深水桩墩结构振动台试验及地震响应预测分析
详细信息 本馆镜像全文    |  推荐本文 | | 获取馆网全文
摘要
动力模型试验是研究桥梁结构抗震设计理论的重要方法,而神经网络技术对非线性系统具有很好的辨识和预测功能.为了分析地震动作用下动水压力对结构的影响及探索神经网络应用于地震响应预测分析的可能性,进行了水下桩墩结构振动台模型试验及其仿真预测,衡量了水下桩墩结构的地震响应和动力特性.首先,介绍了相似律的选取、模型制作、试验现象及试验结果分析;然后,基于神经网络的预测功能,对模型试件的地震响应进行预测,并与试验结果对比研究;最后,分析试验结果及预测误差.试验结果表明:结构周围水体的存在改变了结构的地震响应及动力特性;训练有素的神经网络模型可以作为一个有用的工具,用于结构的地震响应预测.
The dynamic model test is an important method to research into seismic design theory of the bridge structure.The function of identification and prediction of neural network can be applied to nonlinear system effectively.In order to develop more advanced and reliable design procedures and explore the possibility of application of neural network to analysis and prediction of seismic response,investigation and prediction on shaking table model test of submerged pile-pier system,including pile-pier and the lumped mass,are conducted.Firstly,the similitude laws,model making,failure process and experimental results are introduced.Then,based on the function of prediction of neural network,the seismic response of model specimen is predicted and compared.Finally,the test results and prediction error are analyzed.The experimental results show that the dynamic characteristics and seismic response of the specimen can be changed because of the effect of water;the neural network can predict the seismic response accurately,and it can be used as an effective supplement for the experimental research.
引文
[1]范立础.现代化城市桥梁抗震设计若干问题[J].同济大学学报,1997,25(2):147-154.FAN Li-chu.Some problems in seismic design formodern urban bridges[J].Journal of TongjiUniversity,1997,25(2):147-154.(in Chinese)
    [2]李鸿晶,陆鸣,温增平,等.汶川地震桥梁震害的特征[J].南京工业大学学报:自然科学版,2009,31(1):24-29.LI Hong-jing,LU Ming,WEN Zeng-ping,et al.Characteristics of bridge damages in Wenchuanearthquake[J].Journal of Nanjing University ofTechnology:Natural Science Edition,2009,31(1):24-29.(in Chinese)
    [3]魏春莉.桩-土-桥梁结构地震动力相互作用振动台模拟试验研究[D].重庆:重庆交通大学,2008.WEI Chun-li.Shaking table test of seismic pile-soil-structure interaction[D].Chongqing:ChongqingJiaotong University,2008.(in Chinese)
    [4]唐亮,凌贤长,徐鹏举,等.可液化场地桥梁群桩-独柱墩结构地震反应振动台试验研究[J].土木工程学报,2009,42(11):102-108.TANG Liang,LING Xian-zhang,XU Peng-ju,et al.Shaking table tests for seismic response ofpile-supported bridge structure with single-columnpier in liquefiable ground[J].China CivilEngineering Journal,2009,42(11):102-108.(inChinese)
    [5]艾庆华,李宏男,王东升,等.基于位移设计的钢筋混凝土桥墩抗震性能试验研究(Ⅱ):振动台试验[J].地震工程与工程振动,2008,28(3):39-46.AI Qing-hua,LI Hong-nan,WANG Dong-sheng,et al.Experimental evaluation of seismicperformance of reinforced concrete bridge piersdesigned on the basis of displacement(Ⅱ):Shakingtable test[J].Journal of Earthquake Engineeringand Engineering Vibration,2008,28(3):39-46.(inChinese)
    [6]Sakai Junichi,Unjoh Shigeki.Shake tableexperiment on circular reinforced concrete bridgecolumn under multidirectional seismic excitation[C]//Structural Engineering Research Frontiers.Reston:ASEC,2007:1-12.
    [7]赖伟,王君杰,韦晓,等.桥墩地震动水效应的水下振动台试验研究[J].地震工程与工程振动,2006,26(6):164-171.LAI Wei,WANG Jun-jie,WEI Xiao,et al.Theshaking table test for submerged bridge pier[J].Journal of Earthquake Engineering and EngineeringVibration,2006,26(6):164-171.(in Chinese)
    [8]LIU Hao-peng,SONG Bo,ZHANG Guo-ming.Study of hydrodynamic pressure on the cylindricalpile-cap pier in deep water subjected to seismicaction[C]//Proceedings of the 9th InternationalConference of Chinese Transportation Professionals,ICCTP 2009:Critical Issues in TransportationSystems Planning,Development,and Management.Reston:ASCE,2009:528-535.
    [9]林皋,朱彤,林蓓.结构动力模型试验的相似技巧[J].大连理工大学学报,2000,40(1):1-8.LIN Gao,ZHU Tong,LIN Bei.Similaritytechnique for dynamic structural model test[J].Journal of Dalian University of Technology,2000,40(1):1-8.(in Chinese)
    [10]刘悦.神经网络集成及其在地震预报中的应用研究[D].上海:上海大学,2005.LIU Yue.Research on neural network ensemble andits application to earthquake prediction[D].Shanghai:Shanghai University,2005.(in Chinese)
    [11]陈大川,李华辉,欧阳攀.基于BP神经网络模型的村镇砖砌体结构震害预测研究[J].地震工程与工程振动,2010,30(3):102-107.CHEN Da-chuan,LI Hua-hui,OUYANG Pan.Seismic damage prediction of masonry buildings invillage based on BP neural network model[J].Journal of Earthquake Engineering and EngineeringVibration,2010,30(3):102-107.(in Chinese)
    [12]Chakraverty S,Marwala T,Gupta P,et al.Response prediction of structural system subject toearthquake motions using artificial neural network[J].Asian Journal of Civil Engineering(Buildingand Housing),2006,7(3):301-308.
    [13]Caglar N,Elmas M,Yaman Z D,et al.Neuralnetworks in 3-dimensional dynamic analysis ofreinforced concrete buildings[J].Construction andBuilding Materials,2008,22(5):788-800.
    [14]徐赵东,沈亚鹏,郭迎庆.神经网络对结构地震反应的预测及试验研究[J].振动与冲击,2003,22(2):8-11.XU Zhao-dong,SHEN Ya-peng,GUO Ying-qing.Neural network prediction for seismic response ofstructure and experimental study[J].Journal ofVibration and Shock,2003,22(2):8-11.(inChinese)
    [15]韩敏,史志伟.递归神经网络在堆石坝地震响应分析中的应用[J].系统仿真学报,2005,17(10):2533-2540.HAN Min,SHI Zhi-wei.Application of recurrentneural network to earthquake response analysis ofrock-fill dam[J].Acta Simulata Systematica Sinica,2005,17(10):2533-2540.(in Chinese)
    [16]闫滨.大坝安全监控及评价的智能神经网络模型研究[D].大连:大连理工大学,2006.YAN Bin.Study of intelligent neural network modelfor dam safety monitoring and safety evaluation[D].Dalian:Dalian University of Technology,2006.(inChinese)

版权所有:© 2023 中国地质图书馆 中国地质调查局地学文献中心