Utilization of Artificial Neural Networks in the Context of Materials Selection for Thermofluid Design

被引：14

作者：

Belanger, Simon ^{[1
]}

Gosselin, Louis ^{[1
]}

机构：

[1] Univ Laval, Dept Genie Mecan, Quebec City, PQ G1V 0A6, Canada

来源：

NUMERICAL HEAT TRANSFER PART A-APPLICATIONS | 2009年 / 55卷 / 09期

基金：

加拿大自然科学与工程研究理事会;

关键词：

LAYERED POROUS-MEDIA; GENETIC ALGORITHM; HEAT SINK; TEMPERATURE; OPTIMIZATION; THICKNESS;

D O I：

10.1080/10407780902925515

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

In this article, we use artificial neural networks (ANNs) to approximate the design space of heat transfer problems involving several choices of materials. The approximations provided by ANNs are used with genetic algorithms (GAs) to optimize the systems. Three test cases with multilayer structures are studied: 1) layered porous media heat sink, 2) finned heat sink, and 3) exterior building wall. Important computational time savings are reported compared to optimizations with GAs that rely on direct simulations. Optimal or nearly optimal designs have been identified in each case.

引用

页码：825 / 844

页数：20

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