| JOURNAL OF COMPUTATIONAL PHYSICS | 卷:417 |
| Topology optimization of thermal fluid?structure systems using body-fitted meshes and parallel computing | |
| Article | |
| Feppon, F.1,2  Allaire, G.1  Dapogny, C.3  Jolivet, P.4  | |
| [1] Ecole Polytech, Ctr Math Appl, Palaiseau, France | |
| [2] Safran Tech, Magny Les Hameaux, France | |
| [3] Univ Grenoble Alpes, CNRS, Grenoble INP, LJK, F-38000 Grenoble, France | |
| [4] CNRS, IRIT, Toulouse, France | |
| 关键词: Shape and topology optimization; Fluid-structure interaction; Convective heat transfer; Aerodynamic design; Mesh adaptation; Distributed computing; | |
| DOI : 10.1016/j.jcp.2020.109574 | |
| 来源: Elsevier | |
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【 摘 要 】
An efficient framework is described for the shape and topology optimization of realistic three-dimensional, weakly-coupled fluid-thermal-mechanical systems. At the theoretical level, the proposed methodology relies on the boundary variation of Hadamard for describing the sensitivity of functions with respect to the domain. From the numerical point of view, three key ingredients are used: (i) a level set based mesh evolution method allowing to describe large deformations of the shape while maintaining an adapted, highquality mesh of the latter at every stage of the optimization process; (ii) an efficient constrained optimization algorithm which is very well adapted to the infinite-dimensional shape optimization context; (iii) efficient preconditioning techniques for the solution of large finite element systems in a reasonable computational time. The performance of our strategy is illustrated with two examples of coupled physics: respectively fluid-structure interaction and convective heat transfer. Before that, we perform three other test cases, involving a single physics (structural, thermal and aerodynamic design), for comparison purposes and for assessing our various tools: in particular, they prove the ability of the mesh evolution technique to capture very thin bodies or shells in 3D. (c) 2020 Elsevier Inc. All rights reserved.
【 授权许可】
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【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| 10_1016_j_jcp_2020_109574.pdf | 25234KB |
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