铜-水振荡热管的传热特性

Copper-Water Pulsating Heat Pipe Heat Transfer Characteristics

测定了风冷垂直放置的蛇形弯曲封闭循环铜 -水热管在不同充注率、加热功率下的热阻 .根据实验现象及对热阻的比较 ,分析不同情况下振荡热管的传热特性 ,并用完全联接的多层前向神经网络和具有动量项的误差反向传递学习算法建立了振荡热管传热性能的人工神经网络理论模型 .由于热管在不同充注率时传热机理不同 ,用统一的神经网络模型难以精确描述 。

This paper does research of an air-cooled vertical looped copper-water pulsating heat pipe to identify its thermal resistance under different heat loads and working fluid filling rates. The characteristics of the heat pipe under different conditions are studied according to the experiment phenomena and comparison on thermal resistance, and an artificial neural network (ANN) theoretic model of the heat pipe is established based on fully-connected multilayer feed forward neural network and back propagation learning algorithm with momentum. Because different phenomena appear in the heat pipe under different conditions, a unified ANN model can not simulate them all accurately, it is suggested to built ANN model periodically according to the physical phenomena.