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Computational simulation data using the Lattice Boltzmann method to generate correlations for gas diffusion layer parameters

Espinoza-Andaluz, Mayken LU ; Reyna, Raul ; Qi, Yuanxin LU ; Li, Tingshuai and Andersson, Martin LU (2019) In Data in Brief 27.
Abstract

Analyzing the fluid behavior in complex porous media like gas diffusion layers (GDLs) in polymer electrolyte fuel cells (PEFCs) can be accurately done using the lattice Boltzmann method (LBM). This article shows the data obtained from a study in which diffusion parameters such as porosity, gas phase tortuosity and diffusibility are computed considering simulated porous media [1]. The data were computed when a water drop obstacle is placed inside the GDL domain and the size of the water-drop is varied. Additionally, figures showing the evolution of the flow velocity field are presented alongside graphics that presents the change in local and bulk porosity for each obstacle size. Finally, there is a detailed method explanation concerning... (More)

Analyzing the fluid behavior in complex porous media like gas diffusion layers (GDLs) in polymer electrolyte fuel cells (PEFCs) can be accurately done using the lattice Boltzmann method (LBM). This article shows the data obtained from a study in which diffusion parameters such as porosity, gas phase tortuosity and diffusibility are computed considering simulated porous media [1]. The data were computed when a water drop obstacle is placed inside the GDL domain and the size of the water-drop is varied. Additionally, figures showing the evolution of the flow velocity field are presented alongside graphics that presents the change in local and bulk porosity for each obstacle size. Finally, there is a detailed method explanation concerning the implementation of the lattice Boltzmann method and a general description of computational codes for the domain and obstacle generation as well as the boundary conditions simulation. Data and processes in this article can be exploited in new attempts to solve real case problems in complex mesoscale media.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Diffusibility, Gas diffusion layer, Gas-phase tortuosity, PEFC, Water-droplet
in
Data in Brief
volume
27
article number
104688
publisher
Elsevier
external identifiers
  • pmid:31720338
  • scopus:85074129559
ISSN
2352-3409
DOI
10.1016/j.dib.2019.104688
language
English
LU publication?
yes
id
0b2abecc-37eb-420f-9b53-13554485b15e
date added to LUP
2019-11-05 10:58:23
date last changed
2020-02-05 03:00:34
@article{0b2abecc-37eb-420f-9b53-13554485b15e,
  abstract     = {<p>Analyzing the fluid behavior in complex porous media like gas diffusion layers (GDLs) in polymer electrolyte fuel cells (PEFCs) can be accurately done using the lattice Boltzmann method (LBM). This article shows the data obtained from a study in which diffusion parameters such as porosity, gas phase tortuosity and diffusibility are computed considering simulated porous media [1]. The data were computed when a water drop obstacle is placed inside the GDL domain and the size of the water-drop is varied. Additionally, figures showing the evolution of the flow velocity field are presented alongside graphics that presents the change in local and bulk porosity for each obstacle size. Finally, there is a detailed method explanation concerning the implementation of the lattice Boltzmann method and a general description of computational codes for the domain and obstacle generation as well as the boundary conditions simulation. Data and processes in this article can be exploited in new attempts to solve real case problems in complex mesoscale media.</p>},
  author       = {Espinoza-Andaluz, Mayken and Reyna, Raul and Qi, Yuanxin and Li, Tingshuai and Andersson, Martin},
  issn         = {2352-3409},
  language     = {eng},
  publisher    = {Elsevier},
  series       = {Data in Brief},
  title        = {Computational simulation data using the Lattice Boltzmann method to generate correlations for gas diffusion layer parameters},
  url          = {http://dx.doi.org/10.1016/j.dib.2019.104688},
  doi          = {10.1016/j.dib.2019.104688},
  volume       = {27},
  year         = {2019},
}