Material Thickness Design of Work Clothes in High Temperature Environment
- DOI
- 10.2991/978-94-6463-046-6_3How to use a DOI?
- Keywords
- Temperature Distribution; Fourier’s Law; Heat Conduction Equation; Genetic Algorithm
- Abstract
When working in high temperature environment, in order to prevent burns, workers need to wear special clothes composed of single-layer or multi-layer fabric materials. This paper aims to study the relationship between the thickness of each fabric layer and heat conduction. By establishing a mathematical model, the temperature distribution model and the optimal thickness of each fabric layer under different temperature conditions are obtained. The dummy is tested in the high-temperature environment. Through data fitting, the temperature distribution curve on the outside of the dummy’s skin in the high-temperature environment is obtained. The heat conduction model is established by Fourier heat conduction law and energy conservation, and the model is solved. Experiments show that the model is easy to solve and can effectively obtain the optimal thickness of each layer of special clothing.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xinwei Zhang AU - Yaxiong Li AU - Xinzhi Yang PY - 2022 DA - 2022/12/17 TI - Material Thickness Design of Work Clothes in High Temperature Environment BT - Proceedings of the 2022 2nd International Conference on Computer Technology and Media Convergence Design (CTMCD 2022) PB - Atlantis Press SP - 14 EP - 19 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-046-6_3 DO - 10.2991/978-94-6463-046-6_3 ID - Zhang2022 ER -