An Artificial Neural Network Approach to Cooling Analysis of Electronic Components in Enclosures Filled With Nanofluids-Reference-Cited by-同舟云学术

An Artificial Neural Network Approach to Cooling Analysis of Electronic Components in Enclosures Filled With Nanofluids

Published:2011-03-01 Issue:1 Volume:133 Page:
ISSN:1043-7398
Container-title:Journal of Electronic Packaging
language:en
Short-container-title:

Author:

Kargar A.¹,Ghasemi B.¹,Aminossadati S. M.²

Affiliation:

1. Engineering Faculty, Shahrekord University, P.O. Box 115, Shahrekord, Iran

2. School of Mechanical and Mining Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia

Abstract

Computational fluid dynamics (CFD) and artificial neural network (ANN) are used to examine the cooling performance of two electronic components in an enclosure filled with a Cu-water nanofluid. The heat transfer within the enclosure is due to laminar natural convection between the heated electronic components mounted on the left and right vertical walls with a relatively lower temperature. The results of a CFD simulation are used to train and validate a series of ANN architectures, which are developed to quickly and accurately carry out this analysis. A comparison study between the results from the CFD simulation and the ANN analysis indicates that the ANN accurately predicts the cooling performance of electronic components within the given range of data.

Publisher

ASME International

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Electronic, Optical and Magnetic Materials

Link

http://asmedigitalcollection.asme.org/electronicpackaging/article-pdf/doi/10.1115/1.4003215/5884824/011010_1.pdf

Reference33 articles.

1. Applications of Nanofluids: Current and Future;Wong;Advances in Mechanical Engineering

2. Thermophysical and Electrokinetic Properties of Nanofluids—A Critical Review;Murshed;Appl. Therm. Eng.

3. Natural Convection Heat Transfer Enhancement in Horizontal Concentric Annuli Using Nanofluids;Abu-Nada;Int. Commun. Heat Mass Transfer

4. Buoyancy-Driven Heat Transfer Enhancement in a Two-Dimensional Enclosure Utilizing Nanofluids;Khanafer;Int. J. Heat Mass Transfer

5. Numerical Study of Natural Convection in Partially Heated Rectangular Enclosures Filled With Nanofluids;Oztop;Int. J. Heat Fluid Flow

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep encoder–decoder hierarchical convolutional neural networks for conjugate heat transfer surrogate modeling;Applied Energy;2024-10

2. A Comprehensive Review of Electronic Cooling Technologies in Harsh Field Environments: Obstacles, Progress, and Prospects;Journal of Mines, Metals and Fuels;2024-09-04

3. Performance and prediction of baffled cold plate based battery thermal management system;Applied Thermal Engineering;2023-01

4. Effective Computational Approach for Optimization of Temperature on Printed Circuit Board;Journal of The Institution of Engineers (India): Series C;2022-02-08

5. Temperature prediction of heat sources using machine learning techniques;Heat Transfer;2021-07-22