An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM)
Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanopartic...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/44516/ http://umpir.ump.edu.my/id/eprint/44516/1/An%20approach%20for%20the%20optimization%20of%20thermal%20conductivity.pdf |
| _version_ | 1848827119949316096 |
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| author | Chong, Tak Yaw Siaw, Paw Koh Sandhya, Madderla Ramasamy, Devarajan Kadirgama, Kumaran Benedict, Foo Kharuddin, Ali Sieh, Kiong Tiong Abdalla, Ahmed N. Kok, Hen Chong |
| author_facet | Chong, Tak Yaw Siaw, Paw Koh Sandhya, Madderla Ramasamy, Devarajan Kadirgama, Kumaran Benedict, Foo Kharuddin, Ali Sieh, Kiong Tiong Abdalla, Ahmed N. Kok, Hen Chong |
| author_sort | Chong, Tak Yaw |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanoparticles in the base fluid of ethylene glycol and water (60:40). Using response surface methodology (RSM) based on central composite design (CCD) and mini tab 20 standard statistical software, the impact of temperature, volume concentration, and type of nanofluid is used to construct an empirical mathematical formula. Analysis of variance (ANOVA) is applied to determine that the developed empirical mathematical analysis is relevant. For the purpose of developing the equations, 32 experiments are conducted for second-order polynomial to the specified outputs such as thermal conductivity and viscosity. Predicted estimates and the experimental data are found to be in reasonable arrangement. In additional words, the models could expect more than 85% of thermal conductivity and viscosity fluctuations of the nanofluid, indicating that the model is accurate. Optimal thermal conductivity and viscosity values are 0.4962 W/m-K and 2.6191 cP, respectively, from the results of the optimization plot. The critical parameters are 50 °C, 0.0254%, and the category factorial is GNP/CNC, and the relevant parameters are volume concentration, temperature, and kind of nanofluid. From the results plot, the composite is 0.8371. The validation results of the model during testing indicate the capability of predicting the optimal experimental conditions. |
| first_indexed | 2025-11-15T03:55:39Z |
| format | Article |
| id | ump-44516 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:55:39Z |
| publishDate | 2023 |
| publisher | MDPI AG |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-445162025-05-29T08:31:02Z http://umpir.ump.edu.my/id/eprint/44516/ An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) Chong, Tak Yaw Siaw, Paw Koh Sandhya, Madderla Ramasamy, Devarajan Kadirgama, Kumaran Benedict, Foo Kharuddin, Ali Sieh, Kiong Tiong Abdalla, Ahmed N. Kok, Hen Chong T Technology (General) TA Engineering (General). Civil engineering (General) Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanoparticles in the base fluid of ethylene glycol and water (60:40). Using response surface methodology (RSM) based on central composite design (CCD) and mini tab 20 standard statistical software, the impact of temperature, volume concentration, and type of nanofluid is used to construct an empirical mathematical formula. Analysis of variance (ANOVA) is applied to determine that the developed empirical mathematical analysis is relevant. For the purpose of developing the equations, 32 experiments are conducted for second-order polynomial to the specified outputs such as thermal conductivity and viscosity. Predicted estimates and the experimental data are found to be in reasonable arrangement. In additional words, the models could expect more than 85% of thermal conductivity and viscosity fluctuations of the nanofluid, indicating that the model is accurate. Optimal thermal conductivity and viscosity values are 0.4962 W/m-K and 2.6191 cP, respectively, from the results of the optimization plot. The critical parameters are 50 °C, 0.0254%, and the category factorial is GNP/CNC, and the relevant parameters are volume concentration, temperature, and kind of nanofluid. From the results plot, the composite is 0.8371. The validation results of the model during testing indicate the capability of predicting the optimal experimental conditions. MDPI AG 2023 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/44516/1/An%20approach%20for%20the%20optimization%20of%20thermal%20conductivity.pdf Chong, Tak Yaw and Siaw, Paw Koh and Sandhya, Madderla and Ramasamy, Devarajan and Kadirgama, Kumaran and Benedict, Foo and Kharuddin, Ali and Sieh, Kiong Tiong and Abdalla, Ahmed N. and Kok, Hen Chong (2023) An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM). Nanomaterials, 13 (10). pp. 1-18. ISSN 2079-4991. (Published) https://doi.org/10.3390/nano13101596 https://doi.org/10.3390/nano13101596 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) Chong, Tak Yaw Siaw, Paw Koh Sandhya, Madderla Ramasamy, Devarajan Kadirgama, Kumaran Benedict, Foo Kharuddin, Ali Sieh, Kiong Tiong Abdalla, Ahmed N. Kok, Hen Chong An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) |
| title | An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) |
| title_full | An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) |
| title_fullStr | An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) |
| title_full_unstemmed | An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) |
| title_short | An approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) |
| title_sort | approach for the optimization of thermal conductivity and viscosity of hybrid (graphene nanoplatelets, gnps: cellulose nanocrystal, cnc) nanofluids using response surface methodology (rsm) |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://umpir.ump.edu.my/id/eprint/44516/ http://umpir.ump.edu.my/id/eprint/44516/ http://umpir.ump.edu.my/id/eprint/44516/ http://umpir.ump.edu.my/id/eprint/44516/1/An%20approach%20for%20the%20optimization%20of%20thermal%20conductivity.pdf |