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Proceedings of 2009 International Workshop on Information Security and Application (IWISA 2009)

Qingdao, China, November 21-22, 2009

Editors: Feng Gao and Xijun Zhu

AP Catalog Number: AP-PROC-CS-09CN004

ISBN: 978-952-5726-06-0

Page(s): 11-14

Research and Analysis of the Resistance Characteristic of Combined Flow Channel

        Zhi’An Song and Yong’An Wang

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This article unified BP neural network with the computation hydrodynamics to carry on the research of hydraulic manifold block interior combined flow channel's 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 channel's pressure drop; the resistance characteristic curves of different structure channels are obtained, through to mathematical analysis of pipe network's 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 channel's resistance characteristic accurately and efficiently.

Index Terms

computational fluid dynamics, BP neural network, Hydraulic Manifold block, combination channel, resistance characteristic

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