Studies of the Thermal Protective Performance of Textile Fabrics used in Firefighters’ Clothing under Various Thermal Exposures

• Author / Creator

  Mandal, Sumit

• This PhD study aims to thoroughly investigate the thermal protective performance of textile fabrics used in firefighters’ clothing under various thermal exposures. This study has two key objectives – firstly, to characterize the thermal protective performances of different fabrics under a comprehensive range of thermal exposures; secondly, to empirically analyze the thermal protective performance of these fabrics under the thermal exposures. To accomplish both the objectives, physical properties (e.g., thickness, air permeability) of multi-layered fabrics that are commonly used in firefighters’ clothing were measured; these multi-layered fabrics consisted different combinations of one type of shell fabric, three types of thermal liners, and one type of moisture barrier. Next, the thermal protective performances of these fabrics were evaluated in the Protective Clothing and Equipment Research Facility at the University of Alberta, Canada under the thermal exposures of flame, radiant heat, hot surface contact, steam, hot-water splash, and hot-water immersion with compression. The experimental data obtained were statistically analyzed to identify the effects of fabrics’ physical properties on the performance under these thermal exposures. Also, the performances provided by the fabrics were compared, and the nature of heat and mass transfer through the fabrics under these exposures was explored. Using the significant fabric properties that affected the performance, numerical Multiple Linear Regression (MLR) and Artificial Neural Networks (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 of the fabrics. The study demonstrates that the protective performance of textile fabrics varies with different types of thermal exposures. To provide effective protection in flame, radiant heat, and hot surface contact exposures, the most important fabric properties to address are thickness and thermal resistance. Steam and hot-water (splash and immersion with compression) exposures allow mass transfer through fabrics. In the presence of steam jet pressure or water, fabric thickness, air or water vapor permeability, and evaporative resistance are primary properties to consider in protecting the human body. In this study, it has been identified that ANN models can be effectively used in comparison to MLR models for predicting the thermal protective performance of fabrics under different thermal exposures. By analyzing the best fit ANN models, it is identified that different fabric properties play a key role in predicting thermal protective performance of fabrics under various thermal exposures. Overall, this PhD study will enhance our understanding of fabric materials used in firefighters’ clothing. This deeper understanding could be applied to engineer new test standards and fabric materials for clothing that can provide optimum occupational health and safety for firefighters.

• Subjects / Keywords

  • Firefighters' Clothing
  • Thermal Protective Performance
  • Thermal Protective Fabric Systems
  • Fabric Systems Properties
  • Empirical Analysis
  • Multiple Linear Regression
  • Artificial neural networks
  • Thermal Exposures
  • Burn Injury

• Graduation date

  Spring 2016

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R32B8VP1R

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.