数学优化
各向同性
绝热过程
帕累托原理
多目标优化
拓扑优化
数学
渐近线
灵敏度(控制系统)
参数化(大气建模)
应用数学
拓扑(电路)
计算机科学
有限元法
数学分析
热力学
物理
工程类
组合数学
辐射传输
量子力学
电子工程
作者
Gilles Marck,Maroun Nemer,J.‐L. Harion,Serge Russeil,Daniel Bougeard
标识
DOI:10.1080/10407790.2012.687979
摘要
The efficient cooling of a finite-size volume generating heat, including adiabatic boundary conditions with the exception of a small heat sink, poses the problem of optimal allocation of high-conductivity material. Among the structural optimization methods, this article couples solid isotropic material with penalization parametrization (SIMP) with an aggregated objective function approach (AOF) to tackle this topology optimization problem through a multiobjective strategy. Both average and variance temperature-reduction problems is solved by the identification of Pareto fronts, which are highly dependent on the quantity of the high-conductivity material. This study also underlines the link between the sensitivity analysis of both objective functions, which is required by the method of moving asymptotes (MMA). Furthermore, additional calculations have been done to include variations in heat-generation rate between two conductive materials by means of an additional penalization strategy. The main conclusion deals with the possibility of finding an acceptable trade-off between average and variance objective functions thanks to the convex shape of Pareto frontiers.
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