loss from the manikin (W); H s is the heat generated from the heating elements in the manikin (W); H p is the heat generated from the pump; H a is the energy required to heat the water supplement to manikin s body temperature (W) and H e is the evaporative heat loss from skin to the environment (W). T a and T s are the environmental temperature and the area-weighted mean skin temperature in degrees centigrade ( C). A s is the body (manikin) surface area (m 2 ). p sa and p ss are the saturated moisture vapour pressure (Pa) at environment temperature and at skin temperature, respectively. RH a is the relative humidity of the environment in percent (%). Q is the water loss (or perspiration rate ) from the manikin (g h 1 ). R es is the moisture vapour resistance of the manikin skin (8.6 Pa m 2 W 1 ) (Qian and Fan, 2005). All tests were conducted in the climatic chamber under the environmental temperature of 20 0.3 C and humidity of 50 5%. Each of the 32 sets of clothing ensembles was tested under six levels of wind velocity (V wind = 0.22, 0.85, 1.69, 2.48, 3.12 and 4.04 m s 1, with V wind = 0.22 m s 1 representing the no wind condition) when the manikin was in standing position. At the wind velocity of 0.22 and 2.48 m s 1, the clothing ensembles were also tested at four levels of walking motion (V walk = 0, 0.23, 0.46 and 0.69 m s 1 with V walk = 0ms 1 representing the standing position). So for each clothing ensemble, there are 12 cases investigated. With overnight operation, it took about 2 days to complete all measurements for each clothing ensemble. Experimental results of the measurements are listed in Supplementary Table 2 in the on-line Supplementary Material to this article.

Prediction of clothing thermal insulation 835 Table 1. Description of clothing ensembles tested in the present study CL_ID Label of Description clothing 1 A S size knitting jacket, casual pants 2 B M size knitting jacket, casual pants 3 C L size knitting jacket, casual pants 4 D XXL size knitting jacket, casual pants 5 E S size denim jacket, casual pants 6 F M size denim jacket, casual pants 7 G L size denim jacket, casual pants 8 H XXL size denim jacket, casual pants 9 I S size poplin jacket, casual pants 10 J M size poplin jacket, casual pants 11 K L size poplin jacket, casual pants 12 L XXL size poplin jacket, casual pants 13 M PET napping jacket, casual pants 14 N Oxford woven cotton long-sleeve shirt, casual pants 15 O Oxford woven cotton long-sleeve army uniform, casual pants 16 P Two-layer design windbreaker comprised of nylon shell and PET mesh lining, casual pants 17 Q Dacron shell with PET bedding long-sleeve shirt, casual pants 18 R One-layer design PU coated windbreaker (leisure jacket), casual pants 19 C+S Vest and underwear brief, cotton short T-shirt, L size knitting jacket, casual pants 20 M+S Vest and underwear brief, cotton short T-shirt, PET napping jacket, casual pants 21 N+S Vest and underwear brief, cotton short T-shirt, Oxford woven cotton long-sleeve shirt, casual pants 22 O+S Vest and underwear brief, cotton short T-shirt, Oxford woven cotton long-sleeve army uniform, casual pants 23 G+S Vest and underwear brief, cotton short T-shirt, L size denim jacket, casual pants 24 K+S Vest and underwear brief, cotton short T-shirt, L size poplin jacket, casual pants 25 P+S Vest and underwear brief, cotton short T-shirt, Two-layer design windbreaker comprised of nylon shell and PET mesh lining, casual pants 26 Q+S Vest and underwear brief, cotton short T-shirt, Dacron shell with PET bedding long-sleeve shirt, casual pants 27 R+S Vest and underwear brief, cotton short T-shirt, one-layer design PU coated windbreaker (leisure jacket), casual pants 28 U+S Vest and underwear brief, cotton short T-shirt, PU coated breathable army outdoor leisure jacket, casual pants 29 V+S Vest and underwear brief, cotton short T-shirt, two-layer jacket comprised of 80% nylon/20%pet napping lining and PET poplin shell, casual pants 30 U+S +T+N Vest and underwear brief, cotton short T-shirt, Oxford woven cotton long-sleeve shirt, long cotton sweat pants, PU coated breathable army outdoor leisure jacket, casual pants 31 V+S +T+N Vest and underwear brief, cotton short T-shirt, Oxford woven cotton long-sleeve shirt, long cotton sweat pants, two-layer jacket comprised of 80% nylon/20% PET napping lining and PET poplin shell, casual pants 32 W+S Vest and underwear brief, cotton short T-shirt, long cotton sweat pants, nylon film leisure jacket S Vest and underwear brief and with short T-shirt, cotton T Sweat pants, cotton Note: CL_ID represents a clothing ensemble label denoting which clothing ensemble was clothed on manikin. BUILDING A NEW DIRECT REGRESSION PREDICTION MODEL Effect of wind velocity In the existing prediction models, the reduction of thermal insulation or moisture vapour resistance by wind was considered in very different forms. Spencer-Smith (1977a,b) used a linear relationship, Loten and Havenith (1991) used the square root function, whereas Holmer et al. (1999) and Nilsson et al. (2000) used a complex exponential function to model the effect of wind velocity. It is therefore necessary to investigate the best way to model the effect of wind velocity before an improved prediction model can be established. Figure 2a and b plot the clothing thermal insulation and moisture vapour resistance against the

836 X. Qian and J. Fan Table 2. Description of clothing ensembles tested in the present study CL_ID Label of clothing Style Thickness T 2 (mm) Permeability ap [l (s m 2 ) 1 Pa) 1 ] Fit index 1 A Jacket 1.405 20.6133 2.9 2 B 5.2 3 C 8.7 4 D 11.6 5 E 0.939 1.0761 2.9 6 F 5.2 7 G 8.7 8 H 11.6 9 I 0.443 0.0392 2.9 10 J 5.2 11 K 8.7 12 L 11.6 13 M Jacket 3.891 4.2415 10.3 14 N Shirt 0.406 1.7480 11.3 15 O Uniform 0.724 1.4488 11.1 16 P Jacket_2 0.720 0.0280 12.2 17 Q Shirt 3.250 0.0280 12.2 18 R Jacket_1 0.113 0.0166 14.5 19 C+S Jacket 1.405 20.6133 8.7 20 M+S Jacket 3.891 4.2415 10.3 21 N+S Shirt 0.406 1.7480 11.3 22 O+S Uniform 0.724 1.4488 11.1 23 G+S Jacket 0.939 1.0761 8.7 24 K+S Jacket 0.443 0.0392 8.7 25 P+S Jacket_2 0.720 0.0280 12.2 26 Q+S Shirt 3.250 0.0280 12.2 27 R+S Jacket_1 0.113 0.0166 14.5 28 U+S Jacket_1 0.469 0.0000 24.3 29 V+S Jacket_2 3.952 0.0000 23.9 30 U+S+T+N Jacket_1 0.469 0.0000 24.3 31 V+S+T+N Jacket_2 3.952 0.0000 23.9 32 W+S Jacket_1 0.113 0.0000 20.3 Note: CL_ID represents a clothing ensemble label denoting which clothing ensemble was clothed on manikin. wind velocity for three clothing ensembles. It can be seen that there is a general trend that clothing thermal insulation or moisture vapour resistance decreases with the increase in wind velocity, but the rate of reduction decreases with the increase in wind velocity. The reduction ratios, F I and F R, for thermal insulation and for moisture vapour resistance can be expressed as: I st ¼ ð1 þ F I ÞI t ð5þ F I ¼ I st I t I t ð6þ R st ¼ ð1 þ F R ÞR t ð7þ F R ¼ R st R t R t ; ð8þ where, I st and I t are the total thermal insulation (m 2 CW 1 ) of garment in the case of body standing in still air and under any situations, respectively. R st and R t are the total moisture vapour resistance (m 2 Pa W 1 ) of garment in the case of body standing in still air and under any situations, respectively. The reduction ratios, F I and F R, are related to the wind velocity; they are plotted against the wind velocity for three clothing ensembles in Fig. 3a and b as examples. As can been seen, the reduction ratios, F I and F R, have approximately linear relations with the wind velocity. The slopes of F I and F R versus the wind velocity may vary with different types of clothing ensembles. Figure 4a and b plot the F I and F R versus the wind for all clothing ensembles tested in the present study. As can been seen, the approximate linear relationship between F I and F R and the wind velocity holds for all

Prediction of clothing thermal insulation 837 clothing ensembles tested and the slopes vary within certain ranges. Therefore, we can assume: F I ¼ K I ðv wind v 0 Þ ð9þ F R ¼ K R ðv wind v 0 Þ ð10þ where, K I and K R are the slopes of Fig. 4a and b, respectively; v 0 is the air current in the chamber under still air condition, i.e. the condition under which I st and R st are measured, in this study, v 0 = 0.22 m s 1 (In any climate chamber, even at still air condition, there is air current. This is essential for the operation of air conditioning system in the chamber). K I and K R can be obtained by linear regression for each clothing ensemble. The values are listed in Supplementary Table 4 in the on-line Supplementary Material. Fig. 1. Walter in walking motion. Effect of walking speed Figure 5a and b plot the clothing thermal insulation and moisture vapour resistance against walking speed for three clothing ensembles under two windy conditions. As can be seen, the clothing thermal (a) (b) Fig. 2. (a) Clothing thermal insulation versus wind velocity. (b) Clothing moisture vapour resistance versus wind velocity.

838 X. Qian and J. Fan (a) (b) Fig. 3. (a) F I versus wind velocity for three clothing ensembles and (b) F R versus wind velocity for three clothing ensembles. (a) (b) Fig. 4. (a) F I versus wind velocity for all clothing ensembles (the lines show the range of the variation of F I ) and (b) F R versus wind velocity for all clothing ensembles (the lines show the range of the variation of F R ).

Prediction of clothing thermal insulation 839 (a) (b) Fig. 5. (a) Total thermal insulation versus walking speed for three clothing ensembles and (b) total moisture vapour resistance versus walking speed for three clothing ensembles. insulation and moisture vapour resistance decrease with increasing walking speed, and the ratio of reduction decreases with increasing walking speed and wind velocity. This is similar to the effect of wind velocity on clothing thermal insulation and moisture vapour resistance. Therefore, we can use an equivalent wind velocity to take into account the effect of walking speed. By analogy with the definition of effective wind velocity v eff for the surface thermal insulation and surface moisture vapour resistance (Lotens and Havenith, 1991; Qian and Fan, 2005), let us define: v F ¼ V wind þ b F V walk ð11þ where, b F is an equivalent factor of walking speed. Using the values of K I and K R listed in Supplementary Table 3 in the on-line Supplementary Material, b F can be obtained by fitting equations (9) and (10), using v F from equation (11) instead of the wind velocity. b F ¼ 1:8 ð12þ with a correlation coefficient of fit (R 2 ) of 0.97. This means the effect of walking speed on the thermal insulation and moisture vapour resistance is stronger than the effect of wind velocity. The new regression model Substituting equations (6) and (8) with equations (9) (12) and rewritten as below: I t I st ¼ R t R st ¼ 1 1 þ K I ðv wind þ 1:8V walk v 0 Þ 1 1 þ K R ðv wind þ 1:8V walk v 0 Þ ð13þ ð14þ When the body is walking in wind, according to the equations (13) and (14), the K I and K R for each clothing ensembles can be calculated by fitting the data; K I and K R are listed in Supplementary Table 4 in the on-line Supplementary Material in the on-line edition of this issue.

840 X. Qian and J. Fan In Supplementary Table 4 in the on-line Supplementary Material, it can be seen that K I may vary from 0.24 to 0.31, and K R may vary from 0.23 to 0.42, depending on the clothing characteristics such as fabric air permeability, garment style, garment fitting and clothing construction. Using the average values of K I and K R, we have: I t I st ¼ 1 1 þ 0:27ðV wind þ 1:8V walk v 0 Þ ð15þ (a) R t R st ¼ 1 1 þ 0:32ðV wind þ 1:8V walk v 0 Þ ð16þ With equations (15) and (16), the clothing thermal insulation and moisture vapour resistance under windy conditions and walking motion can be predicted from those measured when the manikin is standing in still air condition. Figure 6a and b plot the predicted clothing thermal insulation and moisture vapour resistance against the measured values. As can been seen, the model can fit the measured data very well with a correlation coefficient of fit (R 2 ) of 0.97. (b) VALIDATION OF THE MODELS The models are based on the experimental data of 32 sets of clothing ensembles, including tight and loose fit garments, jackets, shirts and uniforms with permeable and impermeable outer fabrics. These clothing assembles were tested on the walking-able sweating manikin Walter in a climate chamber under 20 C and 50% RH, with the wind velocity and walking speed varying from 0.22 to 4.04 m s 1 and 0 to 0.69 m s 1, respectively. The static total thermal insulation and moisture vapour resistance of the clothing ensembles ranged 1.131.93 clo (0.175 0.299 m 2 C W 1 ) and 30.0751.91 m 2 Pa W 1, respectively. Although this has been a systematic experimental investigation, the models developed based on these limited experimental data were validated with experimental data from other sources. The database used to validate the models includes those reported in the published literatures. Some of these data were obtained from manikins (Hong, 1992; Holmer et al., 1996; Bouskill et al., 2002; Adair, 2005) and some were from measurements on human subjects (Nielsen et al., 1985; Lotens and Havenith, 1988; Havenith 1990a,b). Figure 7 plots the measured dynamic thermal insulation against the values predicted using the new direct regression model developed in the present study with all database. As can be seen, the new direct regression model predicts the measured thermal insulation from both our experiments on the sweating manikin, Walter, and those reported in the literature quite well. There is however some Fig. 6. (a) Measured thermal insulation versus predicted values using the new model and (b) measured moisture vapour resistance versus predicted values using the new model. underestimation for clothing ensembles with high thermal insulation, particularly for the two winter ensembles tested by Holmer et al. and one winter ensemble tested by Bouskill et al. (2002). This may be due to the fact that, in the experimental data used for establishing the new direct regression model, there is no winter clothing ensemble as warm as those two tested by Holmer et al. and that tested by Bouskill et al. (2002). Figure 8 plots the measured clothing moisture vapour resistance against the values predicted using the new direct regression model. With the exception for the data of the impermeable rain coverall tested by Havenith et al. on human subjects using the tracer gas method, the new direct regression model provides very good prediction. The squared correlation coefficient of the new direct regression model would be 0.91, if the data of the impermeable rain coverall tested by Havenith et al. on human subjects using the trace gas method was omitted in the analysis.

Prediction of clothing thermal insulation 841 Fig. 7. Measured thermal insulation with all data versus the values predicted using the new direct regression model. Fig. 8. Measured clothing moisture vapour resistance with all data versus the values predicted using the new direct regression model. CONCLUSIONS From the experimental investigation, it was shown that clothing thermal insulation and moisture vapour resistance decrease with increasing wind velocity and walking speed. The effects of walking speed for the total thermal insulation and moisture vapour resistance of clothing system are equivalent to 180% of the wind velocity. Based on an improved understanding of the effects of wind and walking motion on the clothing thermal insulation and moisture vapour resistance, a simple, but effective regression model was developed for predicting the dynamic clothing thermal insulation and moisture vapour resistance under walking motion and windy conditions from the values of the clothing thermal insulation and moisture vapour resistance measured under person standing in the still air. For the prediction parameters, K I and K R, it was found that different clothing ensembles have different values of K I and K R, and they are significantly affected by the air permeability of the outer fabric, fit index and garment style as well as whether or not there is underwear on the body. Generally, the average values of K I and K R can be selected to predict I t and R t.

842 X. Qian and J. Fan Acknowledgements The authors wish to thank the University Grant Council of Hong Kong SAR for funding the project through a CERG grant no. PolyU5148/01E. APPENDIX Variables b F = an equivalent factor of walking speed for the total clothing thermal insulation and moisture vapour resistance. l=evaporative heat of water at the skin temperature, l=0.67 W h g 1 (35 o C). A p = the air permeability [l (m 2 s) 1 ] of clothing fabrics. A s = the body (manikin) surface area in m 2. F I = the reduction ratio for the total thermal insulation of clothing ensembles [defined by equation (8)]. F it = the garment fit index. F R = the reduction ratio for the total moisture vapour resistance of clothing ensembles under an equivalent wind velocity related to standing in still air situation. H a = the energy required to heat the water supplement to manikin s body temperature in W. H d = the dry heat loss from the manikin in W. H e = the evaporative heat loss from skin to the environment in W. H p = the heat generated from the pump in W. H s = the heat generated from the heating elements in the manikin in W. I st = the total thermal insulation of garment in the case of body standing in still air (m 2 CW 1 ). I t = the total thermal insulation (m 2o CW 1 ) of clothing ensembles under any situation. K I = the slopes of the curve of F I versus the wind velocity. K R = the slopes of the curve of F R versus the wind velocity. p sa = the saturated moisture vapour pressure at environment temperature in Pa. p ss = the saturated moisture vapour pressure at the skin temperature in Pa. Q = the water loss (or perspiration rate) from the manikin (g h 1 ). R es = the moisture vapour resistance of the manikin skin (8.6 Pa m 2 W 1 ). RH a = the relative humidity of the environment in %. R st = the total moisture vapour resistance of garment in the case of body standing in still air (Pa m 2 W 1 ). R t = the total moisture vapour resistance (Pa m 2 W 1 ) of clothing ensembles under any situation (Pa m 2 W 1 ). T a = the environmental temperature in C. T s = the area weighted mean skin temperature in C. v 0 = the air current in the still air condition. In this study, v 0 = 0.22 m s 1. v F = an equivalent wind velocity (m s 1 ). V walk = walking speed (m s 1 ). V wind = wind velocity (m s 1 ). REFERENCES Adair ER. (2005) RF protective garments as a countermeasure to field strengths in excess of IEEE C95.1-1999 Standard, http://www.radhaz.com/files/naptex _thermal_evaluation.pdf. ASTM Book of Standards. (2004) Textiles (I). Vol. 07.01, November 2004. pp. D76 3218. Bouskill LM, Havenith G, Kuklane K et al. (2002) Relationship between clothing ventilation and thermal insulation. AIHA J; 63: 262 8. Fan J, Chen YS. (2002) Measurement of clothing thermal insulation and moisture vapor resistance using a novel perspiring fabric thermal manikin. Meas Sci Technol; 13: 1115 23. Fan JT, Qian XM. (2004) New functions and applications of Walter, thesweatingfabricmanikin. Eur J Appl Physiol; 92: 641 4. Holmer I, Nilsson G, Havenith I et al. (1999) Clothing convective heat exchange. Ann Occup Hyg; 43: 329 37. Holmer I, Nilsson H, Meinander H, (1996) Evaluation of clothing heat transfer by dry and sweating manikin measurements. In Johnson JS and Mansdorf SZ, editors. Performance of protective clothing. 5th Vol. West Conshohoken, PA: American Society for Testing and Materials, STP 1237. Hong S. (1992) A database for determining the effect of walking on clothing insulation. Doctoral dissertation, Department of Clothing, Textiles, and Interior Design, College of Human Ecology, Kansas State University, Manhattan. ISO (1995) Ergonomics of the thermal environment estimation of the thermal insulation and evaporative resistance of a clothing ensemble. ISO 9920. Geneva: International Organization for Standardisation. Lotens WA, Havenith G. (1988) Ventilation of rainwear determined by a trace gas method. In Environmental ergonomics. London: Taylor & Francis. pp. 162 76. Lotens WA, Havenith G. (1991) Calculation of clothing insulation and vapor resistance. Ergonomics; 34: 233 54. Nielsen R, Olesen BW, Fanger PO. (1985) Effect of physical activity and air velocity on the thermal insulation of clothing. Ergonomics; 28: 1617 31. Nilsson HO, Anttonen H, Holmer I. (2000) Method for cold protective clothing evaluation. Ergonomics of protective clothing. In Proceedings of Nokobetef 6and 1st European conference on protective clothing, May 7 10, 2002, Stockholm, Sweden. Qian X, Fan J. (2005) Surface thermal insulation and moisture vapour resistance of human body under varying environmental conditions and walking speeds. In 11th International Conference on Environmental Ergonomics, ICEE2005, May 22 26, 2005, Ystad, Sweden. SiroFAST. (1989) Fabric assurance by simple testing. CSIRO instruction manual. Sydney, Australia: Division of Wool Technology. Spencer-smith JL. (1977a) The physical basis of clothing comfort, Part 2. Cloth Res J; 5: 1 17. Spencer-smith JL. (1977b) The physical basis of clothing comfort, Part 3. Cloth Res J; 5: 82 100.