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A combined numerical simulation and optimization model for the cooling of IC chips under forced convection
International Journal of Modern Physics C ( IF 1.9 ) Pub Date : 2020-02-19 , DOI: 10.1142/s0129183120500813
Naveen G. Patil 1 , Tapano Kumar Hotta 1
Affiliation  

Three-dimensional steady state numerical simulations are carried out from seven protruding IC chips (Aluminium) of different sizes mounted at various positions on a high-power SMPS board (Bakelite) cooled under forced convection ([Formula: see text][Formula: see text]W/cm2, [Formula: see text][Formula: see text]m/s). The objective is to predict the temperature distribution of these IC chips and to determine their optimal arrangement on the SMPS board; that will have the lowest maximum temperature excess among all the possible configurations. To achieve the same, a numerical analysis is carried out using the commercial software ANSYS-Icepak, and then the hybrid optimization strategy (Genetic Algorithm (GA) driven by Artificial Neural Network (ANN)) is employed to obtain the global optimal configuration of these IC chips. Preliminary analysis is performed using a dimensionless position parameter ([Formula: see text]) which is found to be a strong function of the IC chip size, and their positioning on the substrate board. It is observed that the combined ANN-GA strategy is able to predict the optimal behavior of the IC chips more accurately. The larger size IC chips generating higher power should be placed at the substrate bottom for better cooling.

中文翻译:

强制对流下IC芯片冷却的组合数值模拟与优化模型

三个不同尺寸的突出 IC 芯片(铝)在强制对流下冷却的大功率 SMPS 板(Bakelite)上的不同位置进行了三维稳态数值模拟([公式:见正文] [公式:见文字]W/cm2, [公式:见正文][公式:见正文]m/s)。目的是预测这些 IC 芯片的温度分布,并确定它们在 SMPS 板上的最佳布置;在所有可能的配置中,这将具有最低的最大超温。为此,使用商业软件ANSYS-Icepak进行数值分析,然后采用混合优化策略(人工神经网络(ANN)驱动的遗传算法(GA))来获得这些的全局最优配置集成电路芯片。使用无量纲位置参数([公式:见正文])进行初步分析,该参数被发现是 IC 芯片尺寸及其在基板上的定位的强函数。可以观察到,组合的 ANN-GA 策略能够更准确地预测 IC 芯片的最佳行为。产生更高功率的较大尺寸 IC 芯片应放置在基板底部,以实现更好的冷却。
更新日期:2020-02-19
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