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PEM fuel cells are currently at the focus of researchers' attention due to their promising potential application in modern vehicles. Fundamental tiny-scale phenomena occurring in the PEM fuel cell porous electrodes can be represented more faithfully by pore scale simulation techniques which entail microstructure reconstruction of porous media such...
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... general components of hydrogen PEM fuel cell are shown in Fig. 1. The oxidizer and fuel travel through the cathode and anode flow fields and subsequently disperse through the related porous gas diffusion layers (GDLs) with 200e400 mm thickness and diffuse through the related catalyst layers (CLs) with 5e20 mm thickness. In some PEM fuel cells, micro-porous layer (MPL) is placed between GDL and CL to ...
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Citations
A circle/sphere populating method is proposed to generate 2D/3D stochastic microstructures. The proposed method uses circles/spheres as the basic elements and generates microstructure features through the populating process of the circles/spheres. In the populating process, the cores are first generated randomly and circles/spheres start to populate around the cores or the previous generation’s circles/spheres. The populating process is controlled by the input parameters including the volume fraction, core number, circle/sphere size distribution, circle/sphere populating distance distribution, circle/sphere populating number, and populating direction constraint angle. The proposed method was compared with the QSGS method and random circle/sphere method in 2-dimensional (2D) and 3-dimensional (3D) cases. The proposed method shows advantages in generating microstructures with clear feature geometries and boundaries. Furthermore, parametric studies are conducted in 2D and 3D to investigate the effect of input parameters on the generated microstructures. With the consideration of circle/sphere spatial distributions, the proposed method can achieve different degrees of feature clustering and agglomerating. A wide range of microstructure morphologies can be achieved by adjusting the input parameters. A more accurate description of the features in the microstructures can be achieved without the involvement of the annealing-based optimization process. As a case study, the proposed method was used to generate sandstone microstructures with different grain size distributions and spatial distributions, and the permeability of generated sandstone was analyzed. Furthermore, the proposed method was applied to generate the microstructure model with a target radial distribution function to demonstrate its computational efficiency by comparing it with the random sphere method and simulated annealing based method.
The gas diffusion substrate (GDS) is essential in the proton exchange membrane fuel cells. Its fabrication techniques affect the performance significantly and are worthy of investigation. In this study, a manufacturing process of the GDS is proposed to understand the formation process of GDS and promote its structure and performance more pertinently. Different states during the preparation process, raw carbon paper, pre-curing, curing, carbonation, and graphitization, are characterized and measured. Experimental and numerical methods are employed to determine the relationships between microstructure, transport, and mechanical performance variation with the fabricating processes. The results show that its porosity, average pore size, and effective diffusivity decrease first and increase after curing. These parameters after graphitization are lower than that of the carbon paper (CP). The electrical resistivity increases dramatically while pre-curing and decreases gradually after curing, carbonation, and graphitization, and it is much reduced after graphitization. Moreover, mechanical measurement results show that both the picks of tensile strength and flexural modulus occur after curing. Its tensile strength shows little change after graphitization compared to the initial paper's. In contrast, the flexural modulus is improved significantly.
Two challenging tasks in pore-scale modeling of a gas diffusion layer (GDL) are realistic microstructure reconstruction and stress-strain simulation to differentiate the heterogeneous materials. This study proposes a novel method for reconstructing a GDL using fiber tracking technique and pore-scale modeling to investigate its stress-strain and anisotropic transport properties. X-ray computed tomography, fiber tracking, and morphological processing techniques were employed to reconstruct a realistic GDL. Pore-scale modeling was performed to compute the stress-strain, gas diffusivity, and electrical-thermal conductivity at different compression ratios. The sensitivity of compression speed and Young's modulus were investigated to balance the accuracy and computing cost of stress-strain simulation. The results showed that Young's modulus of 1 GPa and compression speed of 3 m/s meet the requirements for both accuracy and computational cost. The reconstructed GDL showed good agreements with the experimental data when considering fibers' orientation, length, and curvature. It was found that the stress among fibers was approximately five times higher than binders. The anisotropic ratios of diffusivity and conductivity decreased from 1.35 to 1.25, and 15 to 5, respectively, as the compression ratio increased to 25%. This study can provide accurate predictions and guidelines for GDL design with low stress and high performance.
