Three-Dimensional Lattice Boltzmann Simulation of Liquid Water Transport in Porous Layer of PEMFC

Han, Bo; Ni, Meng; Meng, Hua

doi:10.3390/e18010017

Cited by 24 publications

(12 citation statements)

References 38 publications

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“…The LBM consists of two main steps: collision and streaming. The evolution of the distribution function f a ( x , t ) is as follows:

f_{a} ((),, boldx + e_{a} normalΔ t, t + Δt) - f_{a} ((),, x, t) = - \frac{Δt}{T_{r}} ((), f_{a} ((),, x, t) - f_{a}^{eq} ((),, x, t))

…”

Section: Methodologiesmentioning

confidence: 99%

“… T r represents the relaxation time required to achieve the equilibrium distribution

f_{a}^{eq}

. A collision operator denotes the collision as a relaxation of the density distribution function toward the Maxwell‐Boltzmann equilibrium distribution function . In the D3Q19 scheme, the collision operator

f_{a}^{eq}

is the Maxwellian distribution function, which is expressed as

f_{a}^{eq} ((),, x, t) = ω_{a} ρ ((),, x, t) ([], 1 + \frac{e_{a} u^{eq}}{{c_{s}}^{2}} + \frac{e_{a} u^{eq}}{2 {c_{s}}^{4}} - \frac{{((), {boldu}^{eq})}^{2}}{2 {c_{s}}^{2}})

where ω a is the weighting associated with the velocity e a , and it is defined for 19 components as follows:

ω_{a} = ({, \begin{array}{l} 1 / 3 a = 0 \\ 1 / 18 a = 1, 2, \dots, 6 \\ 1 / 36 a = 7, 8, \dots, 18 \end{array})

where c s is the lattice sound velocity, which is equal to

1 / \sqrt{3}

for the D3Q19 model.…”

Section: Methodologiesmentioning

confidence: 99%

“…The LBM consists of two main steps: collision and streaming. The evolution of the distribution function f a (x, t) is as follows 39 :…”

Section: Lattice Boltzmann Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Interfacial transport characteristics between heterogeneous porous composite media for effective mass transfer in fuel cells

Liu

Shin

2019

Int J Energy Res

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Summary In this study, a comprehensive computational model based on a full statistical approach was developed to investigate the heterogeneous mass transport properties in the metal foam channels, gas diffusion layers (GDLs), and microporous layers (MPLs) of polymer electrolyte fuel cells (PEFCs) at the 95% confidence level. A series of channels, GDLs, and MPLs were, respectively, generated to reflect the random heterogeneous structures and transport characteristics. The critical hydrophobic pore radius in the mixed wettability GDLs was computed by applying a modified Leverett function. Furthermore, the gas transport phenomenon through a sufficient number of porous transport media was simulated using a D3Q19 (ie, three‐dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics were mathematically presented as a function of the porosity. The permeabilities in the channels, GDLs, and MPLs were derived from the pressure gradient and the simulated velocity distribution. It was found that the effective mass diffusion coefficient in the GDLs is mainly influenced by molecular diffusion. Nevertheless, Knudsen diffusion is the dominant mass transfer mechanism in the MPLs, because of small pore diameters. In addition, critical hydrophobic pore radius was derived using a modified Leverett function, which enables to estimate the fraction of pores larger than the critical pore radius in GDLs for effective water transport. Moreover, the interfacial areal contact ratio between two adjacent porous media (ie, channel/GDL and GDL/MPL) was calculated. The calculations indicated that the variation in the local porosity of the porous media has a significant influence on the interfacial connections. The proposed model is expected to improve the prediction performance of porous heterogeneous transport media in electrochemical energy systems and the optimization of porous media structures.

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“…The LBM consists of two main steps: collision and streaming. The evolution of the distribution function f a ( x , t ) is as follows:

f_{a} ((),, boldx + e_{a} normalΔ t, t + Δt) - f_{a} ((),, x, t) = - \frac{Δt}{T_{r}} ((), f_{a} ((),, x, t) - f_{a}^{eq} ((),, x, t))

…”

Section: Methodologiesmentioning

confidence: 99%

“… T r represents the relaxation time required to achieve the equilibrium distribution

f_{a}^{eq}

f_{a}^{eq}

is the Maxwellian distribution function, which is expressed as

f_{a}^{eq} ((),, x, t) = ω_{a} ρ ((),, x, t) ([], 1 + \frac{e_{a} u^{eq}}{{c_{s}}^{2}} + \frac{e_{a} u^{eq}}{2 {c_{s}}^{4}} - \frac{{((), {boldu}^{eq})}^{2}}{2 {c_{s}}^{2}})

where ω a is the weighting associated with the velocity e a , and it is defined for 19 components as follows:

ω_{a} = ({, \begin{array}{l} 1 / 3 a = 0 \\ 1 / 18 a = 1, 2, \dots, 6 \\ 1 / 36 a = 7, 8, \dots, 18 \end{array})

where c s is the lattice sound velocity, which is equal to

1 / \sqrt{3}

for the D3Q19 model.…”

Section: Methodologiesmentioning

confidence: 99%

See 1 more Smart Citation

Interfacial transport characteristics between heterogeneous porous composite media for effective mass transfer in fuel cells

Liu

Shin

2019

Int J Energy Res

View full text Add to dashboard Cite

show abstract

“…The direct numerical simulation method, computationally demanding but solving all the turbulent scales, has been recently used together with VOF to capture the detailed turbulent two‐phase flow in channel . To more accurately capture the droplet dynamics at pore scale, lattice boltzmann method (LBM) is effective, thus it is employed for multiphase flow simulation in the nanostructured CL . Based on the single relaxation time Bhatnagar‐Gross‐Krook evolution and Shan‐Chan model, the LBM model could capture the dynamics of water transport in the porous electrodes of PEMFC.…”

mentioning

confidence: 99%

“…6,7 To more accurately capture the droplet dynamics at pore scale, lattice boltzmann method (LBM) is effective, thus it is employed for multiphase flow simulation in the nanostructured CL. 8 Based on the single relaxation time Bhatnagar-Gross-Krook evolution and Shan-Chan model, the LBM model could capture the dynamics of water transport in the porous electrodes of PEMFC. It is found that the liquid water transport is strongly affected by the microstructure of the porous layer and the liquid water tends to flow through the large pores.…”

mentioning

confidence: 99%

Challenges and opportunities in modelling of proton exchange membrane fuel cells (PEMFC)

Jiao

2017

Int. J. Energy Res.

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A comprehensive review of the modeling of transport phenomenon in the flow channels of polymer electrolyte membrane fuel cells

Olukayode,

Ye,

et al. 2024

Front. Chem. Sci. Eng.

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Three-Dimensional Lattice Boltzmann Simulation of Liquid Water Transport in Porous Layer of PEMFC

Cited by 24 publications

References 38 publications

Interfacial transport characteristics between heterogeneous porous composite media for effective mass transfer in fuel cells

Interfacial transport characteristics between heterogeneous porous composite media for effective mass transfer in fuel cells

Challenges and opportunities in modelling of proton exchange membrane fuel cells (PEMFC)

A comprehensive review of the modeling of transport phenomenon in the flow channels of polymer electrolyte membrane fuel cells

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