An Empirical Analysis of Thermal Protective Performance of Fabrics Used in Protective Clothing.

Fabric-based protective clothing is widely used for occupational safety of firefighters/industrial workers. The aim of this paper is to study thermal protective performance provided by fabric systems and to propose an effective model for predicting the thermal protective performance under various th...

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Publicado en:Annals of Occupational Hygiene Vol. 58; no. 8; pp. 1065 - 1078
Autores principales: Mandal, Sumit, Song, Guowen
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Oxford University Press / USA Oct2014
Acceso en línea:Ver este registro en EBSCOhost
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        atl: An Empirical Analysis of Thermal Protective Performance of Fabrics Used in Protective Clothing.
      aug:
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          Mandal, Sumit
          Song, Guowen
        affil: 1. Department of Human Ecology , University of Alberta , Human Ecology Building, Edmonton, Alberta T6G 2N1 , Canada
      sug:
        subj:
          Protective Devices
          Burns Prevention and Control
          Occupational Safety
          Heat Adverse Effects
          Textiles
          Human
          Descriptive Statistics
          Data Analysis Software
          Models, Statistical
          T-Tests
          Simulations
          Multiple Linear Regression
          Neural Networks (Computer)
          Funding Source
      ab: Fabric-based protective clothing is widely used for occupational safety of firefighters/industrial workers. The aim of this paper is to study thermal protective performance provided by fabric systems and to propose an effective model for predicting the thermal protective performance under various thermal exposures. Different fabric systems that are commonly used to manufacture thermal protective clothing were selected. Laboratory simulations of the various thermal exposures were created to evaluate the protective performance of the selected fabric systems in terms of time required to generate second-degree burns. Through the characterization of selected fabric systems in a particular thermal exposure, various factors affecting the performances were statistically analyzed. The key factors for a particular thermal exposure were recognized based on the t-test analysis. Using these key factors, the performance predictive multiple linear regression and artificial neural network (ANN) models were developed and compared. The identified best-fit ANN models provide a basic tool to study thermal protective performance of a fabric.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
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        Journal Article
      ougenre: Article
    language: English
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