The Cut-Cell Method for the Conjugate Heat Transfer Topology Optimization of Turbulent Flows Using the "Think Discrete-Do Continuous" Adjoint

被引:0
|
作者
Galanos, Nikolaos [1 ]
Papoutsis-Kiachagias, Evangelos M. [1 ]
Giannakoglou, Kyriakos C. [1 ]
机构
[1] Natl Tech Univ Athens, Sch Mech Engn, Parallel CFD & Optimizat Unit PCOpt, Athens 15772, Greece
关键词
topology optimization; turbulent flow; conjugate heat transfer; cut-cell method; continuous adjoint; primal-adjoint consistency; LEVEL SET TOPOLOGY; SHAPE OPTIMIZATION; DESIGN;
D O I
10.3390/en17081817
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents a topology optimization (TopO) method for conjugate heat transfer (CHT), with turbulent flows. Topological changes are controlled by an artificial material distribution field (design variables), defined at the cells of a background grid and used to distinguish a fluid from a solid material. To effectively solve the CHT problem, it is crucial to impose exact boundary conditions at the computed fluid-solid interface (FSI); this is the purpose of introducing the cut-cell method. On the grid, including also cut cells, the incompressible Navier-Stokes equations, coupled with the Spalart-Allmaras turbulence model with wall functions, and the temperature equation are solved. The continuous adjoint method computes the derivatives of the objective function(s) and constraints with respect to the material distribution field, starting from the computation of derivatives with respect to the positions of nodes on the FSI and then applying the chain rule of differentiation. In this work, the continuous adjoint PDEs are discretized using schemes that are consistent with the primal discretization, and this will be referred to as the "Think Discrete-Do Continuous" (TDDC) adjoint. The accuracy of the gradient computed by the TDDC adjoint is verified and the proposed method is assessed in the optimization of two 2D cases, both in turbulent flow conditions. The performance of the TopO designs is investigated in terms of the number of required refinement steps per optimization cycle, the Reynolds number of the flow, and the maximum allowed power dissipation. To illustrate the benefits of the proposed method, the first case is also optimized using a density-based TopO that imposes Brinkman penalization terms in solid areas, and comparisons are made.
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页数:25
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