文献类型：期刊文章

作　　者：崔晓钰[1] 翁建华[2] M.GROLL[3]

机构地区：[1]上海理工大学动力学院,上海200093 [2]无锡快捷半导体有限公司,江苏无锡214028 [3]斯图加特大学核能与能源系研究所,德国斯图加特70569

出　　处：《化工学报》

基　　金：德国DeutscheForschungsgemeinschaft (DFG)资助(No GR412 /3 3 -1);上海市重点学科建设资助项目~~

年　　份：2003

卷　　号：54

期　　号：9

起止页码：1319-1322

语　　种：中文

收录情况：AJ、BDHX、BDHX2000、CAS、CSCD、CSCD2011_2012、EI(收录号：2004047827333)、IC、JST、RCCSE、SCOPUS、ZGKJHX、核心刊

摘　　要：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.

关 键 词：振荡热管 神经网络 热阻

分 类 号：TK124]