Affiliation:
1. Life Fellow ASME
2. Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556
Abstract
The use of artificial neural network (ANN), as one of the artificial intelligence methodologies, in a variety of real-world applications has been around for some time. However, the application of ANN to thermal science and engineering is still relatively new, but is receiving ever-increasing attention in recent published literature. Such attention is due essentially to special requirement and needs of the field of thermal science and engineering in terms of its increasing complexity and the recognition that it is not always feasible to deal with many critical problems in this field by the use of traditional analysis. The purpose of the present review is to point out the recent advances in ANN and its successes in dealing with a variety of important thermal problems. Some current ANN shortcomings, the development of recent advances in ANN-based hybrid analysis, and its future prospects will also be indicated.
Subject
Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science
Cited by
88 articles.
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