Determination of thermal conductivity ratio of CuO/ethylene glycol nanofluid by connectionist approach

• Published in: Journal of the Taiwan Institute of Chemical Engineers 2018-10, Vol.91, p.383-395
• Main Authors: Ahmadi, Mohammad-Ali, Ahmadi, Mohammad Hossein, Fahim Alavi, Morteza, Nazemzadegan, Mohammad Reza, Ghasempour, Roghayeh, Shamshirband, Shahaboddin
• Format: Article
• Language: English
• Subjects: Ethylen glycol; Modeling; Nanofluid; Thermal conductivity
• ISSN: 1876-1070; 1876-1089
• DOI: 10.1016/j.jtice.2018.06.003

•Developing a robust deterministic tools for determination of Thermal conductivity of nanofluids.•Suggests the predictive model based on least square support vector machine (LSSVM) calculate Thermal conductivity of nanofluids.•Analysis of variance was performed on the data samples.•Genetic algorithm (GA) is employed to optimize hyperparameters (γ and σ2) of LSSVM model. Thermal conductivity of nanofluids plays key rol in heat transfer capacity of fluids. adding nanoparticles to a base fluid can lead to enhancement in thermal conductivty ratio. CuO/Ethyle Glycol (EG) is one of the most applicable nanofluids for heat transfer purposes. In the present study, thermal conductivty ratio of CuO/EG nanofluid is modeled by applying Group Method of Data Hnadling and Least Square Support Vector Machine – Gentic Algorithm approaches. Results indicated that the utilized model are very accurate in predicting thermal conductivty ratio of the nanofluid. The R-squared values for the proposed model are equal to 0.994 and 0.991 by applying Group Method of Data Handling and Least Square Support Vector Machine – Gentic Algorithm approaches, Respectivly. The relative importance of investigated parameters, temperature, size and concentration obtained 57%, 26% and 17%, respectively. [Display omitted]