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<p>As a&#xa0;crucial mechanical fastener, nuts are widely employed in various engineering applications, including mechanical equipment, building structures, transportation systems, and other related fields. However, conventional nuts exhibit an uneven load distribution among the threads under external forces, resulting in significant stress concentration at the thread roots, which adversely affects their load-bearing capacity and fatigue life. To improve the stress state at the thread root, this study addresses the issue of load uniformity in suspension nuts subjected to dynamic loading by proposing a&#xa0;parameter optimization method based on a&#xa0;combination of Genetic Algorithm and finite element co-simulation. With uniform load distribution as the optimization objective, a&#xa0;mathematical model is established with maximum equivalent stress and deformation as constraints, and the genetic algorithm is employed for the optimization process. The optimized results are validated through static simulations using ANSYS Workbench. The result demonstrates that the maximum stress of the optimized suspension nut represents a&#xa0;decrease of 28.1% compared to conventional nuts. This method provides a&#xa0;novel perspective and reference for the optimization design of nuts in bolted connections.</p>

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Optimization design of suspension nut structure based on a combined finite-Element-Genetic algorithm method

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Xiangquan Li,
  • Kai Li,
  • Chao Wang,
  • Guoyu Hu

摘要

As a crucial mechanical fastener, nuts are widely employed in various engineering applications, including mechanical equipment, building structures, transportation systems, and other related fields. However, conventional nuts exhibit an uneven load distribution among the threads under external forces, resulting in significant stress concentration at the thread roots, which adversely affects their load-bearing capacity and fatigue life. To improve the stress state at the thread root, this study addresses the issue of load uniformity in suspension nuts subjected to dynamic loading by proposing a parameter optimization method based on a combination of Genetic Algorithm and finite element co-simulation. With uniform load distribution as the optimization objective, a mathematical model is established with maximum equivalent stress and deformation as constraints, and the genetic algorithm is employed for the optimization process. The optimized results are validated through static simulations using ANSYS Workbench. The result demonstrates that the maximum stress of the optimized suspension nut represents a decrease of 28.1% compared to conventional nuts. This method provides a novel perspective and reference for the optimization design of nuts in bolted connections.