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Annals of Occupational Hygiene Advance Access originally published online on July 20, 2006
Annals of Occupational Hygiene 2006 50(8):833-842; doi:10.1093/annhyg/mel050
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© The Author 2006. Published by Oxford University Press on behalf of the British Occupational Hygiene Society

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

XIAOMING QIAN1,2 and JINTU FAN1,*

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

*Author to whom correspondence should be addressed. E-mail: tcfanjt{at}inet.polyu.edu.hk


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
 REFERENCES
 
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
TOP
 ABSTRACT
 INTRODUCTION
EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
 REFERENCES
 
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 perspiration effectively. So it is desirable to predict the clothing thermal insulation It and moisture vapour resistance Rt, 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 It and Rt 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 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.


   EXPERIMENTAL DESIGN AND RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
 REFERENCES
 
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.


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  		Table 1. Description of clothing ensembles tested in the present study

 


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  		Table 2. Description of clothing ensembles tested in the present study

 
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 area-weighted 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.


Figure 1
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  		Fig. 1. Walter in ‘walking’ motion.

 
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 0 m s–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 It and moisture vapour resistance Rt of clothing can be measured and calculated by the following equations:

Formula 1(1)

Formula 2(2)

Formula 3(3)

Formula 4(4)
where, It and Rt are, respectively, the total thermal insulation (m2 °C W–1) and the total moisture vapour resistance (Pa m2 W–1) of clothing ensembles, respectively. Hd is the dry heat loss from the manikin (W); Hs is the heat generated from the heating elements in the manikin (W); Hp is the heat generated from the pump; Ha is the energy required to heat the water supplement to manikin's body temperature (W) and He is the evaporative heat loss from skin to the environment (W). Ta and Ts are the environmental temperature and the area-weighted mean skin temperature in degrees centigrade (°C). As is the body (manikin) surface area (m2). psa and pss are the saturated moisture vapour pressure (Pa) at environment temperature and at skin temperature, respectively. RHa is the relative humidity of the environment in percent (%). Q is the water loss (or ‘perspiration rate’) from the manikin (g h–1). Res is the moisture vapour resistance of the manikin skin (8.6 Pa m2 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 (Vwind = 0.22, 0.85, 1.69, 2.48, 3.12 and 4.04 m s–1, with Vwind = 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 (Vwalk = 0, 0.23, 0.46 and 0.69 m s–1 with Vwalk= 0 m s–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.


   BUILDING A NEW DIRECT REGRESSION PREDICTION MODEL
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
 REFERENCES
 
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 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.


Figure 2
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  		Fig. 2. (a) Clothing thermal insulation versus wind velocity. (b) Clothing moisture vapour resistance versus wind velocity.

 
The reduction ratios, FI and FR, for thermal insulation and for moisture vapour resistance can be expressed as:

Formula 5(5)

Formula 6(6)

Formula 7(7)

Formula 8(8)
where, Ist and It are the total thermal insulation (m2 °C W–1) of garment in the case of body standing in still air and under any situations, respectively. Rst and Rt are the total moisture vapour resistance (m2 Pa W–1) of garment in the case of body standing in still air and under any situations, respectively.

The reduction ratios, FI and FR, 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, FI and FR, have approximately linear relations with the wind velocity. The slopes of FI and FR versus the wind velocity may vary with different types of clothing ensembles. Figure 4a and b plot the FI and FR versus the wind for all clothing ensembles tested in the present study. As can been seen, the approximate linear relationship between FI and FR and the wind velocity holds for all clothing ensembles tested and the slopes vary within certain ranges.


Figure 3
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  		Fig. 3. (a) FI versus wind velocity for three clothing ensembles and (b) FR versus wind velocity for three clothing ensembles.

 


Figure 4
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  		Fig. 4. (a) FI versus wind velocity for all clothing ensembles (the lines show the range of the variation of FI) and (b) FR versus wind velocity for all clothing ensembles (the lines show the range of the variation of FR).

 
Therefore, we can assume:

Formula 9(9)

Formula 10(10)
where, KI and KR are the slopes of Fig. 4a and b, respectively; v0 is the air current in the chamber under ‘still’ air condition, i.e. the condition under which Ist and Rst are measured, in this study, v0 = 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).

KI and KR can be obtained by linear regression for each clothing ensemble. The values are listed in Supplementary Table 4 in the on-line Supplementary Material.

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 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.


Figure 5
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  		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.

 
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 veff for the surface thermal insulation and surface moisture vapour resistance (Lotens and Havenith, 1991; Qian and Fan, 2005), let us define:

Formula 11(11)
where, ßF is an equivalent factor of walking speed.

Using the values of KI and KR listed in Supplementary Table 3 in the on-line Supplementary Material, ßF can be obtained by fitting equations (9) and (10), using vF from equation (11) instead of the wind velocity.

Formula 12(12)
with a correlation coefficient of fit (R2) 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:

Formula 13(13)

Formula 14(14)
When the body is walking in wind, according to the equations (13) and (14), the KI and KR for each clothing ensembles can be calculated by fitting the data; KI and KR are listed in Supplementary Table 4 in the on-line Supplementary Material in the on-line edition of this issue.

In Supplementary Table 4 in the on-line Supplementary Material, it can be seen that KI may vary from 0.24 to 0.31, and KR 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 KI and KR, we have:

Formula 15(15)

Formula 16(16)
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 (R2) of 0.97.


Figure 6
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  		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.

 

   VALIDATION OF THE MODELS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
 REFERENCES
 
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 1.13~1.93 clo (0.175–0.299 m2 °C W–1) and 30.07~51.91 m2 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 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 7
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  		Fig. 7. Measured thermal insulation with all data versus the values predicted using the new direct regression model.

 
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.


Figure 8
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  		Fig. 8. Measured clothing moisture vapour resistance with all data versus the values predicted using the new direct regression model.

 

   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
APPENDIX
 ACKNOWLEDGEMENTS
 REFERENCES
 
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, KI and KR, it was found that different clothing ensembles have different values of KI and KR, 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 KI and KR can be selected to predict It and Rt.


   APPENDIX
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
ACKNOWLEDGEMENTS
 REFERENCES
 
Variables

ßF = an equivalent factor of walking speed for the total clothing thermal insulation and moisture vapour resistance.

{lambda} = evaporative heat of water at the skin temperature, {lambda} = 0.67 W h g–1 (35oC).

Ap = the air permeability [l (m2 s)–1] of clothing fabrics.

As = the body (manikin) surface area in m2.

FI = the reduction ratio for the total thermal insulation of clothing ensembles [defined by equation (8)].

Fit = the garment fit index.

FR = the reduction ratio for the total moisture vapour resistance of clothing ensembles under an equivalent wind velocity related to standing in still air situation.

Ha = the energy required to heat the water supplement to manikin's body temperature in W.

Hd = the dry heat loss from the manikin in W.

He = the evaporative heat loss from skin to the environment in W.

Hp = the heat generated from the pump in W.

Hs = the heat generated from the heating elements in the manikin in W.

Ist = the total thermal insulation of garment in the case of body standing in still air (m2 °C W–1).

It = the total thermal insulation (m2 oC W–1) of clothing ensembles under any situation.

KI = the slopes of the curve of FI versus the wind velocity.

KR = the slopes of the curve of FR versus the wind velocity.

psa = the saturated moisture vapour pressure at environment temperature in Pa.

pss = the saturated moisture vapour pressure at the skin temperature in Pa.

Q = the water loss (or ‘perspiration rate) from the manikin (g h–1).

Res = the moisture vapour resistance of the manikin skin (8.6 Pa m2 W–1).

RHa = the relative humidity of the environment in %.

Rst = the total moisture vapour resistance of garment in the case of body standing in still air (Pa m2 W–1).

Rt = the total moisture vapour resistance (Pa m2 W–1) of clothing ensembles under any situation (Pa m2 W–1).

Ta = the environmental temperature in °C.

Ts = the area weighted mean skin temperature in °C.

v0 = the air current in the ‘still’ air condition. In this study, v0 = 0.22 m s–1.

vF = an equivalent wind velocity (m s–1).

Vwalk = walking speed (m s–1).

Vwind = wind velocity (m s–1).


   ACKNOWLEDGEMENTS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
REFERENCES
 
The authors wish to thank the University Grant Council of Hong Kong SAR for funding the project through a CERG grant no. PolyU5148/01E.

Received June 2, 2005; in final form May 30, 2006


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL DESIGN AND RESULTS
 BUILDING A NEW DIRECT...
 VALIDATION OF THE MODELS
 CONCLUSIONS
 APPENDIX
 ACKNOWLEDGEMENTS
 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. 07.01D76–3218 November 2004.

Bouskill LM, Havenith G, Kuklane K, et al. (2002) Relationship between clothing ventilation and thermal insulation. AIHA J 63:262–8.

Fan J and 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.[CrossRef]

Fan JT and Qian XM. (2004) New functions and applications of Walter, the sweating fabric manikin. Eur J Appl Physiol 92:641–4.[CrossRef][Web of Science][Medline]

Holmer I, Nilsson G, Havenith I, et al. (1999) Clothing convective heat exchange. Ann Occup Hyg 43:329–37.[Abstract/Free Full Text]

Holmer I, Nilsson H, Meinander H. (1996) Evaluation of clothing heat transfer by dry, sweating manikin measurements. In Johnson JS and Mansdorf SZ (Eds.). Performance of protective clothing.(American Society for Testing and Materials, STP, West Conshohoken, PA) 5th Vol: pp. 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 and Havenith G. (1988) Ventilation of rainwear determined by a trace gas method. Environmental ergonomics(Taylor & Francis, London) pp. pp. 162–76.

Lotens WA and 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.[Medline]

Nilsson HO, Anttonen H, Holmer I. (2000) Method for cold protective clothing evaluation. Ergonomics of protective clothing. Proceedings of Nokobetef 6and 1st European conference on protective clothingMay 7–10, 2002Stockholm, Sweden.

Qian X and Fan J. (2005) Surface thermal insulation and moisture vapour resistance of human body under varying environmental conditions and walking speeds. 11th International Conference on Environmental Ergonomics, ICEE2005May 22–26, 2005Ystad, 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.


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