摘要
流体在并联管组换热器中的流动状况将直接影响到换热器运行的效率和安全性 ,通过离散模型计算方法可得到流动工质在并联管组内的流动特性 .在对离散模型的建立进行详细分析的基础上 ,采用人工神经网络中的 BP算法来确定离散模型中的关键系数 ,即集箱中的静压变化系数和支管进出口的阻力系数 .通过离散模型计算得出的结果与实验数据符合良好 ,说明与简化的连续模型相比 ,离散模型是一种更为符合并联管组流动特性的理论模型 ,同时也表明了用
The status of the flow in manifold systems will directly affect the efficiency and security of an exchanger. With the help of discrete model, the characteristic of the flow in manifold systems will be gotten. After analyzing the establishment of the discrete model, this paper proposed a method applying BP neural networks to measure the key coefficient of the discrete model, namely the static pressure change coefficient and the branch tube's inlet and outlet resistance coefficient. The calculated results of the discrete model accord with the experimental data well. Compared with a simple continual model, the discrete model is true of the characteristic of the flow in manifold systems, and it also shows the availability of the way to use BP neural networks to measure the key coefficient of the discrete model.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2002年第11期1685-1688,共4页
Journal of Shanghai Jiaotong University