Determining temperature ratings for children's cold weather clothing

This study examined the physical and physiological differences between children and adults that affect body heat generation and losses and then developed a heat loss model for determining the temperature ratings of cold weather clothing designed for use by children of various ages. The thermal insulation values of selected jackets were measured using a heated manikin dressed in two base ensembles, and the temperature ratings were calculated using the model. The results indicated that the type of garments used in the base ensemble had a major effect on jacket ensemble insulation and the predicted comfort temperature. For a given level of insulation, the temperature rating decreased as the wearer's age and activity level increased. This is probably because children have a higher surface area per unit mass ratio than adults, and they lose heat faster. However, this effect is partially offset by their higher metabolic rates.     

Wearer related performance standards for conditioned clothing

Abstract

Estimates, based on American experience of work in the heat, indicate that in the UK, half a million workers or more may be working in thermally uncomfortable and stressfully hot environments. In addition, many will be experiencing cold working conditions and associated discomfort. The role of protective clothing as one of the factors involved in imposing thermal stress is emphasized.

One method of thermal stress control is to provide conditioned garments which warm or cool the wearer as required. The use of ‘air supplied’ garments for cooling is specifically dealt with and the methods of defining their performance reviewed. The application of the concept of ‘per cent wetted skin surface area’ is discussed as one method of defining the performance of air ventilated garments if thermal comfort cannot be achieved. The use of low pressure air for ventilating garments is proposed. The performance of such a system employing a small battery powered blower is defined in terms of the wearers work rate and supply air temperature and volume using the wetted surface area concept. The necessary steps to be taken by manufacturers if they are to develop the market for such conditioned garments are outlined.     

Using computer-based models for predicting human thermal responses to hot and cold environments

Four influential models, capable of predicting human responses to hot and cold environments and potentially suitable for use in practical applications, were evaluated by comparing their predictions with human data published previously. The models were versions of the Pierce Lab 2-node and Stolwijk and Hardy 25-node models of human thermoregulation, the Givoni and Goldman model of rectal temperature response, and ISO/DIS 7933. Experimental data were available for a wide range of environmental conditions, with air temperatures ranging from ?10 to 50°C, and with different levels of air movement, humidity, clothing and work. The experimental data were grouped into environment categories to allow examination of the effects of variables, such as wind or clothing, on the accuracy of the models' predictions. This categorization also enables advice to be given regarding which model is likely to provide the most accurate predictions for a particular combination of environmental conditions. Usually at least one of the models was able to give predictions with an accuracy comparable with the degree of variation that occurred within the data from the human subjects. The evaluation suggests that it is possible to make useful predictions of deep-body and mean skin temperature responses to cool, neutral, warm and hot environmental conditions. The models' predictions of deep-body temperature in the cold were poor. Overall, the 25-node model provided the most consistently accurate predictions. The 2-node model was often accurate but could be poor for exercise conditions. The rectal-temperature model usually overestimated deep-body temperature, although its predictions for very hot or heavy exercise conditions could be useful. The ISO model's allowable exposure times would not have protected subjects for some exercise conditions.     

A CAD system for multi-style thermal functional design of clothing

Designing clothing with good thermal functional performance is very demanding and time-consuming if we follow traditional design methods. An innovative method consisting of a CAD system, allowing the designer to perform multi-style clothing thermal functional design on a customized virtual human body, is presented in this paper. The new functionalities of the virtual system provide the abilities to perform intelligent design of different clothing styles and materials for different body parts according to individual design requirements, namely design of various categories of clothing, such as hat, coat, trousers, gloves and shoes in the same design scheme. The designed clothing can be worn on a virtual human body and set in various wearing scenarios. The thermal behaviors in the human body-clothing-environment are simulated to predict the thermal performance of clothing and thermal response of the human body at multi-parts. 2D/3D visualization and animation of the simulation results are presented to help the designers to preview and determine whether the thermal performance of clothing is satisfactory and then obtain feedback to improve their designs iteratively.     

The accuracy of estimating the thermal insulation of clothing ensembles - the effect of appraisers

The effect of the appraisers on the estimation of the thermal insulation of clothing ensembles was investigated. Nine appraisers, four experienced and five inexperienced, estimated the total thermal insulation by summing the values for individual garments. Lists of individual garments worn by workers were given during thermal comfort measurements carried out in shops and stores during one winter and summer. The beginners estimated the thermal insulation as accurately as the experienced appraisers. There were, however, great individual differences, for which three main reasons were found. Interpolation between the insulation provided by two garments was insufficient, and the insulation of these garments should be checked in more precise tables. Classification of the garments into heavy, medium and light clothing items was not adequate, and garments not listed by the workers confused the estimation given by different appraisers. The effect of error in thermal insulation on the PMV index is negligible if more than one appraiser estimates the thermal insulation and the mean of the estimates is used.     

A multi-disciplinary strategy for computer-aided clothing thermal engineering design

The designers and manufactures in apparel industry have urgent needs in designing clothing with superior thermal functions with user-friendly and cost-effective design tools. This paper presents a multi-disciplinary strategy for computer-aided clothing thermal engineering design. It provides a systematical approach to integrate multi-disciplinary knowledge and transfer it into engineering-oriented design tools, thus the designers and manufacturers can easily carry out 1D, 2D and even 3D clothing thermal engineering designs according to the practical design requirements with a short design cycle and low design cost. The research work of this strategy begins from the investigation of the role of the thermal functions of clothing in the thermal comfort of human body. Then the framework is proposed to integrate the multi-disciplinary knowledge and illustrate the process to achieve the thermal engineering design of clothing. The important issues in the realization of computational simulation are addressed, including multi-scale model integration, data availability of characteristic parameters and hierarchical computational scheme. To issue easy-to-use design tools, the thermal functional design of clothing is quantified with important influence parameters, and the user-friendly wizard is designed for the CAD system development. Finally, the design applications of this strategy are discussed in terms of 1D, 2D and 3D thermal engineering designs with versatile CAD systems.     

A fuzzy neural network model for predicting clothing thermal comfort

This paper presents a Fuzzy Neural Network (FNN) based local to overall thermal sensation model for prediction of clothing thermal function in functional textile design system. Unlike previous experimental and regression analysis approaches, this model depends on direct factors of human thermal response — body core and skin temperatures. First the local sensation is predicted by a FNN network using local body part skin temperatures, their change rates, and core temperature as inputs; then the overall sensation is predicted. This is also performed by a FNN network. The FNN networks are developed on the basis of the Feed-Forward Back-Propagation (FFBP) network; the advantage of using fuzzy logic here is to reduce the requirement of training data. The simulation result shows a good correlation between predicted and the traditional experimental data.     

Effects of moisture absorption in clothing on the human heat balance

A theory of moisture absorption in clothing, with the associated effects of heat transfer, was developed and applied in a computer model. The model considers the body, underclothing, an outer layer, and the adjacent air layer. The theory was checked with an experiment involving four subjects. They wore heavy woollen clothing, which was either initially dry or humid, in both a warm and a cool environment. Model calculations and experimental results agree approximately upon the timing and magnitude of the effect of absorbing clothing on heat flows, temperatures and physiological reactions. Contrary to expectations the observed vapour resistance is lower in the heat than in the cold, probably due to differences in sweat distribution. It is pointed out that the usual way to determine the clothing characteristics by means of partitional calorimetry leads to considerable errors when the steady state has not been reached. In clothing that has high absorption properties the transient effects may be sustained for hours. Tests using the model show few beneficial effects of absorbing clothing on thermal sensation.     

Perceptions of temperature,moisture and comfort in clothing during environmental transients

A study has been carried out to investigate the psychophysical mechanisms of the perception of temperature and moisture sensations in clothing during environmental transients. A series of wear trials was conducted to measure the psychological perception of thermal and moisture sensations and the simultaneous temperature and humidity at the skin surface, fabric surface and in the clothing under simulated moderate rain conditions. Jumpers made from wool and acrylic fibres were used in the trial. Analysis has been carried out to study the relationship between psychological perceptions of temperature and moisture and the objectively measured skin and fabric temperatures and relative humidity in clothing microclimate. The perception of warmth seems to follow Fechner's law and Stevens' power law, having positive relationships with the skin temperature and fabric temperatures. The perception of dampness appears to follow Fechner's law more closely than Stevens' power law with a negative relationship with skin temperature, and is nonlinearly and positively correlated with relative humidity in clothing microclimate. The perception of comfort is positively related to the perception of warmth and negatively to the perception of dampness. This perception of comfort is positively related to the skin temperature, which appears to follow both Fechner's law and Stevens' law, also non-linearly and negatively related to relative humidity in clothing microclimate.     

A quasi-physical model for predicting the thermal insulation and moisture vapour resistance of clothing

Based on the improved understanding of the effects of wind and walking motion on the thermal insulation and moisture vapour resistance of clothing induced by air ventilation in the clothing system, a new model has been derived based on fundamental mechanisms of heat and mass transfer, which include conduction, diffusion, radiation and natural convection, wind penetration and air ventilation. The model predicts thermal insulation of clothing under body movement and windy conditions from the thermal insulation of clothing measured when the person is standing in the still air. The effects of clothing characteristics such as fabric air permeability, garment style, garment fitting and construction have been considered in the model through the key prediction parameters. With the new model, an improved prediction accuracy is achieved with a percentage of fit being as high as 0.96.     

Comparative analysis of methods for determining the clothing surface temperature (tcl) in order to provide a balance between man and the environment

The PMV (Predicted Mean Vote) is an index which shows the thermal sensation of a large group of people exposed to the same environment. However, discrepancies are found between the PMV model and thermal sensation responses obtained in field studies. One of the components for the calculation of PMV is clothing surface temperature (t_cl), which can be a factor which contributes towards these discrepancies. Therefore, the aim of this article was to show t_cl influence on the PMV index. For this, the calculation of t_cl was done in two ways: the first was through the algorithm presented in the Annex D of ISO 7730 (2005) (Algorithm 1) and the second way was through Newton's Method (Algorithm 2), on a group of welders of a metal-mechanic industry. After calculating t_cl in these two ways, (algorithms 1 and 2), the two values obtained for t_cl were compared and the results were not the same. Consequently, different values for t_cl generate different results for the PMV. Newton's Method, having quadratic convergence, is more precise for the calculation; therefore, the suggestion is to use this method to determine t_cl since this is a variable with direct influence in determining the PMV.Relevancy to industryWhenever it is possible to determine the PMV and when this result is closer to people's responses to thermal sensation, one can provide a more appropriate environment to users in order to have Thermal Comfort and, principally, to avoid Thermal Stress.     

Pumping effects on thermal insulation of clothing worn by human subjects

This study was undertaken in order to analyse the importance of the pumping effect on clothing's thermal insulation. To enhance differences in heat exchanges due to the pumping effect, two sets of condition were fixed, minimizing either the convective or the radiative heat transfers. The results showed that: (i) the clothing insulation determined on a manikin, even if he is moving, is larger than the resultant clothing insulation for living subjects; (ii) the insulation is not the same for radiant heat or cold as for convective heat or cold;(iii) the pumping effect can increase or decrease the resultant clothing insulation; (iv) the clothing insulation is smaller in warmer conditions thanin cooler ones; (v) it becomes necessary to make a definite distinction between several kinds of clothing insulation; intrinsic or basic insulation against radiation and convection; effective insulation against radiation and convection taking into account only the heat flowing through the clothing fabric; resultant insulation taking into account the magnitude of the pumping effect when clothing is worn by living subjects     

Work tolerance and physiological responses to thermal environment wearing protective NBC clothing

Abstract

Six young, healthy male subjects performed a series of experiments in a climatic chamber in different environmental conditions wearing protective ventilated NBC clothing. Ambient temperature, TA, ranged from -20 to 35°C, relative humidity, RH, from 20 to 85%, and air velocity, VA, from 0·1 to 5·0 ms^?1. In addition, thermal radiation, measured by the temperature of the globothermometer, TG, was artificially increased in some experiments. A total of 32 experiments were performed. The subject had to exercise on a bicycle ergometer at a mechanical power of 60 W for 120 min. Heart rate, HR, oxygen uptake, VO₂, skin temperature, T_sk and rectal temperature, T_re, were measured during the experiments together with the temperature of the space between skin and garment, T_u. Sweat loss was determined as the difference of the body weight before and after the experiment. T_u was well correlated with the chamber environmental parameters. During heat exposure work duration began to decrease progressively from a T_u 30°C, reducing to 40 min at the highest thermal load. About the same value of T_u, marked the departure of HR, VO₂, T_sk and T_re from the values measured during the same work load in neutral conditions. Also, during cold exposure at -20°C work duration was reduced below 1 h, but the limit appeared to be the cold at the extremities. From these findings it appears that T_u is a good indicator of the thermal load and is related to the environmental condition by the equation: T_u = 9·93 + 0·56 TA + 0·023 TG + 0·14 RH (T in °C, RH in %. For better comfort and performance T_u should be monitored whenever a subject has to work wearing an NBC garment and the ventilating system must be adequate to fulfil the needs imposed on the subject by an adverse environment, in particular a high relative humidity.     

Data-efficient learning of robotic clothing assistance using Bayesian Gaussian process latent variable model

ABSTRACT

Motor-skill learning for complex robotic tasks is a challenging problem due to the high task variability. Robotic clothing assistance is one such challenging problem that can greatly improve the quality-of-life for the elderly and disabled. In this study, we propose a data-efficient representation to encode task-specific motor-skills of the robot using Bayesian nonparametric latent variable models. The effectivity of the proposed motor-skill representation is demonstrated in two ways: (1) through a real-time controller that can be used as a tool for learning from demonstration to impart novel skills to the robot and (2) by demonstrating that policy search reinforcement learning in such a task-specific latent space outperforms learning in the high-dimensional joint configuration space of the robot. We implement our proposed framework in a practical setting with a dual-arm robot performing clothing assistance tasks.