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Multi-resolution Topology Optimization Using B-spline to Represent the Density Field

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1 South China University of Technology, Guangzhou, 510641, China

* Corresponding Author: Zhenbiao Guo. Email: email

The International Conference on Computational & Experimental Engineering and Sciences 2023, 25(4), 1-1. https://doi.org/10.32604/icces.2023.08904

Abstract

This work proposes a novel multi-resolution topology optimization method using B-spline to represent the density field, and overcomes the defects of tedious post-processing of element-based models and low computational efficiency of topology optimization for large-scale problems. The design domain embedded in the B-spline space is discretized with a coarser analysis mesh and a finer density mesh to reduce the computational cost of finite element analysis. As design variables, the coefficients of the control points control the shape of the B-spline. The optimized B-spline can be quickly and precisely converted into a CAD model. Sensitivity filtering is additionally applied to enhance B-spline’s smoothness and suppress QRpatterns. Numerical examples, including 2D and 3D cases, are tested to demonstrate that the proposed method significantly saves computational time without sacrificing the performance of the optimized structure. Moreover, the post-processing procedures are streamlined, resulting in continuous, smooth, and editable models.

Cite This Article

APA Style
Zhenbiao Guo, (2023). Multi-resolution topology optimization using b-spline to represent the density field . The International Conference on Computational & Experimental Engineering and Sciences, 25(4), 1-1. https://doi.org/10.32604/icces.2023.08904
Vancouver Style
Zhenbiao Guo . Multi-resolution topology optimization using b-spline to represent the density field . Int Conf Comput Exp Eng Sciences . 2023;25(4):1-1 https://doi.org/10.32604/icces.2023.08904
IEEE Style
Zhenbiao Guo, “Multi-resolution Topology Optimization Using B-spline to Represent the Density Field ,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 25, no. 4, pp. 1-1, 2023. https://doi.org/10.32604/icces.2023.08904



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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