Research on Intelligent Distribution of Liquid Flow Rate in Embedded Channels for Cooling 3D Multi-Core Chips

被引:8
作者
Zhang, Jian [1 ]
Xie, Zhihui [1 ]
Lu, Zhuoqun [1 ,2 ]
Li, Penglei [1 ]
Xi, Kun [1 ]
机构
[1] Naval Univ Engn, Coll Power Engn, Wuhan 430033, Peoples R China
[2] Hunan Univ Humanities Sci & Technol, Sch Energy & Electromech Engn, Loudi 417000, Peoples R China
基金
中国国家自然科学基金;
关键词
embedded cooling; dynamic thermal management; artificial neural network; genetic algorithm; nonuniform heat source; HEAT-TRANSFER; PERFORMANCE; DESIGN; ELECTRONICS; NANOFLUID; SINK;
D O I
10.3390/mi13060918
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A numerical simulation model of embedded liquid microchannels for cooling 3D multi-core chips is established. For the thermal management problem when the operating power of a chip changes dynamically, an intelligent method combining BP neural network and genetic algorithm is used for distribution optimization of coolant flow under the condition with a fixed total mass flow rate. Firstly, a sample point dataset containing temperature field information is obtained by numerical calculation of convective heat transfer, and the constructed BP neural network is trained using these data. The "working condition-flow distribution-temperature" mapping relationship is predicted by the BP neural network. The genetic algorithm is further used to optimize the optimal flow distribution strategy to adapt to the dynamic change of power. Compared with the commonly used uniform flow distribution method, the intelligently optimized nonuniform flow distribution method can further reduce the temperature of the chip and improve the temperature uniformity of the chip.
引用
收藏
页数:12
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