Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique
This paper presents the fuzzy logic expert system (FLES) for heat transfer performance investigation in helically coiled heat exchanger with spirally corrugated wall operated with water and CuO/water nanofluids. Compared with traditional logic model, fuzzy logic is more efficient in connecting the m...
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2014
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my.um.eprints.106832014-06-24T06:31:02Z http://eprints.um.edu.my/10683/ Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique Khairul, M.A. Hossain, A. Saidur, R. Alim, M.A. TJ Mechanical engineering and machinery This paper presents the fuzzy logic expert system (FLES) for heat transfer performance investigation in helically coiled heat exchanger with spirally corrugated wall operated with water and CuO/water nanofluids. Compared with traditional logic model, fuzzy logic is more efficient in connecting the multiple units to a single output and is invaluable supplements to classical hard computing techniques. Hence, the main objective of this analysis is to investigate the relationship between heat exchanger working parameters and performance characteristics, and to determine how fuzzy logic expert system plays a significant role in prediction of heat transfer performance. Analytical values are taken in helically coiled heat exchanger with spirally corrugated wall operated with water and CuO/water nanofluids for investigation of heat transfer performance. The heat transfer coefficients of CuO/water nanofluids significantly increased about 5.90-14.24 with the increase of volume concentrations compared to water and while the values of the friction factor decreased with the increase in volume flow rate and volume concentration by using nanofluid instead of water. A fuzzy logic expert system model has developed for the prediction of heat transfer coefficient and friction factor. Verification of the developed fuzzy logic model was carried out through various numerical error criteria. For all parameters, the relative error of predicted values are found to be less than and/or slightly above the acceptable limit (5). The goodnesses of fit of the prediction values from the fuzzy logic expert system model are found to be close to 1.0 as expected, and hence demonstrated the good performance of the developed system. © 2014 Elsevier Ltd. Elsevier Ltd 2014 Article PeerReviewed Khairul, M.A. and Hossain, A. and Saidur, R. and Alim, M.A. (2014) Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique. Computers and Fluids, 100. pp. 123-129. ISSN 00457930 http://www.scopus.com/inward/record.url?eid=2-s2.0-84901981337&partnerID=40&md5=e99eb6afa2335a1928fbd83758ab7822 10.1016/j.compfluid.2014.05.007 |
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TJ Mechanical engineering and machinery Khairul, M.A. Hossain, A. Saidur, R. Alim, M.A. Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| description |
This paper presents the fuzzy logic expert system (FLES) for heat transfer performance investigation in helically coiled heat exchanger with spirally corrugated wall operated with water and CuO/water nanofluids. Compared with traditional logic model, fuzzy logic is more efficient in connecting the multiple units to a single output and is invaluable supplements to classical hard computing techniques. Hence, the main objective of this analysis is to investigate the relationship between heat exchanger working parameters and performance characteristics, and to determine how fuzzy logic expert system plays a significant role in prediction of heat transfer performance. Analytical values are taken in helically coiled heat exchanger with spirally corrugated wall operated with water and CuO/water nanofluids for investigation of heat transfer performance. The heat transfer coefficients of CuO/water nanofluids significantly increased about 5.90-14.24 with the increase of volume concentrations compared to water and while the values of the friction factor decreased with the increase in volume flow rate and volume concentration by using nanofluid instead of water. A fuzzy logic expert system model has developed for the prediction of heat transfer coefficient and friction factor. Verification of the developed fuzzy logic model was carried out through various numerical error criteria. For all parameters, the relative error of predicted values are found to be less than and/or slightly above the acceptable limit (5). The goodnesses of fit of the prediction values from the fuzzy logic expert system model are found to be close to 1.0 as expected, and hence demonstrated the good performance of the developed system. © 2014 Elsevier Ltd. |
| format |
Article |
| author |
Khairul, M.A. Hossain, A. Saidur, R. Alim, M.A. |
| author_facet |
Khairul, M.A. Hossain, A. Saidur, R. Alim, M.A. |
| author_sort |
Khairul, M.A. |
| title |
Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| title_short |
Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| title_full |
Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| title_fullStr |
Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| title_full_unstemmed |
Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| title_sort |
prediction of heat transfer performance of cuo/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique |
| publisher |
Elsevier Ltd |
| publishDate |
2014 |
| url |
http://eprints.um.edu.my/10683/ http://www.scopus.com/inward/record.url?eid=2-s2.0-84901981337&partnerID=40&md5=e99eb6afa2335a1928fbd83758ab7822 |
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