Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao International Journa...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
International Journal of Hydrogen Energy
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
versions View all 1 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Investigation of two-phase flow in the compressed gas diffusion layer microstructures

Authors: Xia Zhou; Zhiqiang Niu; Yanan Li; Xiaoyan Sun; Qing Du; Jin Xuan; Kui Jiao;

Investigation of two-phase flow in the compressed gas diffusion layer microstructures

Abstract

Abstract This study aims to investigate how multiple parameters affect the two-phase flow in compressed gas diffusion layer (GDL). A stochastic model is adopted to reconstruct the GDL microstructures. Solid mechanics simulations on the reconstructed GDL microstructures are performed, based on the finite element method (FEM). Various pore morphologies and distributions of compressed GDLs are observed. Two-phase flow in GDL is simulated using a volume of fluid (VOF) model. Corner droplet (on the GDL surface) and water flow (emerging from GDL bottom) are considered. It is found that two-phase flow in the GDL is highly influenced by compression, fiber diameter, porosity, and GDL thickness. The results indicate that a larger fiber diameter or higher porosity contributes to the water transport due to larger average pore size. Furthermore, water removal from a thicker GDL is more difficult, whereas water transport in the lower part of a compressed thick GDL is easy.

Related Organizations
  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    48
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 10%
Top 10%
Top 1%