| dc.description.abstract | Artificial intelligence and machine learning systems, faster processors, miniaturized computational components, and supercomputer centers are accompanied by larger heat dissipation and the need for innovative cooling methods. In this work, a combined jet-in-crossflow cooling system is introduced and numerically investigated with an application in localized hotspot treatment. A validation study, a grid independence study, and an uncertainty analysis are conducted to ensure the accuracy of the obtained results. Both vertical and angled jet impingement at different jet locations are studied indicating the advantage of using a 45 deg angled jet placed upstream of the hotspot. In addition, the advantage of jet-in-crossflow in comparison with pure crossflow and pure jet impingement is studied. The results show that the angled jet-in-crossflow setup, in comparison with pure crossflow at the same overall mass flowrate, considerably reduces the temperature values at the heated surface, and decreases the temperature standard deviation by 65%, while lowering the required pumping power by 35%. In comparison with pure jet impingement at the same overall mass flowrate, the angled jet-in-crossflow method reduces the required pumping power by 87%, while local temperature and temperature standard deviation values are very comparable. Furthermore, the advantage of structured rib channels in cooling effectiveness is investigated for the jet-in-crossflow setup. Although the addition of a rib slightly increases the pressure drop, the employment of a proper rib size minimizes the increased pressure drop while considerably improving the cooling effectiveness and temperature uniformity. | |
