Modeling for predicting the thermal protective and thermo-physiological comfort performance of fabrics used in firefighters' clothing

Abstract

Standardized test methods are available for measuring the thermal protective as well as thermo-physiological comfort Performance of fabrics used in firefighters' clothing. However, these tests are usually fabric destructive in nature, time consuming, and/or expensive to carry out on a regular basis. Hence, the availability of empirical models could be useful for conveniently predicting the thermal protective and thermo-physiological comfort performances from the fabric properties. The aim of this study is to develop individual models for predicting thermal protective and thermo-physiological comfort performances of fabrics. For this, different single- and multi-layered fabrics that are commercially used to manufacture firefighters' protective clothing were selected, and the fundamental properties of these fabrics (weight, thickness, thermal resistance, air-permeability, evaporative resistance, and water spreading speed) were measured using the standard test methods developed by the International Organization for Standardization (ISO) or the American Association of Textile Chemists and Colorists. The thermal protective performance of these fabrics was measured by the ISO 9151:2016 test method under 80 kW/m2 flame exposure. The thermo-physiological comfort performance of fabrics was determined by the ISO 18640-1:2018 test method and a statistical model. Thereafter, the key fabric properties affecting the thermal protective and thermo-physiological comfort performances of fabrics were determined statistically. It has been found that thermal and evaporative resistances are the key fabric properties to affect the thermal protective performance, whereas the fabric weight, evaporative resistance, and water spreading speed are the key properties to affect the thermo-physiological comfort performance. By employing these key fabric properties, Multiple Linear Regression and Artificial Neural Network (ANN) models were developed for predicting the thermal protective and thermo-physiological comfort performances. Through a comparison of the predicting performance parameters of these models, it has been found that ANN models can more accurately predict the performances of fabrics. These models can be implemented in the textile industry and academia for effectively and conveniently predicting the thermal protective and thermo-physiological comfort performances only by utilizing the key fabric properties.

Characterization and Modeling of Thermal Protective and Thermo-Physiological Comfort Performance of Polymeric Textile Materials—A Review

“…Recently, Mandal et al (2019) [ 61 ] evaluated the thermo-physiological comfort performance of wide range of fabrics used in workwear. In this study, ISO 18640-1:2018 and ISO 18640-2:2018 standards were used to evaluate the thermo-physiological comfort performance of fabrics in terms of time required to generate heat stress on wearers’ bodies.…”

“…In this study, it has been found that fabric weight, water spreading speed, and evaporative resistance are the significant properties to affect the thermo-physiological comfort performance of fabrics. By using these properties, Mandal et al (2019) [ 61 ] also developed the MLR and ANN models for predicting the thermo-physiological comfort performance of fabrics; it has been found that ANN model could perform better for predicting the thermo-physiological comfort performance of fabrics.…”

“…This kind of tool could help in finding the best balance between these two performances, which could guide workwear manufacture to select an appropriate fabric for the workwear based on their requirements for end uses. Considering this, recently Mandal et al (2019) [ 61 ] conducted a study on categorizing the fabrics based on their thermal protective and thermo-physiological comfort performances. However, in this study, the categorization tool was developed mainly based on the thermal protective and thermo-physiological comfort performances values of dry fabrics without any consideration of the air gaps.…”

“…However, these tests are fabric destructive in nature, time consuming, and/or expensive to carry out on a regular basis [ 23 , 24 , 25 ]. As a result, previous studies have focused on characterizing and developing empirical models to predict the protective and comfort performance based on physical properties of the fabrics [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ]. For this, first, significant fabrics’ properties that affect the protective and comfort performance of fabrics were identified.…”

Influential Parameters of Starching Process on Mechanical Properties of Yarns Intended for Multifunctional Woven Fabrics for Thermal Protective Clothing

“…It is becoming more demanding, complex and difficult to achieve certain material properties, prescribed by standards for a particular purpose, and it is even more difficult to achieve the sustainability during use. Therefore, finishing processes (surface treatments and layering) are conducted on the material, which simultaneously affect the property of breathability, resulting in the insufficient material comfort [ 3 , 4 , 5 , 6 , 7 ].…”