基于Kriging改进响应面法的桥梁地震动力可靠度研究
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摘要
鉴于桥梁结构对地震响应的非线性和复杂性等问题,提出了基于Kriging改进响应面法的桥梁结构地震动力可靠度分析方法。首先利用Kriging模型的优越模拟性能,将其作为响应面函数,并采取自适应策略加以改进,而后采取线性过滤器脉冲响应法对地震随机激励荷载进行了离散,并基于首次超越问题的定义建立了动力可靠度极限状态方程,最后对桥梁结构的地震可靠度问题进行了分析。计算分析结果表明:提出的基于Kriging模型的改进响应面法能有效完成桥梁地震动力可靠度的计算分析(包括结构参数随机性对桥梁动力可靠度的影响),且结果具有较高的准确性和高效性。
Since nonlinearity and other complexity problems exist in the seismic response analysis of bridge structure,an improved Kriging-based response surface method for bridge dynamic reliability analysis was proposed.The Kriging model was treated as the response surface function by using its excellent modeling capabilities,and further improved by self-adaption strategy.Then the linear filter impulse response method was adopted to discretize the random seismic excitation,and the dynamic limit state function was established based on the definition of first excursion reliability.The proposed method was utilized to analyze the problem of structural first excursion dynamic reliability of bridge under random seismic excitation.The calculation results show that: the proposed improved Kriging-based response surface method can effectively achieve the bridge seismic reliability analysis(including the influences of the randomness of structural parameters on the bridge seismic reliability),and the calculation results are of high accuracy and effectiveness.
Since nonlinearity and other complexity problems exist in the seismic response analysis of bridge structure,an improved Kriging-based response surface method for bridge dynamic reliability analysis was proposed.The Kriging model was treated as the response surface function by using its excellent modeling capabilities,and further improved by self-adaption strategy.Then the linear filter impulse response method was adopted to discretize the random seismic excitation,and the dynamic limit state function was established based on the definition of first excursion reliability.The proposed method was utilized to analyze the problem of structural first excursion dynamic reliability of bridge under random seismic excitation.The calculation results show that: the proposed improved Kriging-based response surface method can effectively achieve the bridge seismic reliability analysis(including the influences of the randomness of structural parameters on the bridge seismic reliability),and the calculation results are of high accuracy and effectiveness.
引文
[1]陈兵.桥梁抗震分析的随机理论及应用研究[D].成都:西南交通大学,2008.
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[4]陈颖,宁佐贵.基于神经网络响应面法的随机结构动力可靠度分析[J].振动与冲击,2007,26(1):65-68.CHEN Ying,NING Zuo-gui.Dynamic reliability analys is of a stochastic structure with neural network response surface method[J].Journal of Vibration and Shock,2007,26(1):65-68.
[5]苏成,徐瑞.非平稳地震作用下随机结构动力可靠度计算[J].振动工程学报,2011,24(2):118-124.SU Cheng,XU Rui.Dynamic reliability analysis of stochastic structures subjected to non-stationary seismic excitations[J].Journal of Vibration and Shock,2011,24(2):118-124.
[6]Kaymaz I.Application of Kriging method to structural reliability problems[J].2005,27(2):133-151.
[7]Ghanem R G,Spanos P D.Spectral stochastic finite-element formulation for reliability analysis[J].Journal of Engineering Mechanics,1991,117(10):2351-2372.
[8]Zhang J,Ellingwood B.SFEM for reliability of structures with material nonlinearities[J].Journal of Structural Engineering New York,N.Y,1996,122(6):701-704.
[9]Der Kiureghian A.Geometry of random vibrations and solutions by FORM and SORM[J].Probabilistic Engineering Mechanics,2000,15(1):81-90.
[10]Schueremans L,Van Gemert D.Benefit of splines and neural networks in simulation based structural reliability analysis[J].Structural Safety,2005,27(3):246-261.
[2]Romero V J,Swiler L P,Giunta A A.Construction ofresponse surfaces based on progressive-lattice-samplingexperimental designs with application to uncertaintypropagation[J].Structural Safety,2004,26(2):201-219.
[3]乔红威,吕震宙,关爱锐,等.平稳随机激励下随机结构动力可靠度分析的多项式逼近法[J].工程力学,2009,26(2):60-64.QIAO Hong-wei,Lu Zhen-zhou,GUAN Ai-rui,et al.Dynamicreliability analysis of stochastic structures under stationaryrandom excitation using hermite polynomials approximation[J].Engineering Mechanics,2009,26(2):60-64.
[4]陈颖,宁佐贵.基于神经网络响应面法的随机结构动力可靠度分析[J].振动与冲击,2007,26(1):65-68.CHEN Ying,NING Zuo-gui.Dynamic reliability analys is of a stochastic structure with neural network response surface method[J].Journal of Vibration and Shock,2007,26(1):65-68.
[5]苏成,徐瑞.非平稳地震作用下随机结构动力可靠度计算[J].振动工程学报,2011,24(2):118-124.SU Cheng,XU Rui.Dynamic reliability analysis of stochastic structures subjected to non-stationary seismic excitations[J].Journal of Vibration and Shock,2011,24(2):118-124.
[6]Kaymaz I.Application of Kriging method to structural reliability problems[J].2005,27(2):133-151.
[7]Ghanem R G,Spanos P D.Spectral stochastic finite-element formulation for reliability analysis[J].Journal of Engineering Mechanics,1991,117(10):2351-2372.
[8]Zhang J,Ellingwood B.SFEM for reliability of structures with material nonlinearities[J].Journal of Structural Engineering New York,N.Y,1996,122(6):701-704.
[9]Der Kiureghian A.Geometry of random vibrations and solutions by FORM and SORM[J].Probabilistic Engineering Mechanics,2000,15(1):81-90.
[10]Schueremans L,Van Gemert D.Benefit of splines and neural networks in simulation based structural reliability analysis[J].Structural Safety,2005,27(3):246-261.
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