基于NSGA-Ⅱ算法的微通道结构参数优化

Parameter Optimization of Microchannel Structure Based on NSGA-ⅡAlgorithm

随着集成电路技术的迅速发展,电子芯片的发展趋势逐渐朝向高度集成、微型化以及多核化的方向,这导致芯片在工作时产生的热量急剧增加。由于不同核心产生的发热量不同,因此需要针对不同核心的发热情况来有效解决散热问题。本文的研究重点是阵列芯片的分布式散热,通过设计一种多入口单出口的半开放式微通道来解决这一问题。具体来说,研究使用了微通道中的梯形肋,通过调整肋的前楔角和肋宽系数,以提高传热效率并控制压降。为了找到最佳的微通道结构参数,研究采用了NSGA-Ⅱ多目标遗传算法进行优化。研究结果显示,与未经优化的微通道相比,优化后的微通道结构在相同泵功率下Nusselt数(Nu数)提高了30%,微通道内的温度分布更加均匀。

With the rapid development of integrated circuit technology,the development trend of electronic chips tends to be highly integrated,miniaturized and multi-core,and the heat generated during the operation of chips rises sharply.Guided by the distributed heat dissipation of arrays,this paper designs a semi-open microchannel with multiple inlets and single outlets to solve the heat dissipation problem of arrays.Taking the front wedge angle and rib width coefficient of trapezoidal ribs in microchannels as independent variables,and the efficiency and pressure drop of heat transfer as the dependent variables,the NSGA-Ⅱmulti-objective genetic algorithm is used to construct a microchannel structure parameter optimization model.The results show that compared with the optimized channel,the optimized microchannel structure has better heat transfer performance under the same pump power,the Nusselt number is increased by 30%,and the temperature distribution in the microchannel is more uniform.The comprehensive heat transfer performance is much better.