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<p>Surface texture design is one of the effective means of improving tribological performance of sliding surface. This study presents a novel approach for topology optimization of surface texture using discrete design variables to improve the tribological performance. Leveraging the Sequence Approximate Integer Programming (SAIP) framework and finite element discretization, the discrete 0–1 variables are employed for every finite element to denote the presence or absence of lubrication regions. Since the uniform thickness of texture are assigned and guaranteed by the discrete 0–1 variables, the manufacturability can be ensured. Unlike traditional pixel-based methods with continuous variables, this approach avoids reliance on penalty schemes and eliminates issues of continuous and irregular thickness variations. Furthermore, feature size constraint in conjunction with SAIP is also introduced to control the texture complexity. These attractive features make connection of design and manufacturing processes. Some typical numerical examples are given to demonstrate the effectiveness of the approach in optimizing surface texture, offering optimized solutions for applications in bearings, seals, and engine cylinders.</p>

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Topology optimization of sliding surface texture via discrete variable using sequence approximate integer programming

  • 期刊论文

  • 发表日期：

    2025年9月30日

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  • Weisheng Zhang,
  • Zhigang Dai,
  • Yuan Liang,
  • Bao Zhu

摘要

Surface texture design is one of the effective means of improving tribological performance of sliding surface. This study presents a novel approach for topology optimization of surface texture using discrete design variables to improve the tribological performance. Leveraging the Sequence Approximate Integer Programming (SAIP) framework and finite element discretization, the discrete 0–1 variables are employed for every finite element to denote the presence or absence of lubrication regions. Since the uniform thickness of texture are assigned and guaranteed by the discrete 0–1 variables, the manufacturability can be ensured. Unlike traditional pixel-based methods with continuous variables, this approach avoids reliance on penalty schemes and eliminates issues of continuous and irregular thickness variations. Furthermore, feature size constraint in conjunction with SAIP is also introduced to control the texture complexity. These attractive features make connection of design and manufacturing processes. Some typical numerical examples are given to demonstrate the effectiveness of the approach in optimizing surface texture, offering optimized solutions for applications in bearings, seals, and engine cylinders.