Development of an ‘artificial human’ for clothing research

The clothing is the closest envelope of the human body, and hence, has the primary im-pact on thermal comfort, physiological response of the human body and environmental strain. On the other hand, the clothing microenvironment is affected by physiological reactions (sweating, temperature distribution, body movement). Nowadays, thermal sweating manikins used to study the interactions of the body-clothing-environment system are unable to simulate adequately the spatial and transient thermal behaviour of the human body. Ideally, a human simulator should ‘feel’ and re-spond dynamically to the thermal environment as real humans do. In this work thermal sweating devices were coupled with the iesd-Fiala multi-node model of human physiology and thermal comfort. The coupling procedure was first de-veloped for the iesd-Fiala model and a single-sector cylinder Torso. A new single-sector thermophysiological human simulator reproduced adequately the overall physiological response of the average human, which was proved by comparison with results of human subject tests for a wide range of environmental conditions. In the next step, the elaborated coupling method was applied to the multi-sector, ana-tomically-shaped thermal sweating manikin SAM. The multi-sector thermophysiologi-cal human simulator with homogenous surface temperature distribution reproduced the thermal behaviour observed in human subject tests with good accuracy. However, an attempt to advance this human simulator to one with a heterogeneously distributed sur-face temperature was unsuccessful, as the results predicted by the simulator differed greatly from those obtained from human subject tests. The single-sector physiological simulator has been shown to perform well in the valida-tion tests with use of clothing ensembles. Time saving testing, repeatability of the measurement of the physiological response of an average individual and the ability of testing in conditions unsafe for humans are major advantages of this human simulator.Swiss National Science Foundation W. L. Gore & Associate

Determination of the local evaporative resistances of two typical office clothing ensembles and the effect of air speed and body movement

Peer-reviewed extended abstract submitted to 12i3m, 29-30 September 2018, St. Gallen, Switzerlan

Comfort limit and heat protection properties of single layer cotton/nylon-Kermel blended fabrics

Fire and heat protection and thermal comfort properties of cotton/nylon-Kermel blended fabrics have been studied to predict thermal comfort and protection limit of this fabric structure. The results indicate that the cotton/nylon blended with Kermel fabrics, particularly with 30% Kermel fibres, exhibits the highest upper thermal comfort limit and also the widest range of fabric metabolic activity level. The obtained result indicates that all the sample fabrics consisting of 50% cotton fibres have close drying times. The result also shows that the increase in Kermel fibres ratio in blended fabrics has a pronounced effect on prevention of fire diffusion. An increase of Kermel fibres have significant effect on radiant protective performance of fabric samples. The results of vertical wicking and MMT tests show that the addition of Kermel fibres up to 10% significantly detracts these thermal comfort properties. However, the increase of Kermel fibres ratio from 10% to 100% have no significant effect on wicking as well as moisture management properties. The study shows that the blending of Kermel fibre at 30% blend ratio with cotton and nylon enhances thermal comfort limit and heat protection of blended fabrics

Heat flux measurements for use in physiological and clothing research

Scientists use passive heat flow meters to measure body heat exchanges with the environment. In recent years, several such sensors have been developed and concerns about their proper calibration have been addressed. However, calibration methods have differed in the geometry of the heated device as well as in the heat transfer mechanism. Therefore, a comparison of calibration methods is needed in order to understand the obtained differences in calibration lines. We chose three commercially available heat flux sensors and placed them on four different heated devices: a hot plate, double hot plate, nude cylinder and a cylinder covered with a spacer material. We found differences between the calibration line of the manufacturer and our own measurements, especially when forced convection was involved as the main heat transfer mechanism. The results showed clearly that the calibration method should be chosen according to the intended purpose of use. In addition, we recommend use a thin, light heat flux sensor with good thermal conduction in human subject studies

Effect of ambient temperature and attachment method on surface temperature measurements

Accurate measurement of skin surface temperature is essential in both thermo-physiological and clinical applications. However, a literature review of the last two decades of physiological or clinical research revealed an inconsistency or a lack of information on how temperature sensors were attached to the skin surface. The purpose of this study was to systematically compare and quantify the performance of different commercially available temperature sensors and their typical attachment methods, and, secondly, to provide a time-efficient and reliable method for testing any sensor-tape combination. In conclusion, both the sensor type and the attachment method influenced the results of temperature measurements (both its absolute and relative dimensions). The sensor shape and the contact of its sensing area to the surface, as well as the conductance of the tape were the most important parameters to minimise the influence of environmental conditions on surface temperature measurement. These results suggest that temperature sensors and attachment methods for human subject and manikin trials should be selected carefully, with a systematic evaluation of the sensor-tape system under conditions of use, and emphasise the need to report these parameters in publications

Human responses in heat – comparison of the Predicted Heat Strain and the Fiala multi-node model for a case of intermittent work

Two mathematical models of human thermal regulation include the rational Predicted Heat Strain (PHS) and the thermophysiological model by Fiala. The approaches of the models are different, however, they both aim at providing predictions of the thermophysiological responses to thermal environments of an average person. The aim of this study was to compare and analyze predictions of the two models against experimental data. The analysis also includes a gender comparison. The experimental data comprised of ten participants (5 males, 5 females, average anthropometric values were used as input) conducting an intermittent protocol of rotating tasks (cycling, stacking, stepping and arm crank) of moderate metabolic activities (134-291 W/m2) with breaks in-between in a controlled environmental condition (34°C, 60% RH). The validation consisted of the predictions’ comparison against experimental data from 2.5 hours of data of rectal temperature and mean skin temperature based on contact thermometry from four body locations. The PHS model over-predicted rectal temperatures during the first activity for males and the cooling effectiveness of sweat in the recovery periods, for both males and females. As a result, the PHS simulation underestimated the thermal strain in this context. The Fiala model accurately predicted the rectal temperature throughout the exposure. The fluctuation of the experimental mean skin temperature was not reflected in any of the models. However, the PHS simulation model showed better agreement than the Fiala model. As both models predicted responses more accurately for males than females, we suggest that in future development of the models it is important to take this result into account. The paper further discusses possible sources of the observed discrepancies and concludes with some suggestions for modifications

Validation of the Fiala multi-node thermophysiological model for UTCI application

The important requirement that COST Action 730 demanded of the physiological model to be used for the Universal Thermal Climate Index (UTCI) was its capability of accurate simulation of human thermophysiological responses across a wide range of relevant environmental conditions, such as conditions corresponding to the selection of all habitable climates and their seasonal changes, and transient conditions representing the temporal variation of outdoor conditions. In the first part of this study, available heat budget/two-node models and multi-node thermophysiological models were evaluated by direct comparison over a wide spectrum of climatic conditions. The UTCI-Fiala model predicted most reliably the average human thermal response, as shown by least deviations from physiologically plausible responses when compared to other models. In the second part of the study, this model was subjected to extensive validation using the results of human subject experiments for a range of relevant (steady-state and transient) environmental conditions. The UTCI-Fiala multi-node model proved its ability to predict adequately the human physiological response for a variety of moderate and extreme conditions represented in the COST 730 database. The mean skin and core temperatures were predicted with average root-mean-square deviations of 1.35 ± 1.00°C and 0.32 ± 0.20°C, respectivel

An introduction to the Universal Thermal Climate Index (UTCI)

The assessment of the thermal environment is one ofthe main issues in bioclimatic research, and more than 100 simple bioclimatic indices have thus far been developed to facilitate it. However, most of these indices have proved to be of limited applicability, and do not portroy the actual impacts of thermal conditions on human beings. Indices derived from human heatbalance models (one- or two-node) have been found to offer a better representation of the environmental impact in question than do simple ones. Indeed, the new generation of multi-node models for human heat balance do allow full account to be taken of heat transfer and exchange, both within the human body and between the body surface and the surrounding air layer. In this paper, it is essential background information regarding the newly-developed Universal Thermal Climate Index UTCI that is presented, this in fact deriving from the Fiala multi-node model of human heatbalance. The UTCI is defined as the air temperature (Ta) of the reference condition causing the same model response as actual conditions. UTCI was developed in 2009 by virtue of international co-operation between leading experts in the areas of human thermophysiology, physiological modelling, meteorology and climatology. The necessary research for this had been conducted within the framework of a special commission of the International Society of Biometeorology (ISB) and European COST Action 730

Prediction of human core body temperature using non-invasive measurement methods

The measurement of core body temperature is an efficient method for monitoring heat stress amongst workers in hot conditions. However, invasive measurement of core body temperature (e.g. rectal, intestinal, oesophageal temperature) is impractical for such applications. Therefore, the aim of this study was to define relevant non-invasive measures to predict core body temperature under various conditions. We conducted two human subject studies with different experimental protocols, different environmental temperatures (10°C, 30°C) and different subjects. In both studies the same non-invasive measurement methods (skin temperature, skin heat flux, heart rate) were applied. A principle component analysis was conducted to extract independent factors, which were then used in a linear regression model. We identified six parameters (three skin temperatures, two skin heat fluxes and heart rate), which were included for the calculation of two factors. The predictive value of these factors for core body temperature was evaluated by a multiple regression analysis. The calculated root mean square deviation (rmsd) was in the range from 0.28°C to 0.34°C for all environmental conditions. These errors are similar to previous models using non-invasive measures to predict core body temperature. The results from this study illustrate that multiple physiological parameters (e.g. skin temperature and skin heat fluxes) are needed to predict core body temperature. In addition, the physiological measurements chosen in this study and the algorithm defined in this work are potentially applicable as real-time core body temperature monitoring to assess health risk in broad range of working conditions