Scholarlink

<p>Metal additive manufacturing (AM) processes inherently introduce internal and surface defects, which significantly reduce the fatigue performance of fabricated components. This paper presents a computational fatigue-aware topology optimization framework that explicitly accounts for multiple manufacturing-induced defects during the early design phase. A critical equivalent defect model is developed by statistically estimating the multiple defect sizes and translating them into the first principal stress constraint using the Murakami equation. The proposed method integrates the Bi-Directional Evolutionary Structural Optimization (BESO) approach, employing both first principal and von Mises stresses to guide the optimization process. Numerical studies on three structural examples, including an L-shaped bracket, a T-shaped beam, and a fixed–fixed beam, demonstrate that the topology optimization incorporating critical equivalent defect constraint leads to improved fatigue performance with minimal compromise in structural stiffness. This work establishes a fatigue-aware simulation framework for the robust design of AM components, laying the foundation for future integration with experimental validation and manufacturing practices.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fatigue-aware topology optimization for multiple defects based on critical equivalent defect

  • 期刊论文

  • 发表日期：

    2026年3月30日

查看全文
  • Zhicheng He,
  • Wentao He,
  • Rongqi Li,
  • Hui Gao

摘要

Metal additive manufacturing (AM) processes inherently introduce internal and surface defects, which significantly reduce the fatigue performance of fabricated components. This paper presents a computational fatigue-aware topology optimization framework that explicitly accounts for multiple manufacturing-induced defects during the early design phase. A critical equivalent defect model is developed by statistically estimating the multiple defect sizes and translating them into the first principal stress constraint using the Murakami equation. The proposed method integrates the Bi-Directional Evolutionary Structural Optimization (BESO) approach, employing both first principal and von Mises stresses to guide the optimization process. Numerical studies on three structural examples, including an L-shaped bracket, a T-shaped beam, and a fixed–fixed beam, demonstrate that the topology optimization incorporating critical equivalent defect constraint leads to improved fatigue performance with minimal compromise in structural stiffness. This work establishes a fatigue-aware simulation framework for the robust design of AM components, laying the foundation for future integration with experimental validation and manufacturing practices.