|本期目录/Table of Contents|

[1]高培培,章光,胡少华,等.基于GA-BP的渗透系数多目标反演分析模型研究[J].中国安全生产科学技术,2019,15(8):12-18.[doi:10.11731/j.issn.1673-193x.2019.08.002]
　GAO Peipei,ZHANG Guang,HU Shaohua,et al.Research on multiobjective inversion analysis model of permeability coefficient based on GA-BP[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2019,15(8):12-18.[doi:10.11731/j.issn.1673-193x.2019.08.002]
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基于GA-BP的渗透系数多目标反演分析模型研究
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
15
期数:
2019年8期
页码:
12-18
栏目:
学术论著
出版日期:
2019-08-31

文章信息/Info

Title:
Research on multiobjective inversion analysis model of permeability coefficient based on GA-BP
文章编号:
1673-193X(2019)-08-0012-07
作者:
高培培1; 章光1; 胡少华1; 2; 武晓炜1; 文锋1; 刘志1
（1.武汉理工大学 安全科学与应急管理学院，湖北 武汉 430070；
2.武汉理工大学 道路桥梁与结构工程湖北省重点实验室，湖北 武汉 430070）
Author(s):
GAO Peipei1; ZHANG Guang1; HU Shaohua1; 2; WU Xiaowe1i; WEN Feng1; LIU Zhi1
(1.School of Safety Science and Emergency Management,Wuhan University of Technology,Wuhan Hubei 430070,China;
2.Hubei Key Laboratory of Roadway Bridge and Structure Engineering,Wuhan University of Technology,Wuhan Hubei 430070,China)
关键词:
GA-BP神经网络; 渗透系数; 反演模型; 正交设计
Keywords:
GA-BP neural network;  permeability coefficient;  inversion model;  orthogonal design
分类号:
X936;TU45
DOI:
10.11731/j.issn.1673-193x.2019.08.002
文献标志码:
A
摘要:
针对渗透系数反演结果不唯一问题，以扬压力和渗流量2类渗流监测效应量为反演目标，建立了基于正交设计、有限元正分析和GA-BP相结合的渗透系数多目标反演分析模型。结合水口大坝2009—2018年渗流监测时间序列数据，开展了大坝坝体、坝基岩体渗透系数反演研究，并对反演结果进行了验证。研究结果表明：建立的渗透系数反演模型可较好地解决渗流单目标反演的缺陷，反演结果为绝对渗透系数，且反演结果真实可靠。
Abstract:
Aiming at the problem that the inversion results of permeability coefficient were not unique,two kinds of seepage monitoring effect quantities including the uplift pressure and the seepage quantity were used as the inversion objectives,and the multiobjective inversion analysis model of permeability coefficient based on the combined methods of orthogonal design,finite element positive analysis and GA-BP was established.Combined with the time series data of the seepage monitoring in the Shuikou dam from 2009 to 2018,the inversion research on the permeability coefficients of the dam and dam foundation rock mass was carried out,and the inversion results were verified.The results showed that the inversion model of permeability coefficient could solve the defect of seepage singleobjective inversion better.The inversion results were the absolute permeability coefficients,which were true and reliable.

参考文献/References:

［1］顾冲时,苏怀智.混凝土坝工程长效服役与风险评定研究述评［J］.水利水电科技进展,2015,35(5):1-12.GU Chongshi,SU Huaizhi.Current status and prospects of long-term service and risk assessment of concrete dams ［J］.Advances in Science and Technology of Water Resources,2015,35(5):1-12.
［2］李宗伟,孙丹,尹大娟.吊水壶尾矿坝渗流特性三维有限元分析［J］.中国安全生产科学技术,2012,8(6):65-69.LI Zongwei,SUN Dan,YIN Dajuan.Analysis on seepage behavior of Diaoshuihu tailing dam by 3-D FEM ［J］.Journal of Safety Science and Technology,2012,8(6):65-69
［3］ASJAD M,KHAN S.Analysis of maintenance cost for an asset using the genetic algorithm［J］.International Journal of System Assurance Engineering & Management,2016,8(2):1-13.
［4］NEAUPANE K M,ACHET S H.Use of backpropagation neural network for landslide monitoring:a case study in the higher Himalaya ［J］.Engineering Geology,2004,74(3-4):213-226.
［5］刘要来,周红波,荀小伟.基于BP神经网络的渗流场反演分析［J］.中国水运(下半月),2014,14(10):113-116,141.LIU Yaolai,ZHOU Hongbo,XUN Xiaowei.Inversion analysis of seepage field based on BP neural network ［J］.China Water Transport（Second half of the month）,2014,14(10):113-116,141.
［6］林雪松,王永吉,王东,等.细尾矿砂非饱和渗流稳态含水率二维解析解［J］.中国安全生产科学技术,2019,15(5):111-116.LIN Xuesong,WANG Yongji,WANG Dong,et al.Two-dimensional analytical solution of steady water content for fine tailing sand with unsaturated seepage［J］.Journal of Safety Science and Technology.2019,15(5):111-116.
［7］黄珊,秦卫星,黎峰,等.石牛水库防渗加固后大坝渗透系数反分析［J］.吉林水利,2014(2):1-2,6.HUANG Shan,QIN Weixing,LI Feng,et al.Inversion analysis of permeability coefficients for Shiniu reservoir after anti-seepage reinforcements ［J］.Jilin Water Resources,2014(2):1-2,6.
［8］LINGIREDDY S.Aquifer parameter estimation using genetic algorithms and neural networks［J］.Civil Engineering and Environmental Systems,1998,15(2):125-144.
［9］李守巨,刘迎曦,王登刚,等.基于神经网络的岩体渗透系数反演方法及其工程应用［J］.岩石力学与工程学报,2002，21(4):479-483.LI Shouju,LIU Yingxi,WANG Denggang,et al.Inversion algorithm of permeability coefficients of rockmass and its application based on artificial neural network ［J］.Chinese Journal of Rock Mechanics and Engineering,2002，21(4):479-483.
［10］魏进兵,邓建辉,高春玉,等.三峡库区泄滩滑坡非饱和渗流分析及渗透系数反演［J］.岩土力学,2008，29(8):2262-2266.WEI Jinbing,DENG Jianhui,GAO Chunyu,et al.Unsaturated seepage analysis and back analysis of permeability coefficient for Xietan landslide in Three Gorges Reservoir area ［J］.Rock and Soil Mechanics,2008，29(8):2262-2266.
［11］王媛,刘杰.重力坝坝基渗透参数进化反演分析［J］.岩土工程学报,2003，25(5):552-556.WANG Yuan,LIU Jie.Back analysis of the permeability coefficients of gravity dam foundation by evolution method ［J］.Chinese Journal of Geotechnical Engineering,2008，25(5):552-556.
［12］崔皓东,朱岳明.二滩高拱坝坝基渗流场的反演分析［J］.岩土力学,2009,30(10):3194-3199.CUI Haodong,ZHU Yueming.Back analysis of seepage field of Ertan high arch dam foundation ［J］.Rock and Soil Mechanics,2009,30(10):3194-3199.
［13］毛昶熙.渗流计算分析与控制(第2版)［M］.北京：中国水利水电出版社,2003.
［14］孟如真,胡少华,陈益峰,等.高渗压条件下基于非达西流的裂隙岩体渗透特性研究［J］.岩石力学与工程学报,2014,33(9):1756-1764.MENG Ruzhen,HU Shaohua,CHEN Yifeng,et al.Permeability of Non-Darcian flow in fractured rock mass under high seepage pressure［J］.Chinese Journal of Rock Mechanics and Engineering,2014,33(9):1756-1764.
［15］王雯,顾中明,杨杰,等.基于正交设计的大坝深层抗滑稳定敏感性分析［J］.西安理工大学学报,2018,34(3):321-325.WANG Wen,GU Zhongming,YANG Jie,et al.Sensitivity analysis of deep anti-sliding stability of dam based on orthogonal design ［J］.Journal of Xi’an University of Technology,2018,34(3):321-325.
［16］刘毅,赵斌滨,殷坤龙,等.基于正交设计的麻柳林滑坡稳定性敏感分析［J］.地球科学,2019,44(2):677-684.LIU Yi,ZHAO Binbin,YIN Kunlong,et al.Sensitivity analysis of Maliulin landslide stability based on orthogonal design ［J］.Earth Science,2019,44(2):677-684.
［17］曾三友,魏巍,康立山,等.基于正交设计的多目标演化算法［J］.计算机学报,2005,28(7):1153-1162.ZENG Sanyou,WEI Wei,KANG Lishan,et al.A Multi-Objective evolutionary algorithm based on orthogonal design ［J］.Chinese Journal of Computers,2005,28(7):1153-1162.
［18］NORMAN B A.A genetic algorithm methodology for complex scheduling problems［J］.Naval Research Logistics,2015,46(2):199-211.
［19］HARTMANN S.A competitive genetic algorithm for resource-constrained project scheduling［J］.Naval Research Logistics,2015,45(7):733-750.
［20］李全明,张丙印,袁会娜.三峡茅坪溪沥青混凝土心墙堆石坝位移反演分析与安全预测［J］.中国安全生产科学技术,2007,3(3):12-16.LI Quanming,ZHANG Bingyin,YUAN Huina.Displacement back analysis and safety forecast of Maopingxi rockfill dam with asphalt concrete core in Three Georges Project ［J］.Journal of Safety Science and Technology,2007,3(3):12-16.
［21］王俊,刘进宝,韩剑,等.基于人工神经网络的混凝土大坝渗透系数反演［J］.华北水利水电学院学报,2003,24(3):9-12.WANG Jun,LIU Jinbao,HAN Jian,et al.Inversion of permeability coefficients of concrete dam based on artificial neural network ［J］.Journal of North China University of Water Resources and Electric Power.2003,24(3):9-12.
［22］李友坤.BP神经网络的研究分析及改进应用［D］.淮南：安徽理工大学,2012.

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备注/Memo

备注/Memo:
收稿日期： 2019-07-05
* 基金项目： 国家自然科学基金青年基金项目(51609184)；道路桥梁与结构工程湖北省重点实验室（武汉理工大学）开放课题基金项目（DQJJ201705）
作者简介： 高培培，硕士研究生，主要研究方向为安全工程与水工结构。
通信作者： 胡少华，博士，讲师，主要研究方向为安全工程与水工结构。
更新日期/Last Update: 2019-09-04