ArticleMicromachines2022
Research on Intelligent Distribution of Liquid Flow Rate in Embedded Channels for Cooling 3D Multi-Core Chips.
Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Suitability of Embedded Liquid Cooling and Heat Generation for Chips.Micromachines · 2023Article
- Thermal-Hydrodynamic Behavior and Design of a Microchannel Pin-Fin Hybrid Heat Sink.Micromachines · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
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.
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Registered trials
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