Research and Analysis of the Resistance Characteristic of Combined Flow Channel

摘要：

This article unified BP neural network with the computation hydrodynamics to carry on the research of hydraulic manifold block interior combined flow channels resistance characteristic. The numerical method confirmed that the input parameter of combined flow channel model has the influence to the pressure drop, according to this, the BP neural network model variable is established to carry on the forecast of combined flow channels pressure drop; the resistance characteristic curves of different structure channels are obtained, through to mathematical analysis of pipe networks resistance characteristic curve, proposed the through flow performance parameter of pipe network. The forecasting result tallies with the numerical calculus result, which indicated that this method may determine the combined flow channels resistance characteristic accurately and efficiently.

关键词： computational fluid dynamics BP neural network Hydraulic Manifold block combination channel resistance characteristic

作者: ZhiAn Song Wang YongAn

作者单位: Shandong University of Science And Technology, QingDao, China Dalian University of Technology, DaLian,China

会议类型: 国际会议

会议名称: 2009 International Workshop on Information Security and Application(2009 信息安全与应用国际研讨会)

会议地点: 青岛

会议语种:英文

页码: 11-14

在线出版日期: 2009-11-21（万方平台首次上网日期，不代表论文的发表时间）