Multi-Set MMV Topology Optimization Approach for Sliding Surface Texture Design

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Weisheng Zhang, Honghao Tian, Bao Zhu, Xu Guo, Sung-Kie Youn
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引用次数: 0

Abstract

Surface texture is of great practical importance in applications due to its significant effect on the tribological performance of the sliding surface. In the present work, an explicit topology optimization framework for surface texture design is proposed. For this purpose, the moving morphable void (MMV)-based explicit topology optimization approach is used to maximize the load carrying capacity (LCC) of the bearing by optimizing the distribution of the surface texture. A multi-set of voids is established to describe the multi-film thickness of the texture. By using the explicit geometry information in MMV, the present work can be seamlessly linked to the CAD system, resulting in the accurate processing of complex surface textures. Besides some numerical examples to demonstrate the effectiveness of the proposed approach, experimental tests are also provided to verify the validity of the optimization results.

滑动表面纹理设计的多集MMV拓扑优化方法
由于表面织构对滑动表面的摩擦学性能有重要影响,因此在应用中具有重要的实际意义。本文提出了一种用于表面纹理设计的显式拓扑优化框架。为此,采用基于移动变形空洞(MMV)的显式拓扑优化方法,通过优化表面纹理的分布,使轴承的承载能力(LCC)最大化。建立了多组空洞来描述织构的多膜厚度。通过使用MMV中的显式几何信息,可以将当前的工作与CAD系统无缝连接,从而实现复杂表面纹理的精确处理。通过数值算例验证了所提方法的有效性,并通过实验验证了优化结果的有效性。
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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