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Modelling and optimisation of thermophysical properties and convective heat transfer of nanofluids by using artificial intelligence methods
Thesis (PhD)--University of Pretoria, 2015.
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| Format: | Thesis |
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University of Pretoria
2015
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| _version_ | 1867613531260583936 |
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| access_status_str | Open Access |
| author2 | Sharifpur, Mohsen |
| author_browse | Sharifpur, Mohsen |
| author_facet | Sharifpur, Mohsen |
| collection | Thesis |
| dc_rights_str_mv | © 2015 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD)--University of Pretoria, 2015. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/45962 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:37.672Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/45962 Modelling and optimisation of thermophysical properties and convective heat transfer of nanofluids by using artificial intelligence methods Sharifpur, Mohsen Meyer, Josua P. Mehrabi, M. UCTD Nanofluids Thermophysical properties Convective heat transfer Artificial intelligence methods Thermal conductivity Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production Thesis (PhD)--University of Pretoria, 2015. Nanofluids are modern heat transfer fluids which can significantly increase the thermal performance of a thermal system. It enhances the thermal conductivity of working fluids due to adding solid nanoparticles to the base fluid. In order to use nanofluids widely in industrial applications knowing the thermophysical properties of these new heat transfer fluids are essential. In this research, the GA-PNN and FCMANFIS methods are employed to present models for thermophysical properties of nanofluids. Furthermore, modified NSGA-II technique has been used to optimise the convective heat transfer of nanofluids in a turbulent flow regime. In recent years considerable correlations have been suggested by different researchers for thermophysical properties of nanofluids based on the experimental and theoretical works, which a large number of those correlations are failed to predict the thermophysical properties of nanofluids for a wide range of particle size, temperature and nanoparticle volume concentrations. In this thesis, experimental data available in literature have been used to propose models for thermophysical properties of nanofluids to overcome this problem by using artificial intelligencebased techniques. Two models based on FCM-ANFIS and GA-PNN techniques have been proposed for the thermal conductivity and viscosity of nanofluids. To show the accuracy of the proposed models, the predicted result has been compared with experimental data as well as well-cited correlations in literature. Furthermore, the convective heat transfer of nanofluids was studied and different models based on artificial intelligence techniques have been proposed to model the Nusselt number and pressure drop of nanofluids in a turbulent regime. Finally, a multi-objective optimisation technique was used to optimise the convective heat transfer characteristics and pressure drop of nanofluids to find the best design point base on the Pareto front of the results. The predictions of the models for all cases agreed with the experimental data much better than the available correlations. tm2015 mi2025 Mechanical and Aeronautical Engineering PhD Unrestricted SDG-07: Affordable and clean energy SDG-09: Industry, innovation and infrastructure SDG-12: Responsible consumption and production 2015-07-02T11:06:11Z 2015-07-02T11:06:11Z 2015/04/23 2015 Thesis Mehrabi, M 2015, Modelling and optimisation of thermophysical properties and convective heat transfer of nanofluids by using artificial intelligence methods, PhD Thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/45962> A2015 http://hdl.handle.net/2263/45962 en © 2015 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Nanofluids Thermophysical properties Convective heat transfer Artificial intelligence methods Thermal conductivity Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production Modelling and optimisation of thermophysical properties and convective heat transfer of nanofluids by using artificial intelligence methods |
| title | Modelling and optimisation of thermophysical properties and
convective heat transfer of nanofluids by using artificial
intelligence methods |
| title_full | Modelling and optimisation of thermophysical properties and
convective heat transfer of nanofluids by using artificial
intelligence methods |
| title_fullStr | Modelling and optimisation of thermophysical properties and
convective heat transfer of nanofluids by using artificial
intelligence methods |
| title_full_unstemmed | Modelling and optimisation of thermophysical properties and
convective heat transfer of nanofluids by using artificial
intelligence methods |
| title_short | Modelling and optimisation of thermophysical properties and
convective heat transfer of nanofluids by using artificial
intelligence methods |
| title_sort | modelling and optimisation of thermophysical properties and convective heat transfer of nanofluids by using artificial intelligence methods |
| topic | UCTD Nanofluids Thermophysical properties Convective heat transfer Artificial intelligence methods Thermal conductivity Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production |
| url | http://hdl.handle.net/2263/45962 |