Multiscale structural optimization based on integrated multidisciplinary system design method

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K19768
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 60:Information science, computer engineering, and related fields
• Research Institution: Kyoto University
• Principal Investigator: Izui Kazuhiro 京都大学, 工学研究科, 教授 (90314228)
• Co-Investigator(Kenkyū-buntansha): 西脇 眞二 京都大学, 工学研究科, 教授 (10346041)
• Project Period (FY): 2021-07-09 – 2024-03-31
• Keywords: マルチスケール最適化 / ミクロ構造 / マクロ構造 / トポロジー最適化

Outline of Final Research Achievements

By using topology optimization simultaneously in the macroscale structural shape design and the microscale material design, we can expect to design high-performance devices using materials with special properties that cannot be obtained with ordinary bulk materials. In this research, we investigated methods for modeling nonlinear characteristics by introducing surrogate models for the results of microscale topology optimization problems. We constructed a surrogate model using radial basis functions based on Gaussian functions, and also constructed a method to optimize macroscale structural shape design method using optimization using that surrogate model.

Free Research Field

設計工学

Academic Significance and Societal Importance of the Research Achievements

機械構造やデバイスのマクロスケールの形状を最適化するだけでなく，ミクロスケールの材料設計を行うことで，バルク材では実現できない特異な性能をもつ製品を設計できる可能性がある．ここでは，そのような製品を試行錯誤ではなく計算で求めるための方法として，トポロジー最適化に着目し，マクロ・ミクロの両者を同時に最適化するマルチスケールトポロジー最適化法の基礎理論の構築を行った．