Clothing Evaporative Resistance: Its Measurements and Application in Prediction of Heat Strain

Clothing evaporative resistance is one of the most important inputs for both the modelling and for standards dealing with thermal comfort and heat stress. It might be determined on guarded hotplates, on sweating manikins or even on human subjects. Previous studies have demonstrated that the thermal manikin is the most ideal instrument for testing clothing evaporative resistance. However, the repeatability and reproducibility of manikin wet experiments are not very high for a number of reasons such as the use of different test protocols, manikins with different configurations, and different methods applied for calculation. The overall goals of the research presented were: (1) to examine experimental parameters that cause errors in evaporative resistance and to set up a well-defined test protocol to obtain repeatable data; and (2) to apply the reliable clothing evaporative resistance data obtained from manikin measurements and physiological data acquired from human trials to validate the Predicted Heat Strain (PHS) model (ISO 7933). Most of the calculations on clothing evaporative resistance up until now have been based on manikin temperature rather than fabric skin temperature because the fabric skin temperature was unknown. However, the calculated evaporative resistance has been overestimated because the fabric skin temperature is usually lower than the manikin temperature. This is mainly due to that water evaporation cooling down the fabric skin. In Paper I, the error of using manikin temperature instead of fabric skin temperature for evaporative resistance calculation was examined. In Paper II, a universal empirical equation was developed to predict wet skin temperature based on the total heat loss obtained from the manikin and the controlled manikin temperature. Paper III investigated discrepancy between the two options for the calculation of clothing evaporative resistance and how to select one of them for measurements conducted in a so called isothermal condition. Paper IV studied localised clothing evaporative resistance through an inter-laboratory study. The localised dynamic evaporative resistance caused by air and body movement was examined as well. In addition, reduction factor equations for localised evaporative resistance at each local segment were established. The thermophysiological responses of eight human subjects who wore five different vocational garments in various warm and hot environments were investigated (Paper V and Paper VI). The PHS model was validated by those human trials. Some suggestions on how to revise this model in order to achieve wider applicability were discussed and proposed. The results showed that the prevailing method for the calculation of evaporative resistance can generate an error of up to 35.9% on the boundary air layer’s evaporative resistance Rea. In contrast, it introduced an error of up to 23.7% to the clothing total evaporative resistance Ret. The error was dependent on the value of the clothing intrinsic evaporative resistance Recl. The isothermal condition is the most preferred test condition for measurements of clothing evaporative resistance; the isothermal mass loss method is always the correct option to calculate evaporative resistance. The reduction equations developed for localised clothing evaporative resistance have demonstrated that a total evaporative resistance value provided very limited information for local clothing properties and thus, localised values should be reported. The skin temperatures predicted by the PHS model were greatly overestimated in light clothing and high humidity environments (RH>80%). Similarly, the predicted core temperatures in protective clothing FIRE in warm and hot environments were also largely overestimated. The predicted evaporation rate was always much lower than the observed data. Therefore, a further revision of this model is required. This can be achieved by performing more human subject tests and applying more sensitive mathematical equations

Evaluation of the Performances of Electrically Heated Clothing

Cold weather garments are necessary for people who are exposed to cold environments (below -5 °C). The weight and bulkiness of such a cold weather clothing ensemble may limit human activity and reduce the productivity. In order to solve these problems, a slim garment with a built-in heating element could be useful. The heat input power and heating efficiency are the two most important parameters for a piece of heated clothing. The input power determines how much heat can be released from the whole clothing system, while the heating efficiency demonstrates how many percent of the thermal energy could effectively contribute to wearers. However, previous studies have mainly focused on heat input power and there is a lack of knowledge about the heating efficiency of the heated clothing. In this thesis, performances of electrically heated garments were compared and evaluated on two thermal manikins. The factors that affect on the clothing heating efficiency were thoroughly studied. It was found that the ambient temperature (or temperature gradient), air velocity and clothing combination can significantly influence the heating efficiency of a heated garment. In order to make good use of the thermal energy, the heating power should be well adjusted according to the environmental conditions. The heated clothing sandwiched between underwear and jacket in a three-layer clothing ensemble is one of the most effective ways to enhance the heating efficiency. In addition, the heated clothing alters the thermal evenness of clothing ensemble due to the heat release. This gives further evidence that the serial calculation method of clothing thermal resistance does not work for heterogeneous clothing ensembles

Characterization on pore size of honeycomb-patterned micro-porous PET fibers using image processing techniques

This Paper Presents a method to characterize the pore structure of the fibre surface for the honeycomb-patterned PET fibers; by using scanning electron microscopy (SEM) and image processing techniques. They consist of linear channel pores (LCP) and ellipse pores The surface pore distribution and micro pore numbers varied from each fiber to another, which can make significant differences on the. property of the spun yarns. It is proposed that the fiber should be sufficiently rinsed with clean water before dewatering and Setting processes, to eliminate the pore-clogging effect

Empirical Equations for Intrinsic and Effective Evaporative Resistances of Multi-layer Clothing Ensembles

To determine the intrinsic and effective clothing evaporative resistances,both in the individual clothing, and in the nulti-layer clothing ensembles meant for winter season, a fabric sweating thermal manikin Walter was used. Based on the tests performed on the individual garments, two empirical equations were developed for the estimation of these resistances, useful either to clothing manufacturers- to roughly estimate the clothing intrinsic/effective evaporative resistance, or to consumers-to assure them an optimal thermal comfort

Toward understanding predictability of climate: a linear stochastic modeling approach

This dissertation discusses the predictability of the atmosphere-ocean climate system on interannual and decadal timescales. We investigate the extent to which the atmospheric internal variability (weather noise) can cause climate prediction to lose skill; and we also look for the oceanic processes that contribute to the climate predictability via interaction with the atmosphere. First, we develop a framework for assessing the predictability of a linear stochastic system. Based on the information of deterministic dynamics and noise forcing, various predictability measures are defined and new predictability-analysis tools are introduced. For the sake of computational efficiency, we also discuss the formulation of a low-order model within the context of four reduction methods: modal, EOF, most predictable pattern, and balanced truncation. Subsequently, predictabilities of two specific physical systems are investigated within such framework. The first is a mixed layer model of SST with focus on the effect of oceanic advection.Analytical solution of a one-dimensional model shows that even though advection can give rise to a pair of low-frequency normal modes, no enhancement in the predictability is found in terms of domain averaged error variance. However, a Predictable Component Analysis (PrCA) shows that advection can play a role in redistributing the predictable variance. This analytical result is further tested in a more realistic two-dimensional North Atlantic model with observed mean currents. The second is a linear coupled model of tropical Atlantic atmosphere-ocean system. Eigen-analysis reveals that the system has two types of coupled modes: a decadal meridional mode and an interannual equatorial mode. The meridional mode, which manifests itself as a dipole pattern in SST, is controlled by thermodynamic feedback between wind, latent heat flux, and SST, and modified by ocean heat transport. The equatorial mode, which manifests itself as an SST anomaly in the eastern equatorial basin, is dominated by dynamic feedback between wind, thermocline, upwelling, and SST. The relative strength of thermodynamic vs dynamic feedbacks determines the behavior of the coupled system, and enables the tropical Atlantic variability to be more predictable than the passive-ocean scenario

Development of Empirical Equations to Predict Sweating Skin Surface Temperature for Thermal Manikins in Warm Environments.

Clothing evaporative resistance is one of the most important parameters for clothing comfort. The clothing evaporation resistance can be measured on a sweating guarded hotplate, a sweating thermal manikin or a human subject. The sweating thermal manikin gives the most accurate value on evaporative resistance of the whole garment ensemble compared to the other two methods. The determination of clothing evaporative resistance on a thermal manikin requires sweating simulation. This can be achieved by either a pre-wetted fabric skin on top of the manikin (TORE), or a waterproof but permeable Gore-tex skin filled with water inside. The addition of a fabric skin can introduce a temperature difference between the manikin surface and the sweating skin surface. However, calculations on clothing evaporative resistance have often been based on the thermal manikin surface temperature. A previous study showed that the temperature differences can cause an error up to 35.9 % on the clothing evaporative resistance. In order to reduce such an error, an empirical equation to predict the skin surface temperature might be helpful. In this study, a cotton knit fabric skin and a Gore-tex skin were used to simulate two types of sweating. The cotton fabric skin was rinsed with tap water and centrifuged in a washing machine for 4 seconds to ensure no water drip. A Gore-tex skin was put on top of the pre-wetted cotton skin on a dry heated thermal manikin ‘Tore’ in order to simulate senseless sweating, similar to thermal manikins ‘Coppelius’ and ‘Walter’. Another simulation involved the pre-wetted fabric skin covered on top of the Gore-tex skin in order to simulate sensible sweating. This type of sweating simulation can be widely found on many thermal manikins worldwide, e.g. ‘Newton’. Six temperature sensors (Sensirion Inc, Switzerland) were attached on six sites of the skin outer surface by white thread rings to record the skin surface temperature. Twelve skin tests for each skin combination were performed at three different ambient temperatures: 34, 25 and 20 oC. Two empirical equations to predict the skin surface temperature were developed based on the mean manikin surface temperature, mean fabric skin surface temperature and the total heat loss. The prediction equations for the senseless sweating and sensible sweating on the thermal manikin ‘Tore’ were Tsk=34.0-0.0146HL and Tsk=34.0-0.0190HL, respectively. Further study should validate these two empirical equations, however