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复合缝腔割缝筛管的流阻分析及优化设计
引用本文:张建乔,刘永红,刘春阳,魏新芳.复合缝腔割缝筛管的流阻分析及优化设计[J].工程设计学报,2006,13(4):260-264.
作者姓名:张建乔  刘永红  刘春阳  魏新芳
作者单位:中国石油大学 机电工程学院, 山东 东营 257061
基金项目:国家重点基础研究发展计划(973计划)
摘    要:原油流经筛管的流动阻力是设计新型复合缝腔割缝筛管的主要考虑因素之一。通过对流经复合缝腔割缝筛管原油流动阻力的精细计算,得到了大量的筛管参数与流阻的关系数据,利用BP神经网络技术,建立了筛管流阻预测模型。基于此预测模型,采用遗传算法对筛管多个参数进行了综合优化。实验实测数据表明,筛管流阻预测模型的计算结果符合工程要求。油田现场应用表明,通过该方法设计的复合缝腔割缝筛管流阻小、强度高、使用寿命长,市场前景广阔。

关 键 词:防砂  复合缝腔    割缝筛管    BP神经网络  
文章编号:1006-754X(2006)04-0260-04
收稿时间:2006-08-28
修稿时间:2005年12月9日

Flow resistance analysis and optimization of slotted screen liner with compound cavity
ZHANG Jian-qiao,LIU Yong-hong,LIU Chun-yang,WEI Xin-fang.Flow resistance analysis and optimization of slotted screen liner with compound cavity[J].Journal of Engineering Design,2006,13(4):260-264.
Authors:ZHANG Jian-qiao  LIU Yong-hong  LIU Chun-yang  WEI Xin-fang
Affiliation:College of Mechanical and Electronic Engineering, University of Petroleum, Dongying 257061, China
Abstract:Flow resistance when crude oil flows through screen liner is a key factor for designing new slotted screen liner with compound cavity.Through accurate computation of such resistance,a large number of relation data between screen liner parameters and flow resistance are obtained.By applying BP neural network,forecast model of flow resistance is built up.Based on this model,Genetic Algorithm is utilized to comprehensively optimize parameters of screen liner.Experiment data shows that this model can fulfill the engineering requirements.Field application indicates that screen liner,designed by this model,has small flow resistance,high intension,long longevity and wide market prospect.
Keywords:sand control  compound cavity  screen liner  BP neural network
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