Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm
Efficient energy conversion and utilization remain paramount in addressing the growing energy demand and environmental concerns. Concentrating photovoltaic thermal (CPVT) systems have emerged as promising solutions by integrating photovoltaic (PV) cells with thermal components for simultaneous elect...
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Elsevier Ltd
2025
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| author | Wang G. Paw J.K.S. Pasupuleti J. Yaw C.T. Yusaf T. Abdalla A.N. Cai Y. |
| author2 | 58839436200 |
| author_facet | 58839436200 Wang G. Paw J.K.S. Pasupuleti J. Yaw C.T. Yusaf T. Abdalla A.N. Cai Y. |
| author_sort | Wang G. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Efficient energy conversion and utilization remain paramount in addressing the growing energy demand and environmental concerns. Concentrating photovoltaic thermal (CPVT) systems have emerged as promising solutions by integrating photovoltaic (PV) cells with thermal components for simultaneous electricity and heat generation. In this paper, we propose the application of the Boosted Regression Tree (BRT) algorithm to predict the entropy generation rate in a CPVT system equipped with a perforated twisted tube turbulator. Brief introduction of numerical analysis of local and global rates of frictional (S?fr) and thermal (S?th) irreversibilities in a CPVT system equipped with a perforated twisted tube turbulator. The results approve the efficacy of the BRT algorithm in predicting the entropy generation rate. Through comprehensive simulations and data analysis, we establish a predictive model that considers factors such as solar irradiance, fluid flow rate, tube geometry, and turbulator characteristics. The BRT model exhibits remarkable accuracy in capturing the nuanced interplay of these factors, enabling reliable estimations of entropy generation rate. ? 2023 |
| format | Article |
| id | my.uniten.dspace-37203 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Elsevier Ltd |
| record_format | dspace |
| spelling | my.uniten.dspace-372032025-03-03T15:48:37Z Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm Wang G. Paw J.K.S. Pasupuleti J. Yaw C.T. Yusaf T. Abdalla A.N. Cai Y. 58839436200 58168727000 11340187300 36560884300 23112065900 25646071000 58787406000 Entropy Flow of fluids Regression analysis Solar power generation Trees (mathematics) Boosted regression trees Concentrating photovoltaic Energy Energy demands Entropy generation Entropy generation rate Environmental concerns Photovoltaic/thermal systems Regression tree algorithms Turbulators Solar energy Efficient energy conversion and utilization remain paramount in addressing the growing energy demand and environmental concerns. Concentrating photovoltaic thermal (CPVT) systems have emerged as promising solutions by integrating photovoltaic (PV) cells with thermal components for simultaneous electricity and heat generation. In this paper, we propose the application of the Boosted Regression Tree (BRT) algorithm to predict the entropy generation rate in a CPVT system equipped with a perforated twisted tube turbulator. Brief introduction of numerical analysis of local and global rates of frictional (S?fr) and thermal (S?th) irreversibilities in a CPVT system equipped with a perforated twisted tube turbulator. The results approve the efficacy of the BRT algorithm in predicting the entropy generation rate. Through comprehensive simulations and data analysis, we establish a predictive model that considers factors such as solar irradiance, fluid flow rate, tube geometry, and turbulator characteristics. The BRT model exhibits remarkable accuracy in capturing the nuanced interplay of these factors, enabling reliable estimations of entropy generation rate. ? 2023 Final 2025-03-03T07:48:37Z 2025-03-03T07:48:37Z 2024 Article 10.1016/j.csite.2023.103729 2-s2.0-85181073956 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181073956&doi=10.1016%2fj.csite.2023.103729&partnerID=40&md5=c400b3771de014341cff7b06c6997dfa https://irepository.uniten.edu.my/handle/123456789/37203 53 103729 All Open Access; Gold Open Access; Green Open Access Elsevier Ltd Scopus |
| spellingShingle | Entropy Flow of fluids Regression analysis Solar power generation Trees (mathematics) Boosted regression trees Concentrating photovoltaic Energy Energy demands Entropy generation Entropy generation rate Environmental concerns Photovoltaic/thermal systems Regression tree algorithms Turbulators Solar energy Wang G. Paw J.K.S. Pasupuleti J. Yaw C.T. Yusaf T. Abdalla A.N. Cai Y. Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm |
| title | Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm |
| title_full | Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm |
| title_fullStr | Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm |
| title_full_unstemmed | Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm |
| title_short | Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm |
| title_sort | predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using boosted regression tree algorithm |
| topic | Entropy Flow of fluids Regression analysis Solar power generation Trees (mathematics) Boosted regression trees Concentrating photovoltaic Energy Energy demands Entropy generation Entropy generation rate Environmental concerns Photovoltaic/thermal systems Regression tree algorithms Turbulators Solar energy |
| url_provider | http://dspace.uniten.edu.my/ |