Analysis of Microchannel Heat Sink Performance Using Nanofluids in Turbulent and Laminar Flow Regimes and Its Simulation Using Artificial Neural Network

In this study, silicon microchannel heat sink (MCHS) performance using nanofluids as coolants was analyzed. The nanofluid was a mixture of nanoscale Cu particles and pure water with various volume fractions. Based on theoretical models and experimental correlations, the heat transfer and friction coefficients required in the analysis were used. In the theoretical model, nanofluid was treated as a single-phase fluid. In the experimental correlation, thermal dispersion due to particle random motion was included. The microchannel heat sink performances for a specific geometries with Wch = Wfin = 100 µm and Lch =300 µm is examined. In this study, flow in laminar and turbulent regimes using the theoretic and experimental relations was investigated; moreover an artificial neural network (ANN) was used to simulate the MCHS having laminar flow with different circumstances and after that, the best geometry and volume fraction of nanofluid could be found based on minimum thermal resistance.