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<p>This paper proposes a new methodology for structural topology optimization that is capable of stress minimization design considering Additive Manufacturing (AM) self-supporting constraints. Unprintable geometries are effectively excluded from the design space, resulting in fully self-supporting stress optimized designs. The Bi-directional Evolutionary Structural Optimization (BESO) method is adopted to circumvent the intermediate density element problem in AM and the singularity issue in stress design. To cope with large scale constraints, the maximal von Mises stress is measured by the global <i>p</i>-norm stress aggregation approach. The density filter BESO method is developed while the sensitivity expressions are derived. Influences of varying printing directions on the optimized topological structures and von Mises stress distributions are investigated through 2D benchmark numerical examples. Comparisons with the stiffness design considering AM self-supporting constraints are discussed. The effectiveness of the proposed method is further validated in comparison with the stress design without considering AM self-supporting constraints. It is revealed that the proposed method can effectively reduce the stress level of the optimized topological structure under stress design with AM self-supporting constraints.</p>

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Stress-based topology optimization of structures considering additive manufacturing self-supporting constraints

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Yongsheng Han,
  • Fanren Wang,
  • Kang Ren,
  • Linfeng Han

摘要

This paper proposes a new methodology for structural topology optimization that is capable of stress minimization design considering Additive Manufacturing (AM) self-supporting constraints. Unprintable geometries are effectively excluded from the design space, resulting in fully self-supporting stress optimized designs. The Bi-directional Evolutionary Structural Optimization (BESO) method is adopted to circumvent the intermediate density element problem in AM and the singularity issue in stress design. To cope with large scale constraints, the maximal von Mises stress is measured by the global p-norm stress aggregation approach. The density filter BESO method is developed while the sensitivity expressions are derived. Influences of varying printing directions on the optimized topological structures and von Mises stress distributions are investigated through 2D benchmark numerical examples. Comparisons with the stiffness design considering AM self-supporting constraints are discussed. The effectiveness of the proposed method is further validated in comparison with the stress design without considering AM self-supporting constraints. It is revealed that the proposed method can effectively reduce the stress level of the optimized topological structure under stress design with AM self-supporting constraints.