Abstract
The use of nanofluids as coolant fluid in the microchannel heat sink (MCHS) is an effective technique for improving the thermal performance of electronic devices. A comparative study is performed with the help of a multi-objective genetic algorithm (MOGA) to find the optimal geometric variables of the MCHS and choose the appropriate nanofluid. For that purpose, four practical nanofluids, including Al2O3-water, Cu-water, SiO2-water, and carbon nanotube (CNT)-water, are thoroughly investigated. Simultaneously minimization of the total thermal resistance and pumping power consumption (POW) are considered as the optimization goal, and the MOGA is employed to achieve the optimal solution. To check the accuracy of the thermal resistance modeling and assessing the optimization algorithm, several case studies with a different number of optimization variables are defined to investigate the capability of the algorithm in finding the soptimal microchannel design variables and choosing the suitable nanofluid. The optimization variables consist of the channel aspect and wall ratios, base thickness, nanoparticles volume concentration, nanoparticles diameter, and the volume flow rate. Compared to other nanofluids, CNT provides better thermal performance. Furthermore, increasing the volume concentration of nanoparticles enhances thermal performance, which can also be achieved through the reduction of nanoparticles diameter.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
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Hamid Fazeli
Hamid Fazeli received his B.S. in Mechanical Engineering from University of Kerman, Iran. He then received his M.S. in Aerospace Engineering from Khajeh-Nasir Toosi University of Technology in Tehran, Iran. He worked as a research engineer and senior mechanical engineer in different industries for more than ten years. He is currently a graduate research assistant at Oregon State University, Corvallis, OR, USA. His research interests include thermal system design and optimization, combustion, and wildland fire.
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Abolfazl Pourrajabian
Abolfazl Pourrajabian received his B.S. in Mechanical Engineering from University of Kerman, Iran. Then, he obtained his M.S. in Aerospace Engineering from Khajeh-Nasir Toosi University of Technology, Tehran, Iran. Following that, he pursued his Ph.D. in the wind energy field at the same university. His main field of research is the aerodynamics of wind turbines and especially the geometric design and optimization of horizontal axis wind turbine blades.
Elnaz Nikooei
Elnaz Nikooei graduated in Energy Systems Engineering from Sharif University of Technology in Tehran, Iran. She has a background in Chemical Engineering and more than three years of work experience in the energy industry. She has experience in wastewater treatment, air quality modeling, and applying intelligent systems in optimization and forecasting problems. She is currently a Ph.D. student in mechanical engineering at Oregon State University, Corvallis, OR, USA. Her research interests include separation processes, wastewater treatment, heat transfer, and phase change.