5 papers
Wasserstein crossover for evolutionary algorithm-based topology optimization
Taisei Kii, Kentaro Yaji, Hiroshi Teramoto +1
Evolutionary algorithms (EAs) are promising approaches for non-differentiable or strongly multimodal topology optimization problems, but they often suffer from the curse of dimensi…
Maximum stress minimization via data-driven multifidelity topology design
Misato Kato, Taisei Kii, Kentaro Yaji +1
The maximum stress minimization problem is among the most important topics for structural design. The conventional gradient-based topology optimization methods require transforming…
Adjoint lattice kinetic scheme for topology optimization in fluid problems
Yuta Tanabe, Kentaro Yaji, Kuniharu Ushijima
This paper proposes a topology optimization method for non-thermal and thermal fluid problems using the Lattice Kinetic Scheme (LKS).LKS, which is derived from the Lattice Boltzman…
Deep Concept Identification for Generative Design
Ryo Tsumoto, Kentaro Yaji, Yutaka Nomaguchi +1
A generative design based on topology optimization provides diverse alternatives as entities in a computational model with a high design degree. However, as the diversity of the ge…
Data-driven topology design with persistent homology for enhancing population diversity
Taisei Kii, Kentaro Yaji, Hiroshi Teramoto +1
This paper proposes a selection strategy for enhancing population diversity in data-driven topology design (DDTD), a topology optimization framework based on evolutionary algorithm…