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Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity

Heat transfer behavior in a 2-D square lid-driven cavity has been studied for various pertinent Reynolds and Rayleigh numbers. The lattice Boltzmann method, a numerical tool based on the particle distribution function is applied to simulate a thermal fluid flow problem. Bhatnagar-Gross-Krook (BGK) i...

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Main Authors: Che Sidik, Nor Azwadi, Zeinali, Mohammadjavad, Safdari, Arman, Kazemi, Alieh
格式: Article
出版: Taylor and Francis Group 2013
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TJ Mechanical engineering and machinery
在線閱讀:http://eprints.utm.my/id/eprint/50505/
http://dx.doi.org/10.1080/10407782.2013.757154
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spelling my.utm.505052018-10-14T08:37:00Z http://eprints.utm.my/id/eprint/50505/ Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity Che Sidik, Nor Azwadi Zeinali, Mohammadjavad Safdari, Arman Kazemi, Alieh TJ Mechanical engineering and machinery Heat transfer behavior in a 2-D square lid-driven cavity has been studied for various pertinent Reynolds and Rayleigh numbers. The lattice Boltzmann method, a numerical tool based on the particle distribution function is applied to simulate a thermal fluid flow problem. Bhatnagar-Gross-Krook (BGK) is combined with the double population thermal Lattice Boltzmann model to solve mixed convection in a square cavity. An adaptive-network-based fuzzy inference system (ANFIS) method is trained and validated using BGK Lattice Boltzmann model results. The results show that the trained ANFIS model successfully predicts the temperature and flow fields in a few seconds with acceptable accuracy Taylor and Francis Group 2013 Article PeerReviewed Che Sidik, Nor Azwadi and Zeinali, Mohammadjavad and Safdari, Arman and Kazemi, Alieh (2013) Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity. Numerical Heat Transfer Part A-Applications, 63 (12). pp. 906-920. ISSN 1040-7782 http://dx.doi.org/10.1080/10407782.2013.757154 DOI: 10.1080/10407782.2013.757154
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Che Sidik, Nor Azwadi
Zeinali, Mohammadjavad
Safdari, Arman
Kazemi, Alieh
Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
description Heat transfer behavior in a 2-D square lid-driven cavity has been studied for various pertinent Reynolds and Rayleigh numbers. The lattice Boltzmann method, a numerical tool based on the particle distribution function is applied to simulate a thermal fluid flow problem. Bhatnagar-Gross-Krook (BGK) is combined with the double population thermal Lattice Boltzmann model to solve mixed convection in a square cavity. An adaptive-network-based fuzzy inference system (ANFIS) method is trained and validated using BGK Lattice Boltzmann model results. The results show that the trained ANFIS model successfully predicts the temperature and flow fields in a few seconds with acceptable accuracy
format Article
author Che Sidik, Nor Azwadi
Zeinali, Mohammadjavad
Safdari, Arman
Kazemi, Alieh
author_facet Che Sidik, Nor Azwadi
Zeinali, Mohammadjavad
Safdari, Arman
Kazemi, Alieh
author_sort Che Sidik, Nor Azwadi
title Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
title_short Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
title_full Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
title_fullStr Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
title_full_unstemmed Adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
title_sort adaptive-network-based fuzzy inference system analysis to predict the temperature and flow fields in a lid-driven cavity
publisher Taylor and Francis Group
publishDate 2013
url http://eprints.utm.my/id/eprint/50505/
http://dx.doi.org/10.1080/10407782.2013.757154
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score 13.251813

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