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基于神经网络的振荡热管传热性能建模 被引量:18
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作者 崔晓钰 翁建华 M.GROLL 《化工学报》 EI CAS CSCD 北大核心 2003年第9期1319-1322,共4页
This paper presents artificial neural network (ANN) modeling of heat transfer performance for a pulsating heat pipe (PHP). The investigated PHP is a vertical closed loop copper/ethanol PHP. Fully connected multi-layer... This paper presents artificial neural network (ANN) modeling of heat transfer performance for a pulsating heat pipe (PHP). The investigated PHP is a vertical closed loop copper/ethanol PHP. Fully connected multi-layer feed forward network is adopted and back propagation momentum algorithm, sigmoid node function are used. In the network, two input nodes correspond to heat load and fill rate and the output is a single node for thermal resistance. The matching of the ANN test output data and the experimental data is satisfying. It can be inferred that the ANN model can be applied to accurately model PHP performance. 展开更多
关键词 振荡热管 神经网络 热阻
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