首页> 外文会议>Proceedings of the 7th international conference on fuel cell science, engineering, and technology 2009 >CONDENSATION BASED PORE NETWORK MODELLING OF WATER TRANSPORT IN HYDROPHOBIC PEM FUEL CELL GDLS
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CONDENSATION BASED PORE NETWORK MODELLING OF WATER TRANSPORT IN HYDROPHOBIC PEM FUEL CELL GDLS

机译:基于冷凝的多孔PEM燃料电池GDLS输水孔道网络建模

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In this work, a novel pore network model is employed to simulate water transport originating from condensation in the polymer electrolyte membrane (PEM) fuel cell gas diffusion layer (GDL). Liquid water transport follows the rules of invasion percolation with trapping, where two mobile phases are considered. Flow conditions are based on dynamic pressure changes in the network. The GDL is assumed to be a hydrophobic pore network, where capillary forces dominate over gravitational and viscous forces. The model follows a condensation based algorithm that begins with a single nucleation site from where liquid water spreads with continuing condensation. To account for a humidity gradient within the GDL, water flow is assumed to originate from condensation occurring in pores facing the cathode catalyst layer. Modelling parameters and their effect on the saturation profile are discussed. Little impact was found on the saturation profile when trapping logic was made more sophisticated, recognizing conditions leading to air trapping in a single throat. It is shown that saturation profiles for slow flow (I.e. slow condensation rates) can be predicted with reasonable accuracy from a known throat topology alone. However, as condensation rates are increased, raising network viscous forces to levels comparable to network capillary forces, the flow patterns begin to depend on a number of variables such as pore sizes and pore filling rates. At such condensation rates, flow patterns show high sensitivity to variance in condensation rates and become much less predictable from simple geometries.
机译:在这项工作中,采用了一种新型的孔网络模型来模拟源自聚合物电解质膜(PEM)燃料电池气体扩散层(GDL)中凝结的水传输。液态水的运输遵循入侵与渗漏的规律,其中考虑了两个流动相。流量条件基于网络中的动态压力变化。假设GDL是疏水性孔隙网络,其中毛细作用力胜过重力和粘性作用力。该模型遵循基于冷凝的算法,该算法从单个成核位置开始,液态水从该成核位置开始扩散并持续冷凝。为了说明GDL内的湿度梯度,假定水流源自在面对阴极催化剂层的孔中发生的冷凝。讨论了建模参数及其对饱和度分布的影响。当使捕集逻辑变得更加复杂时,对饱和度分布的影响很小,因为它可以识别导致在单个喉咙中捕集空气的条件。结果表明,仅从已知的喉道拓扑结构就可以以合理的精度预测慢流量的饱和曲线(即,慢的凝结速率)。然而,随着凝结速率的增加,将网络粘性力提高到与网络毛细管力相当的水平,流动模式开始取决于许多变量,例如孔径和孔填充率。在这样的冷凝速率下,流型显示出对冷凝速率变化的高度敏感性,并且由于简单的几何形状而变得难以预测。

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