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Optimization, Modeling of Thermal Conductivity and Viscosity of Cu/Engine Oil Nanofluids by NSGA-II Using RSM
  • Mohammad Hemmat Esfe,
  • Sayyid Majid Motallebi
Mohammad Hemmat Esfe
Imam Hossein University
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Sayyid Majid Motallebi
Imam Hossein University
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Peer review status:IN REVISION

22 Jun 2020Submitted to Mathematical Methods in the Applied Sciences
27 Jun 2020Assigned to Editor
27 Jun 2020Submission Checks Completed
29 Jun 2020Reviewer(s) Assigned
11 Jul 2020Review(s) Completed, Editorial Evaluation Pending
13 Jul 2020Editorial Decision: Revise Major


This study provides the optimization of thermophysical properties of Cu/engine oil nanofluid. In this optimization, the objective functions were determined with the experimental data of viscosity and TC of nanofluid using RSM. Two equations for predicting thermal conductivity (TC) and viscosity data were presented which can accurately predict these properties. The NSGA-II method was used for multi-objective optimization (Mo-O) and Pareto’s front was introduced to study optimal viscosity and TC responses. According to the results, the highest TC and the lowest viscosity occurs when the temperature and solid volume fraction (SVF) of the nanoparticle are at their maximum values. Among the results, those with the highest TC and the lowest viscosity are referred to as optimal points.