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March 26, 2026The Proceedings of Mechanical Engineering Congress JapanOpen Access

Development of an integrated optimization method for shape generation and material selection using machine learning

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Authors

MIMakoto INOMOTOSOSae OBATA

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Overview

Presents a method optimizing shape and material selection, enhancing design flexibility while meeting constraints.

Key Points

  • The research aims to develop an optimization method that balances shape generation flexibility with material selection and manufacturing constraints.
  • Developed a method for shape modifications aligned with engineering intentions.
  • Used finite element analysis to define morphing vectors for shape generation.
  • Employed Bayesian optimization to minimize stress and maximize flexural rigidity while selecting materials.
  • Achieved diverse shapes while adhering to manufacturing constraints.
  • Simultaneously optimized material selection with shape variations, enhancing design efficiency.

Cite This Study

INOMOTO et al. (2025) studied this question.

synapsesocial.com/papers/69c4cda5fdc3bde44891a4cchttps://doi.org/10.1299/jsmemecj.2025.s121-08
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