Characterization and empirical analysis of hot water immersion with compression protective performance of fabrics used in firefighters’ clothing

Author:

Mandal Sumit1ORCID,Batcheller Jane2,Song Guowen3,Grover Indu Bala4

Affiliation:

1. Department of Design, Housing and Merchandising, Oklahoma State University, USA

2. Department of Human Ecology, University of Alberta, Canada

3. Department of Apparel, Events, and Hospitality Management, Iowa State University, USA

4. Department of Computer Engineering, YMCA Institute of Engineering, India

Abstract

This study aims to investigate hot water immersion with compression protective performance of textile fabrics used in firefighters’ clothing. This study has two key objectives – firstly, to characterize the protective performance of fabrics under different types of hot water immersion with compression exposures; secondly, to empirically analyze the protective performance of these fabrics under different exposures. To accomplish both the objectives, the physical properties (e.g., thickness, air permeability) of multi-layered fabrics that are commonly used in firefighters’ clothing were measured. Next, the protective performances of these fabrics were evaluated under different exposures. The experimental data obtained were statistically analyzed to identify the effects of the fabrics’ physical properties on the performance. Also, the performances provided by the fabrics were compared, and the nature of heat and mass transfer through the fabrics was explored. Using the significant fabric properties that affected the performance, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) modeling techniques were used to empirically predict the performance of the fabrics. The best prediction models were then employed for saliency testing to understand the relative importance of the significant fabric properties on the performance. The study demonstrates that the protective performance of textile fabrics varies with the exposures, depending upon the mass transfer through fabrics. In these exposures, fabric thickness, air or water-vapor permeability, and evaporative resistance are found to be the primary properties to consider in protecting the wearer. In this study, it has been identified that ANN models can be effectively used in comparison to MLR models for predicting the protective performance. By analyzing the best-fit ANN models, it is identified that different fabric properties play a key role in predicting the protective performance. Overall, this study would enhance the understanding of fabric materials used in firefighters’ clothing. This deeper understanding could be applied to engineer new test standards and fabric materials for clothing to provide optimum occupational health and safety for firefighters.

Publisher

SAGE Publications

Subject

Polymers and Plastics,Chemical Engineering (miscellaneous)

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