TY - JOUR
T1 - Concurrent 3D topology optimization method for hierarchical hybrid structures under static and dynamic loads with CPU-GPU heterogeneous parallelism
AU - Liu, Yunfei
AU - Gao, Ruxin
AU - Li, Ying
AU - Fang, Daining
N1 - Publisher Copyright:
© 2025 Elsevier B.V.
PY - 2026/1/1
Y1 - 2026/1/1
N2 - Topology optimization of 3D hierarchical hybrid structures (HHS) is constrained by the coupling of high-dimensional design spaces and multiscale computational complexity, often addressed by restricting certain designable components, which limits the full exploration of the design space and realization of performance potential. This paper proposes a novel concurrent topology optimization method for 3D-HHS, achieving concurrent optimization of all designable components, including macroscopic topology, substructural topology, and their spatial distribution, under static and dynamic loads. This approach significantly expands the design space, enhancing the mechanical performance of hierarchical structures. To address the computational challenges of large-scale 3D problems, we employ CPU-GPU heterogeneous parallel computing to improve the efficiency of structural response and sensitivity analysis. Numerical examples demonstrate that this method delivers superior 3D-HHS designs with markedly improved optimization efficiency, providing an innovative solution for efficient 3D structural optimization.
AB - Topology optimization of 3D hierarchical hybrid structures (HHS) is constrained by the coupling of high-dimensional design spaces and multiscale computational complexity, often addressed by restricting certain designable components, which limits the full exploration of the design space and realization of performance potential. This paper proposes a novel concurrent topology optimization method for 3D-HHS, achieving concurrent optimization of all designable components, including macroscopic topology, substructural topology, and their spatial distribution, under static and dynamic loads. This approach significantly expands the design space, enhancing the mechanical performance of hierarchical structures. To address the computational challenges of large-scale 3D problems, we employ CPU-GPU heterogeneous parallel computing to improve the efficiency of structural response and sensitivity analysis. Numerical examples demonstrate that this method delivers superior 3D-HHS designs with markedly improved optimization efficiency, providing an innovative solution for efficient 3D structural optimization.
KW - 3D hierarchical hybrid structures
KW - All designable components
KW - CPU-GPU heterogeneous parallelism
KW - Concurrent topology optimization
KW - EMsFEM
UR - https://www.scopus.com/pages/publications/105016690356
U2 - 10.1016/j.cma.2025.118408
DO - 10.1016/j.cma.2025.118408
M3 - Article
AN - SCOPUS:105016690356
SN - 0045-7825
VL - 448
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
M1 - 118408
ER -