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<p>Existing multiscale topology optimization methods often suffer from static microstructural designs and fixed material assumptions, hindering true co-evolution of material and structure. To address this, we extend the discrete material optimization (DMO) framework by integrating an environment-aware microstructural evolution mechanism, where micro-topologies adapt dynamically to local thermo-mechanical fields, establishing a closed-loop co-optimization framework across scales. Numerical examples demonstrate that the proposed method effectively promotes the emergence of functionally graded topologies and significantly enhances overall structural performance and convergence efficiency under thermo-mechanical coupling. This work advances the design paradigm from material selection plus structural design to generative material-structure co-design, offering a new pathway for the development of multifunctional, intelligent systems.</p>

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Environmentally driven co-evolution of materials and structure: a generative multiscale topology optimization framework with enhanced discrete material optimization

  • 期刊论文

  • 发表日期：

    2026年7月29日

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  • Shuo Feng,
  • Ke li,
  • Yuhao Yang,
  • Qidong Han

摘要

Existing multiscale topology optimization methods often suffer from static microstructural designs and fixed material assumptions, hindering true co-evolution of material and structure. To address this, we extend the discrete material optimization (DMO) framework by integrating an environment-aware microstructural evolution mechanism, where micro-topologies adapt dynamically to local thermo-mechanical fields, establishing a closed-loop co-optimization framework across scales. Numerical examples demonstrate that the proposed method effectively promotes the emergence of functionally graded topologies and significantly enhances overall structural performance and convergence efficiency under thermo-mechanical coupling. This work advances the design paradigm from material selection plus structural design to generative material-structure co-design, offering a new pathway for the development of multifunctional, intelligent systems.