Topology optimization based on moving deformable components: A new computational framework
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Abstract (arXiv)
In the present work, a new computational framework for structural topology optimization based on the concept of moving deformable components is proposed. Compared with the traditional pixel or node point-based solution framework, the proposed solution paradigm can incorporate more geometry and mechanical information into topology optimization directly and therefore render the solution process more flexible. It also has the great potential to reduce the computational burden associated with topology optimization substantially. Some representative examples are presented to illustrate the effectiveness of the proposed approach.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Apr 2014.
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Citing papers per year: 2023: 2; 2024: 3; 2025: 1.
6 papers.
- 2023Data-Driven Design for Metamaterials and Multiscale Systems: A Reviewcited by 17
- 2024Neural topology optimization: the good, the bad, and the uglycited by 10
- 2023XVoxel-Based Parametric Design Optimization of Feature Modelscited by 1
- 2024Structural Design Through Reinforcement Learningcited by 0
- 2024Data-driven topology design based on principal component analysis for 3D structural design problemscited by 0
- 2025Enhanced Data-driven Topology Design Methodology with Multi-level Mesh and Correlation-based Mutation for Stress-related Multi-objective Optimizationcited by 0
- 2025Enhanced Data-driven Topology Design Methodology with Multi-level Mesh and Correlation-based Mutation for Stress-related Multi-objective Optimization21 Apr 2025
- 2024Data-driven topology design based on principal component analysis for 3D structural design problems3 Sep 2024
- 2024Neural topology optimization: the good, the bad, and the ugly19 Jul 2024
- 2024Structural Design Through Reinforcement Learning10 Jul 2024
- 2023Data-Driven Design for Metamaterials and Multiscale Systems: A Review1 Jul 2023
- 2023XVoxel-Based Parametric Design Optimization of Feature Models17 Mar 2023