Virtual Liquid Water Intrusion in Fuel Cell Gas Diffusion Media
Source abstract
Abstract
A cluster based full morphology (CFM) model is developed to predict liquid water intrusion in GDLs. The CFM model is used to simulate water intrusion into a dry GDL microstructure obtained from μ-CT. Numerical water saturation distributions are compared to experimental μ-CT reconstructions of the same GDL sample at varying saturation levels. A quantitative validation of the CFM model results is then provided by studying the number of voxels in the image that contain water in both the CFM model results and the μ-CT reconstructions. Results reveal that CFM simulations showed 56–95.7% agreement in the liquid water voxels when compared to the μ-CT simulations for saturations in the range of 29–92.3%. Gas transport simulations are then performed on μ-CT and CFM partially saturated GDLs in order to study the validity of the CFM model images to estimate transport properties of partially saturated GDLs. A maximum error of 20% was observed between the predicted effective diffusivities obtained from CFM simulations and those obtained directly from simulations on the μ-CT data for saturations below 40%. Effective diffusivity predictions from the CFM simulations agree well with in-plane effective diffusivities in literature while the through-plane effective diffusivities were underpredicted by a factor of 2.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Fuel Cells and Related Materials · Lattice Boltzmann Simulation Studies · Nanopore and Nanochannel Transport Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (82)
Show source-provided references
1. Hartnig C. Jörissen L. Kerres J. Lehnert W. Scholta J. , Polymer electrolyte membrane fuel cells, Materials for fuel cells. 1st ed. Boca Raton, Boston, New York, Washington DC: CRC Press & Cambridge: Woodhead Publishing Ltd, 101–84 (2008).10.1533/9781845694838.101 ↗
2. Gallart M. Secanell , Computational modeling and optimization of proton exchange membrane fuel cells, Ph.D. thesis (2007).10.1016/j.electacta.2006.09.049 ↗
3. 10.1016/j.electacta.2007.06.06110.1016/j.electacta.2007.06.061 ↗
4. 10.1016/j.electacta.2009.06.06610.1016/j.electacta.2009.06.066 ↗
5. 10.1088/0953-8984/2/S/00810.1088/0953-8984/2/S/008 ↗
6. 10.1017/S002211208800095310.1017/S0022112088000953 ↗
7. 10.1016/j.jpowsour.2009.04.05210.1016/j.jpowsour.2009.04.052 ↗
8. 10.1016/j.jpowsour.2006.06.09610.1016/j.jpowsour.2006.06.096 ↗
9. 10.1016/j.jpowsour.2009.08.03210.1016/j.jpowsour.2009.08.032 ↗
10. 10.1016/j.jpowsour.2015.07.03410.1016/j.jpowsour.2015.07.034 ↗
11. 10.1016/j.ijhydene.2011.01.03610.1016/j.ijhydene.2011.01.036 ↗
12. 10.1016/j.ces.2009.09.04410.1016/j.ces.2009.09.044 ↗
13. 10.1149/06403.0487ecst10.1149/06403.0487ecst ↗
14. 10.1016/j.electacta.2015.03.10010.1016/j.electacta.2015.03.100 ↗
15. 10.1016/j.jelechem.2007.09.01410.1016/j.jelechem.2007.09.014 ↗
16. 10.1016/j.electacta.2011.12.11010.1016/j.electacta.2011.12.110 ↗
17. 10.1007/s11242-016-0648-410.1007/s11242-016-0648-4 ↗
18. 10.1149/2.024211jes10.1149/2.024211jes ↗
19. 10.1016/j.ijheatmasstransfer.2014.05.00510.1016/j.ijheatmasstransfer.2014.05.005 ↗
20. 10.1016/j.ijheatmasstransfer.2017.02.09610.1016/j.ijheatmasstransfer.2017.02.096 ↗
21. 10.1115/1.321109610.1115/1.3211096 ↗
22. 10.1115/1.282160010.1115/1.2821600 ↗
23. 10.1149/1.317687610.1149/1.3176876 ↗
24. 10.1016/j.jpowsour.2013.06.10010.1016/j.jpowsour.2013.06.100 ↗
25. 10.1016/j.ijhydene.2012.08.07710.1016/j.ijhydene.2012.08.077 ↗
26. 10.1016/j.jpowsour.2015.01.11110.1016/j.jpowsour.2015.01.111 ↗
27. 10.1016/j.jpowsour.2016.08.02010.1016/j.jpowsour.2016.08.020 ↗
28. 10.1016/j.elecom.2015.02.00510.1016/j.elecom.2015.02.005 ↗
29. 10.1016/j.electacta.2010.12.01610.1016/j.electacta.2010.12.016 ↗
30. 10.1016/j.ijheatmasstransfer.2015.02.07310.1016/j.ijheatmasstransfer.2015.02.073 ↗
31. Shum A. D. Parkinson D. Y. Xiao X. Weber A. Z. Burheim O. S. Zenyuk I. V. , “Investigating phase-change-induced flow in gas diffusion layers in fuel cells with X-ray computed tomography,” Electrochimica Acta.
32. 10.1021/acs.jpcc.6b1065810.1021/acs.jpcc.6b10658 ↗
33. 10.1039/b703485g10.1039/b703485g ↗
34. 10.1149/1.348609510.1149/1.3486095 ↗
35. 10.1016/j.electacta.2016.08.12610.1016/j.electacta.2016.08.126 ↗
36. 10.1149/2.009308jes10.1149/2.009308jes ↗
37. 10.1016/j.jpowsour.2007.04.05910.1016/j.jpowsour.2007.04.059 ↗
38. 10.1016/j.ijhydene.2010.06.05110.1016/j.ijhydene.2010.06.051 ↗
39. 10.1016/j.ijhydene.2010.04.12610.1016/j.ijhydene.2010.04.126 ↗
40. 10.1149/1.349135910.1149/1.3491359 ↗
41. 10.1016/j.jpowsour.2009.11.12510.1016/j.jpowsour.2009.11.125 ↗
42. 10.4208/cicp.311009.081110s10.4208/cicp.311009.081110s ↗
43. 10.1016/j.jpowsour.2014.12.04410.1016/j.jpowsour.2014.12.044 ↗
44. 10.1016/j.jpowsour.2007.09.02910.1016/j.jpowsour.2007.09.029 ↗
45. 10.1016/j.jpowsour.2016.10.09810.1016/j.jpowsour.2016.10.098 ↗
46. 10.1149/1.247254710.1149/1.2472547 ↗
47. 10.1016/j.ijhydene.2011.01.14610.1016/j.ijhydene.2011.01.146 ↗
48. 10.1149/2.0191507jes10.1149/2.0191507jes ↗
49. 10.1103/PhysRevE.96.02330710.1103/PhysRevE.96.023307 ↗
50. 10.1016/j.ijhydene.2015.08.00910.1016/j.ijhydene.2015.08.009 ↗
51. 10.1002/fuce.20150021310.1002/fuce.201500213 ↗
52. 10.1016/j.ijhydene.2014.08.02710.1016/j.ijhydene.2014.08.027 ↗
53. 10.1007/s11242-014-0422-410.1007/s11242-014-0422-4 ↗
54. 10.1002/fld.419010.1002/fld.4190 ↗
55. Jarauta A. Ryzhakov P. , “Challenges in computational modeling of two-phase transport in polymer electrolyte fuel cells flow channels: A review, Archives of Computational Methods in Engineering,” 1 (2017).10.1007/s11831-017-9243-2 ↗
56. 10.1002/nme.435710.1002/nme.4357 ↗
57. 10.1016/j.jpowsour.2007.10.06610.1016/j.jpowsour.2007.10.066 ↗
58. 10.1016/j.ijhydene.2010.04.05210.1016/j.ijhydene.2010.04.052 ↗
59. 10.1016/j.jcis.2006.04.02110.1016/j.jcis.2006.04.021 ↗
60. 10.2136/vzj2004.011410.2136/vzj2004.0114 ↗
61. Kim F. H. Penumadu D. Schulz V. P. Schmirler R. Krauβ P. , “Lattice boltzmann simulation of two phase flow through porous media and verification using high resolution X-ray and neutron tomography data,” in: Poromechanics V: Proceedings of the Fifth Biot Conference on Poromechanics, pp. 2334–2343, 2013.10.1061/9780784412992.273 ↗
62. 10.1016/j.jpowsour.2016.09.07610.1016/j.jpowsour.2016.09.076 ↗
63. 10.1016/j.electacta.2010.07.01810.1016/j.electacta.2010.07.018 ↗
64. 10.1002/fuce.20100011610.1002/fuce.201000116 ↗
65. 10.1016/j.ijhydene.2014.03.07410.1016/j.ijhydene.2014.03.074 ↗
66. 10.1016/j.jpowsour.2008.09.08610.1016/j.jpowsour.2008.09.086 ↗
67. 10.1016/j.memsci.2010.01.03110.1016/j.memsci.2010.01.031 ↗
68. 10.1016/j.ces.2009.12.01910.1016/j.ces.2009.12.019 ↗
69. 10.1016/j.electacta.2013.04.07110.1016/j.electacta.2013.04.071 ↗
70. 10.1016/j.ijheatmasstransfer.2010.12.00310.1016/j.ijheatmasstransfer.2010.12.003 ↗
71. Moosavi S. M. Niffeler M. Gostick J. Haussener S. , Transport characteristics of saturated gas diffusion layers treated with hydrophobic coatings, Chemical Engineering Science.
72. 10.1149/06403.0655ecst10.1149/06403.0655ecst ↗
73. 10.1002/fuce.20160000810.1002/fuce.201600008 ↗
74. Pant L. M. , Stochastic characterization and reconstruction of porous media, Ph.D. thesis, University of Alberta (2016). URL http://hdl.handle.net/10402/era.42583
75. Bird R. B. Stewart W. E. Lightfoot E. N. , Transport phenomena john wiley & sons, New York (1960) 413.
76. 10.1515/jnma-2016-104510.1515/jnma-2016-1045 ↗
77. 10.1149/2.031209jes10.1149/2.031209jes ↗
78. 10.1006/jcis.1994.140210.1006/jcis.1994.1402 ↗
79. 10.1149/1.359655610.1149/1.3596556 ↗
80. 10.1149/2.0381706jes10.1149/2.0381706jes ↗
81. 10.1149/2.0391706jes10.1149/2.0391706jes ↗
82. 10.1002/adma.20150355710.1002/adma.201503557 ↗