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Multiscale topology optimization of gradient lattice structure based on volume parametric modeling.
- Source :
-
Composite Structures . Jan2024, Vol. 328, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- In this study, a volume parametric modeling method of lattice structure is proposed, and an efficient multiscale topology optimization framework is realized based on isogeometric analysis (IGA) to construct the gradient lattice structure. The skeleton model is constructed, which can accurately describe the topology structure and improve data utilization and computational efficiency. Based on the skeleton model, a uniform volume parameter lattice structure with an arbitrary topology of multiple types of unit cells is constructed, which is suitable for IGA. Moreover, multiscale topology optimization based on IGA is realized to construct the gradient lattice structure. The same data model is used in modeling, analysis, and optimization, which can accurately represent the geometric shape without discretization errors. At the same time, the multiscale topology optimization iteration is realized by adjusting the density of control points. The optimized model can be directly analyzed and re-optimized, thus realizing the integrated design of lattice structure modeling, simulation, and optimization. The effectiveness and robustness of the algorithm are verified by several mechanical parts and freeform models. These examples show that the gradient lattice structure has higher strength and better stress distribution than the uniform lattice structure under the same boundary conditions. • The gradient lattice structure is designed based on multiscale topology optimization. • Various types of volume parametric lattice structures are constructed. • The model can be analyzed directly by using isogeometric analysis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02638223
- Volume :
- 328
- Database :
- Academic Search Index
- Journal :
- Composite Structures
- Publication Type :
- Academic Journal
- Accession number :
- 173968436
- Full Text :
- https://doi.org/10.1016/j.compstruct.2023.117746