Publication:
Using ANFIS technique for prediction of heat transfer in vertical solar chimney

datacite.subject.fos oecd::Engineering and technology
dc.contributor.author Y. Q. Nguyen
dc.contributor.author Thinh N. Doan
dc.contributor.author Minh-Thu T. Huynh
dc.date.accessioned 2022-11-22T00:52:56Z
dc.date.available 2022-11-22T00:52:56Z
dc.date.issued 2021
dc.description.abstract Numerical simulations have been widely employed in buildings, particularly for prediction of natural ventilation. The Computational Fluid Dynamics (CFD) has been utilized successfully for prediction of the airflow and heat transfer in solar chimney, one of the common devices for natural ventilation. However, CFD requires expensive computational resources. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model was tested for quick prediction of the heat transfer in a vertical solar chimney based on the data provided by a CFD model. The Nusselt number in solar chimneys at different heights and heat flux were predicted with the CFD model. The generated data were used to train two ANFIS models which were then validated with the remaining CFD data. The results show that the ANFIS models can predict the Nusselt number and mass flow rate with the maximum discrepancy between the two results of less than 5.0%
dc.identifier.doi 10.1063/5.0066555
dc.identifier.uri http://repository.vlu.edu.vn:443/handle/123456789/1494
dc.language.iso en_US
dc.relation.ispartof 1ST VAN LANG INTERNATIONAL CONFERENCE ON HERITAGE AND TECHNOLOGY CONFERENCE PROCEEDING, 2021: VanLang-HeriTech, 2021
dc.relation.ispartof AIP Conference Proceedings
dc.relation.issn 0094-243X
dc.subject "Artificial intelligence
dc.subject Heat transfer
dc.subject Computational fluid dynamics
dc.subject Fluid flows"
dc.title Using ANFIS technique for prediction of heat transfer in vertical solar chimney
dc.type proceedings-article
dspace.entity.type Publication
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