Advertisement

Computer Simulation of Multi-phase Coupled Heat and Moisture Transfer in Clothing Assembly with a Phase Change Material in a Cold Environment

  • Shuxiao Wang
  • Yi Li
  • Hiromi Tokura
  • J. Y. Hu
  • Aihua Mao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3942)

Abstract

This paper describes a simulation of the physical processes of coupled heat and moisture transfer in a clothing assembly containing phase change material (PCM). This paper focuses on the analysis of the effect of the PCM. The results of simulation show that the PCM can delay the decrease in temperature of the clothing. The experiment results are also shown in this paper. A reasonable agreement was found when comparing the results of the simulation with the experiment results.

Keywords

Phase Change Material Cold Environment Moisture Transfer Thermal Energy Storage Sonable Agreement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bryant, Y.G., Colvin, D.P.: Fibers with enhanced, Reversible Thermal Energy Storage Properties. In: Techtextile Symposium, pp. 1–8 (1992)Google Scholar
  2. 2.
    Li, Y., Zhu, Q.: A model of coupled liquid moisture and heat transfer in porous textiles with consideration of gravity. Numerical Heat Transfer 43(5), 501–523 (2003)CrossRefGoogle Scholar
  3. 3.
    Li, Y., Hu, J., Wang, S., Yeung, K.W.: An Apparatus for Measurement of Infrared Radiation Properties of Textiles, in China patent, filing No: 200410068752.8 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shuxiao Wang
    • 1
  • Yi Li
    • 1
  • Hiromi Tokura
    • 1
  • J. Y. Hu
    • 1
  • Aihua Mao
    • 1
  1. 1.Institute of Textiles and ClothingHong Kong Polytechnic University, Hung Hom, KowloonHong Kong

Personalised recommendations