Tiling of Microstructures According to the Density Values of SIMP Topology Optimization

Date

2020-11-01

Author

Helvaci, Damla Ozkapici
Yaman, Ulaş

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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URI

https://linkinghub.elsevier.com/retrieve/pii/S2351978920320023
https://hdl.handle.net/11511/92320

Journal

Procedia Manufacturing

Collections

Department of Mechanical Engineering, Article

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Tiling of cellular structures into the parts according to the density values of SIMP topology optimization Özkapıcı Helvacı, Damla; Yaman, Ulaş; Department of Mechanical Engineering (2020-9) In this thesis, a method is proposed to enhance the performance of the parts optimized by Solid Isotropic Material with Penalization (SIMP) method. SIMP is a density-based topology optimization method which basically aims to distribute the material through the part subjected to various loads, boundary conditions and constraints in the optimum way. Thus, the part satisfies an optimization goal without violating the predefined constraints. The most prominent feature of this method is that the densities of the...
Tiling of cellular structures into 3d parts according to the density values of simp topology optimization Helvaci, Damla Ozkapici; Yaman, Ulaş (2022-01-01) In this study, a novel approach is proposed to enhance the performance of the parts optimized by Solid Isotropic Material with Penalization (SIMP) method. SIMP is a topology optimization method that aims the optimum distribution of material in a design domain subjected to predefined loads, constraints and boundary conditions. The method forces every finite element composing the geometry to have a density of either 1 or 0. The main reason behind penalizing is that regions with intermediate densities are diff...
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Citation Formats

D. O. Helvaci and U. Yaman, “Tiling of Microstructures According to the Density Values of SIMP Topology Optimization,” Procedia Manufacturing, vol. 51, pp. 1033–1037, 2020, Accessed: 00, 2021. [Online]. Available: https://linkinghub.elsevier.com/retrieve/pii/S2351978920320023.