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Level set topology optimization for design-dependent pressure loads using the reproducing kernel particle method
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Level set topology optimization for design-dependent pressure loads using the reproducing kernel particle method

Andreas Neofytou, Renato Picelli, Tsung-Hui Huang, Jiun-Shyan ChenH. Alicia Kim
Structural and Multidisciplinary Optimization, 卷.61(5), 頁碼.1805-1820
05/2020

摘要

Design-dependent pressure load Level set method Reproducing kernel particle method Topology optimization Software Control and Systems Engineering Computer Science Applications Computer Graphics and Computer-Aided Design Control and Optimization
This paper presents a level set topology optimization method in combination with the reproducing kernel particle method (RKPM) for the design of structures subjected to design-dependent pressure loads. RKPM allows for arbitrary particle placement in discretization and approximation of unknowns. This attractive property in combination with the implicit boundary representation given by the level set method provides an effective framework to handle the design-dependent loads by moving the particles on the pressure boundary without the need of remeshing or special numerical treatments. Moreover, the reproducing kernel (RK) smooth approximation allows for the Young’s modulus to be interpolated using the RK shape functions. This is another advantage of the proposed method as it leads to a smooth Young’s modulus distribution for smooth boundary sensitivity calculation which yields a better convergence. Numerical results show good agreement with those in the literature.

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https://doi.org/10.1007/s00158-020-02549-9檢視
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