nan Udayraj

Effect of structural parameters on thermal protective performance and comfort characteristic of fabrics

Abstract In an attempt to understand the influence of basic structural parameters of fabrics on thermal protection and comfort, present study mainly focuses on analyzing effect of fabric weaving pattern and fabric weight. Fabric samples of three basic weaving patterns (plain, twill, and satin) and three different weights were prepared. Air permeability of the developed fabric samples was measured. Thermal protective performance of fabrics against radiant heat and flame exposures of two different intensities were measured. Spectral transmission behavior of fabrics was also studied. It was observed that for same fabric weight, protective performance and air permeability of satin woven fabrics were better as compared to the fabrics of other patterns. Protective performance increased and air permeability decreased as fabric weight increased for each type of woven structure included in this study. A new structural parameter is proposed which primarily influences the protective performance of fabrics exposed to either radiant heat, flame, or combined convective/radiant heat exposure.

Development of correlations and artificial neural network models to predict second-degree burn time for thermal-protective fabrics

Abstract Firefighters and operators working near industrial furnaces or ovens usually encounter extreme environmental conditions. Heat transfer through fabrics exposed to such high heat flux exposures causes skin burn. There are various parameters which govern heat transfer and second degree burn time in such situations. In this work, six dimensionless parameters associated with heat transfer through fabrics exposed to various flame and radiant heat flux exposures are obtained. Correlations for dimensionless second degree burn time are obtained in terms of other non-dimensional parameters. These separate correlations for each type of exposure can be used to obtain thermal protective performance (TPP) of any fabric exposed to different type of heat conditions, provided that fabric material, fabric geometric parameters, air gap between fabric and skin, and intensity of heat exposure are known. Artificial neural network (ANN) approach is also used to predict TPP of clothing. Multi-layer feed-forward back-propagation networks are developed for different type of exposures. Results shows that both correlations and ANN approach used in the study are promising. ANN model predictions are found to agree better with experimental observations as compared to the outcome of developed correlations. Importance of various dimensionless parameters obtained using dimensional analysis are also emphasized.

Design and Development of a Test Method for Analyzing Protective Performance of Gloves Exposed to Radiant Heat Based on Computational Fluid Dynamics Analysis

ABSTRACT Gloves are one of the most important items in the protective ensemble as they protect hand which is the most frequently burned body part. At present, no international standard or standardized test method is available for analyzing thermal protective performance of gloves exposed to purely radiant heat exposures. In the present work, a systematic approach for developing test setup for radiant heat exposure is proposed using computational fluid dynamics (CFD). A coupled CFD–radiation heat transfer model is first developed and validated with available experimental data. Effects of horizontal and vertical orientations of radiant heaters are then analyzed. Based on this study, an optimized configuration of the experimental setup which results in uniform heat flux distribution throughout the hand under lower level of radiant heat exposure is proposed. Furthermore, effects of different heater temperatures on heat flux distribution are studied. It is found that the proposed configuration works satisfactorily for other higher and lower heat flux levels as well.