首页> 外文会议>ASME International Mechanical Engineering Congress and Exposition >3D MICROSTRUCTURE RECONSTRUCTIONS OF SOLID OXIDE AND PROTON EXCHANGE MEMBRANE FUEL CELL ELECTRODES WITH APPLICATIONS TO NUMERICAL SIMULATIONS OF REACTING MIXTURE FLOWS USING LBM
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3D MICROSTRUCTURE RECONSTRUCTIONS OF SOLID OXIDE AND PROTON EXCHANGE MEMBRANE FUEL CELL ELECTRODES WITH APPLICATIONS TO NUMERICAL SIMULATIONS OF REACTING MIXTURE FLOWS USING LBM

机译:用LBM对反应混合物流量的数值模拟的应用与数值模拟的固体氧化物和质子交换膜燃料电池电极的微观结构重建

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Computational modeling of fuel cell electrode-catalyst layers is an important tool in understanding the different electrochemical reactions and transport phenomena occurring within fuel cell electrodes. Proper modeling of this layer is required for an accurate prediction of cell behavior which in turn can be used for the development of more efficient fuel cells. In macroscopic CFD approaches such layers are typically modeled as infinitely thin interfaces populated by sources and sinks or as very thin homogeneous porous layers. However, these layers are neither infinitely thin nor homogeneous and, thus, modeling in this fashion leads to a loss of information about the microstructure and its varying effects on the reacting mixture flows which pass through and into the structure. Thus, the utility of relying only on such macroscopic representations limits the general applicability of these macroscopic models as tools for design and for predicting fuel cell performance over a wide range of conditions. Furthermore, such macroscopic models cannot aid in the design of the electrode-catalyst layer itself. In order to address this latter point, a microscopic/mesoscopic modeling approach can be used, e.g., the Lattice Boltzmann Method (LBM), which models the reacting mixture flow through the porous microstructure of the electrode-catalyst layer. However, to do so requires reconstructing the porous geometry of this layer which can be done by using 2D microscopic images of cross-sections of the layer to generate 3D geometries from, for example, stochastic models which are relatively cost efficient and lead to similar structures with approximately the same characteristics of porosity, catalyst loading, three-phase boundaries, etc. as the original structure. Two such 3D reconstruction methods, i.e. one based on the granulometry law (one-point statistics) and the other on two-point statistics, are applied to a 2D SEM (scanning electron microscope) image of an SOFC electrode-catalyst layer and to the 2D SEM and TEM (transmission electron microscope) images for such a layer in a PEMFC. Results for these reconstructions are presented as are results for reacting mixture flow simulations through the two different reconstructed 3D SOFC structures using a 3D LBM approach. The development and application of a 3D LBM model for two-phase reacting mixture flows in PEMFC electrode-catalyst layer structures is in progress and will be reported in a future paper.
机译:燃料电池电极催化剂层的计算建模是了解在燃料电池电极内发生的不同电化学反应和运输现象的重要工具。对于对细胞行为的准确预测,需要适当建模,这又可以用于开发更有效的燃料电池。在宏观CFD中,这种层通常被建模为由源源和下沉或作为非常薄的均匀多孔层的无限薄界面。然而,这些层既不明显薄也不是均匀的,因此,以这种方式的建模导致关于微观结构的信息丢失及其对通过通过和进入结构的反应混合物流的信息的损失及其变化效应。因此,仅依赖于这种宏观表示的效用限制了这些宏观模型的一般适用性作为设计的工具,并在广泛的条件下预测燃料电池性能。此外,这种宏观模型不能有助于设计电极催化剂层本身。为了解决后一点,可以使用微观/介性建模方法,例如,晶格Boltzmann方法(LBM),其模拟反应混合物流过电极催化剂层的多孔微观结构。然而,要这样做,需要重建该层的多孔几何形状,这可以通过使用层的横截面的2D微观图像来完成,以从例如具有相对成本效率的随机模型产生3D几何形状并导致类似的结构具有与原始结构大致相同的孔隙,催化剂负载,三相边界等特征。两个这样的3D重建方法,即基于粒度法律(单点统计)和另一种在两点统计中的3D重建方法,应用于SOFC电极催化剂层的2D SEM(扫描电子显微镜)图像和到2D SEM和TEM(透射电子显微镜)PEMFC中的这种层的图像。呈现这些重建的结果,因为可以使用3D LBM方法将混合物流模拟反应混合流量模拟的反应通过两个不同的重建的3D SOFC结构。在PEMFC电极 - 催化剂层结构中的两相反应混合物的3D LBM模型的开发和应用正在进行中,将在未来的纸张中报告。

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