梯度多孔金属纤维载体的多尺度拓扑优化设计

As a novel micro catalyst support, gradient porous metal fiber structure (GPMFS) demonsrates obvious advantages when used in the on-board hydrogen supply system for fuel cell powered vehicle. However, currently GPMFS was designed by intuition, and there is lack of available design theories and methodologies to optimize its structure for hydrogen production performance enhancement, thus greatly limiting the further development of GPMFS. Regarding with the aperiodic and randomized fribrous porous structure, this project aims to investigating the multi-scale topology optimization design methodology for GPMFS, based on our previous studies. Firstly, the key statistic features of GPMFS will be characterized and utilized to drive the generation of the full-size digital model of GPMFS, based on the customization of optimal algorithms. Secondly, the 2-dimensional radom resistance network model will be extended for the 3-dimensional highly connected pore architecture of GPMFS, paving the way to establish a theoretical analysis method for the flow field uniformity inside GPMFS. On this basis, the correlation between the field uniformity and the hydrogen production performance of GPMFS will be revealed, and consequently the performance evaluation creation system based on the flow field uniformity will be established. Thirdly, a two-way information exchange mechanism between macro variables and micro variable distribution will be established, accelerating the development of the efficient multi-scale topology optimization methodology, constrained and controlled by the performance evaluation criterion, for GPMFS. Finally, the proposed methodology will be validated, fixed and improved based on experimental studies. Through multidiscipline theoretical research and experimental validation, it is expected that the project will also set the foundation of novel theories and methodologies for the multi-scale optimization of GPMFS, and facilitate the industrialization of fuel cell for vehicle power supply.

梯度多孔金属纤维结构是一种新型微催化反应载体(简称梯度纤维载体)，在氢燃料电池汽车的移动制氢微反应器中显示出显著优势，但缺乏优化设计理论和技术，严重制约其进一步发展。针对该类非周期性随机纤维多孔结构，项目拟基于前期工作研究梯度纤维载体的多尺度拓扑优化设计方法。表征梯度纤维载体的统计特征，基于优化算法建立统计特征驱动的大尺度梯度纤维载体数字化建模方法；拓展随机电阻网络模型，形成载体内部流场均匀性分析的理论方法，揭示流场均匀性和载体制氢反应性能之间的关联规律，建立梯度纤维载体的性能评价标准体系；探索梯度纤维载体宏-微观物理量双向关联的信息交换机制，建立受性能评价标准约束和控制的高效梯度纤维载体多尺度拓扑优化设计方法；开展物理实验，验证、修正并完善提出的方法。通过多学科理论和实验分析，期望促进梯度纤维载体多尺度优化设计基础理论与技术的发展，以及车载氢燃料电池的工业化应用。

梯度多孔金属纤维结构是一种新型微催化反应载体（简称梯度纤维载体），在氢燃料电池汽车的移动制氢微反应器中显示出显著优势。但由于纤维随机分布，其内部三维孔隙结构错综复杂，其设计缺乏优化设计理论和技术的指导，致使其进一步发展受到严重制约。. 本项目围绕该类非周期性随机纤维多孔功能结构优化设计的迫切需求，以流场均匀性为目标，突破了梯度纤维载体的拓扑优化设计理论和技术。具体而言，项目通过对纤维载体等多孔功能结构的内部三维孔隙结构的核心参数进行统计分析，建立了其统计特征，并形成了三维流体通道的统计表征方法；考虑计算可行性，借鉴基尔霍夫电压和电流定律，基于统计特征，建立了等效随机电阻网络模型对纤维载体等多孔功能结构的内部孔隙结构进行简化，并实现了其中流场的快速求解；在此基础上，通过与已有性能实验结果进行关联分析，形成了面向纤维载体等多孔功能结构拓扑优化的性能评价指标构建方法；针对纤维载体等多孔功能结构不同的优化设计场景，结合可制造性，通过发展耦合参数的解耦优化策略、基于离散伴随敏度的形状优化和拓扑优化方法，突破了基于流速场均匀度指数等性能指标的纤维载体等多孔功能结构的优化设计理论和技术，包括参数优化、形状优化和拓扑优化；以此为基础，基于开源的科学计算可移植扩展工具包PETSc，以及ANSYS、MATLAB和COMSOL等商业软件，搭建了多种类型的纤维载体等多孔功能结构优化设计平台，并在高性能制氢系统的催化反应载体设计中进行了初步应用。项目的研究成果提升了多孔结构数字化建模的能力，有利于发展纤维载体等多孔功能结构优化设计的支撑性理论基础与创新技术，并促进其研制模式向基于性能驱动的“主动”模式转变。

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