新型随机重构微孔隙介质模型与扩散特性

Characterization and Diffusion in Reconstructed Gas Diffusion Layer Based on Stochastic Method

摘要:

提出一种使用碳纸气体扩散层微孔隙结构的真实形态参数，构建三维微孔隙结构模型的算法.此方法通过扫描真实的扩散层结构获取结构的特性参数.通过确定三维微结构内纤维系统的中心坐标，循环构建N层纤维系统，达到需求的扩散层厚度，各层纤维系统由随机分布的重叠并相交的纤维结构构成；并将成功构建的模型转换为能够用于流体仿真的数据模型，对结构模型的渗透率进行了验证.结果表明，该方法生成的模型符合真实扩散层的渗透特性.最后，利用该模型对扩散层各项特性参数的变化关系进行了分析，结果可用于扩散层的结构优化设计，更大程度增强渗透传输特性.

Abstract:

This paper aims to build a 3D micro structure of carbon paper gas diffusion layer (GDL) based on morphological parameter of true materials. This method needs to acquire the basic morphological parameter first by scanning the true GDL structure. Then, by confirming the center coordinates of the whole 3D GDL structure, it constructs a layer of fiber structure each time through the loop and stops when reaching the true thickness. The fiber in each layer will be overlapping and intersecting. After finishing the reconstruction, it needs to be transferred to the binary image that is convenient to fluid modeling. This structure model is used to test the permeability, and the results obtained from the stochastic reconstruct method is very close to the results of the true image. From the case study, the permeability characteristic effect with the change of each structure parameter is given. These results will be used for the structure optimization and improvement of the diffusion of GDL structure.