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...

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Main Authors: Yaw, Chong Tak, Koh, Siaw Paw, Sandhya, Madderla, Ramasamy, Devarajan, Kadirgama, Kumaran, Benedict, Foo, Kharuddin, Ali, Tiong, Sieh Kiong, Abdalla, Ahmed N., Chong, Kok Hen
Format: Article
Language:English
Published: MDPI AG 2023
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/38335/
http://umpir.ump.edu.my/id/eprint/38335/1/An%20Approach%20for%20the%20optimization%20of%20thermal%20conductivity%20and%20viscosity.pdf
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author Yaw, Chong Tak
Koh, Siaw Paw
Sandhya, Madderla
Ramasamy, Devarajan
Kadirgama, Kumaran
Benedict, Foo
Kharuddin, Ali
Tiong, Sieh Kiong
Abdalla, Ahmed N.
Chong, Kok Hen
author_facet Yaw, Chong Tak
Koh, Siaw Paw
Sandhya, Madderla
Ramasamy, Devarajan
Kadirgama, Kumaran
Benedict, Foo
Kharuddin, Ali
Tiong, Sieh Kiong
Abdalla, Ahmed N.
Chong, Kok Hen
author_sort Yaw, Chong Tak
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.
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institution Universiti Malaysia Pahang
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publishDate 2023
publisher MDPI AG
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spelling ump-383352023-08-28T05:14:07Z http://umpir.ump.edu.my/id/eprint/38335/ An Approach for the optimization of thermal conductivity and viscosity of hybrid (Graphene Nanoplatelets, GNPs : Cellulose Nanocrystal, CNC) nanofluids using Response Surface Methodology (RSM) Yaw, Chong Tak Koh, Siaw Paw Sandhya, Madderla Ramasamy, Devarajan Kadirgama, Kumaran Benedict, Foo Kharuddin, Ali Tiong, Sieh Kiong Abdalla, Ahmed N. Chong, Kok Hen T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics 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 2023-05 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/38335/1/An%20Approach%20for%20the%20optimization%20of%20thermal%20conductivity%20and%20viscosity.pdf Yaw, Chong Tak and Koh, Siaw Paw and Sandhya, Madderla and Ramasamy, Devarajan and Kadirgama, Kumaran and Benedict, Foo and Kharuddin, Ali and Tiong, Sieh Kiong and Abdalla, Ahmed N. and Chong, Kok Hen (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 (1596). 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)
TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
Yaw, Chong Tak
Koh, Siaw Paw
Sandhya, Madderla
Ramasamy, Devarajan
Kadirgama, Kumaran
Benedict, Foo
Kharuddin, Ali
Tiong, Sieh Kiong
Abdalla, Ahmed N.
Chong, Kok Hen
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)
TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
url http://umpir.ump.edu.my/id/eprint/38335/
http://umpir.ump.edu.my/id/eprint/38335/
http://umpir.ump.edu.my/id/eprint/38335/
http://umpir.ump.edu.my/id/eprint/38335/1/An%20Approach%20for%20the%20optimization%20of%20thermal%20conductivity%20and%20viscosity.pdf