Numerical Simulation and Designing Artificial Neural Network for Water-Diamond Nanofluid Flow for Micro-Scale Cooling of Medical Equipment

Abstract

Simultaneous using of MEMS (Micro Electro Mechanical Systems) and nanotechnology systems in the cooling of micro-scale electrical equipment has attracted researchers in recent years. In the present study, cooling of medical equipment with electronic board is discussed. For this purpose, water and water-diamond nanofluid with a volume fraction of 1%, 2%, 3% and 4% are used as a coolant of micro-scale cooling system. Coolants are pumped into heat sink at pressures of 5, 15, 25 and 35 kPa. The electronic chip on the board is embedded in the base plate of heat sink and generates uniform heat flux of 85kW/m2. The governing equations have been solved using finite volume method based on finite element. The results show that utilizing water-diamond nanofluid compared to water improves the cooling process so that utilizing water-diamond nanofluid with volume fraction of 4% improves the cooling process between 4.46% and 7.22%. Moreover, increasing pressure drop from 5 kPa to 35 kPa improves cooling indexes between 17.86% and 25.52%. Moreover, designing radial basis function artificial neural network shows good agreement between numerical simulation and predicted results.