【摘要】 本文以服务器N型冷板为研究对象，研究多因素交互作用对服务器热源温度，冷板流体温度和压降的影响。基于响应面法对不同进口温度、流量、冷板导热系数和纳米颗粒体积分数的冷板性能展开研究。结果表明：进口流量对各优化目标均有显著影响，进口温度和流量对热源温度影响最大，进口温度和冷板导热系数对冷板压降影响不显著。优化后热源最高温度降低13.01 K,平均温度降低6.46 K,冷板热性能得到显著改善。更多还原

【Abstract】 A server N-type cold plate was taken as the research object, and the influences of multi-factor interaction on the server heat source temperature, cold plate fluid temperature and pressure drop were studied. Based on the response surface method, the performances of cold plate with different inlet temperature, flow rate, thermal conductivity and volume fraction of nanoparticles were analyzed. The results show that the inlet flow rate has a significant effect on each optimization target. The inlet temperature and flow rate have the greatest influence on the heat source temperature, and the inlet temperature and the thermal conductivity of the cold plate have no significant effect on the pressure drop of the cold plate. After optimization, the maximum temperature of the heat source is reduced by 13.01 K, the average temperature is reduced by 6.46 K, and the thermal performance of the cold plate is significantly improved.更多还原