Research

Conventional heat transfer devices such as heat sinks and heat exchangers are limited to geometrically simple shapes due to their manufacturing constraints. On the other hand, thanks to the recent development of additive manufacturing technology, innovative heat transfer systems are becoming reality in near future. The aim of this research is to realize such an innovative heat transfer system, and we develop design methodologies based on topology optimization.

Redox flow battery is a rechargeable battery, which has attracted attention as a next-generation electrochemical energy storage system. It is widely known that achieving high performance in terms of power density is critical for its commercialization. The aim of this research is to propose a computational design approach for automatically generating an optimized flow field design of a redox flow battery to achieve high performance without relying on the designer's intuition.

Topology optimization is a powerful methodology for generating novel designs with a high degree of design freedom. In exchange for this attractive feature, topology optimization cannot generally avoid multimodality, which often impedes finding a satisfactory solution when dealing with strongly nonlinear optimization problems. In this study, we focus on constructing a framework that aims to indirectly solve such complex topology optimization problems. The framework is based on multifidelity topology design (MFTD), the basic concept of which is to divide solving an original topology optimization problem into two kinds of procedures, i.e., low-fidelity optimization and high-fidelity evaluation.