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A topology optimization method for geometrically nonlinear structures with meshless analysis and independent density field interpolation

机译:一种基于无网格分析和独立密度场插值的几何非线性结构拓扑优化方法

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摘要

Based on the element-free Galerkin (EFG) method, an analysis-independent density variable approach is proposed for topology optimization of geometrically nonlinear structures. This method eliminates the mesh distortion problem often encountered in the finite element analysis of large deformations. The topology optimization problem is formulated on the basis of point-wise description of the material density field. This density field is constructed by a physical meaning-preserving interpolation with the density values of the design variable points, which can be freely positioned independently of the field points used in the displacement analysis. An energy criterion of convergenceis used to resolve the well-known convergence difficulty, which would be usually encountered in low density regions, where displacements oscillate severely during the optimization process. Numerical examples are given to demonstrate the effectiveness of the developed approach. It is shown that relatively clear optimal solutions can be achieved, without exhibiting numerical instabilities like the so-called “layering” or “islanding” phenomena even in large deformation cases. This study not only confirms the potential of the EFG method in topology optimization involving large deformations, but also provides a novel topology optimization framework based on element-free discretization of displacement and density fields, which can also easily incorporate other meshless analysis methods for specific purposes.
机译:基于无元素Galerkin(EFG)方法,提出了一种与分析无关的密度变量方法,用于几何非线性结构的拓扑优化。该方法消除了大变形有限元分析中经常遇到的网格畸变问题。拓扑优化问题是在材料密度场逐点描述的基础上制定的。该密度场是通过使用设计可变点的密度值进行物理意义保留插值构建的,该点可以独立于位移分析中使用的场点自由定位。收敛的能量准则用于解决众所周知的收敛困难,这通常发生在低密度区域,在优化过程中位移会剧烈振荡。通过数值算例验证了所开发方法的有效性。结果表明,即使在大变形情况下,也可以实现相对清晰的最优解,而不会出现所谓的“分层”或“孤岛”现象等数值不稳定性。本研究不仅证实了EFG方法在大变形拓扑优化中的潜力,还提供了一种基于位移场和密度场无单元离散化的新型拓扑优化框架,该框架也可以很容易地将其他无网格分析方法用于特定目的。

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