Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can b...Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.展开更多
Traditional track dynamic geometric state(TDGS)simulation incurs substantial computational burdens,posing challenges for developing reliability assessment approach that accounts for TDGS.To overcome these,firstly,a si...Traditional track dynamic geometric state(TDGS)simulation incurs substantial computational burdens,posing challenges for developing reliability assessment approach that accounts for TDGS.To overcome these,firstly,a simulation-based TDGS model is established,and a surrogate-based model,grid search algorithm-particle swarm optimization-genetic algorithm-multi-output least squares support vector regression,is established.Among them,hyperparameter optimization algorithm’s effectiveness is confirmed through test functions.Subsequently,an adaptive surrogate-based probability density evolution method(PDEM)considering random track geometry irregularity(TGI)is developed.Finally,taking curved train-steel spring floating slab track-U beam as case study,the surrogate-based model trained on simulation datasets not only shows accuracy in both time and frequency domains,but also surpasses existing models.Additionally,the adaptive surrogate-based PDEM shows high accuracy and efficiency,outperforming Monte Carlo simulation and simulation-based PDEM.The reliability assessment shows that the TDGS part peak management indexes,left/right vertical dynamic irregularity,right alignment dynamic irregularity,and track twist,have reliability values of 0.9648,0.9918,0.9978,and 0.9901,respectively.The TDGS mean management index,i.e.,track quality index,has reliability value of 0.9950.These findings show that the proposed framework can accurately and efficiently assess the reliability of curved low-stiffness track-viaducts,providing a theoretical basis for the TGI maintenance.展开更多
在实际工程中,调谐质量阻尼器(Tuned Mass Damper,TMD)作为一种有效的被动控制装置已得到广泛运用,但相关研究表明,TMD的控制效果对其自身参数较为敏感。本文基于概率密度演化方法,分析研究了TMD不同随机参数、相同随机参数不同变异性...在实际工程中,调谐质量阻尼器(Tuned Mass Damper,TMD)作为一种有效的被动控制装置已得到广泛运用,但相关研究表明,TMD的控制效果对其自身参数较为敏感。本文基于概率密度演化方法,分析研究了TMD不同随机参数、相同随机参数不同变异性对系统减震控制效果的影响规律,并对影响差异进行了比较。分析结果表明,TMD的减震性能与系统参数密切相关,在TMD系统优化设计和施工过程中,应考虑系统的随机性。展开更多
Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduce...Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.展开更多
A random medium model is developed to describe damage and failure of concrete.In the first place,to simulate the evolving cracks in a mesoscale,the concrete is randomly discretized as irregular finite elements.Moreove...A random medium model is developed to describe damage and failure of concrete.In the first place,to simulate the evolving cracks in a mesoscale,the concrete is randomly discretized as irregular finite elements.Moreover,the cohesive elements are inserted into the adjacency of finite elements as the possible cracking paths.The spatial variation of the material properties is considered using a 2-D random field,and the stochastic harmonic function method is adopted to simulate the sample of the fracture energy random field in the analysis.Then,the simulations of concrete specimens are given to describe the different failure modes of concrete under tension.Finally,based on the simulating results,the probability density distributions of the stress-strain curves are solved by the probability density evolution methods.Thus,the accuracy and efficiency of the proposed model are verified in both the sample level and collection level.展开更多
The numerical method for multi-dimensional integrals is of great importance, particularly in the uncertainty quantification of engineering structures. The key is to generate representative points as few as possible bu...The numerical method for multi-dimensional integrals is of great importance, particularly in the uncertainty quantification of engineering structures. The key is to generate representative points as few as possible but of acceptable accuracy. A generalized L2（GL2）-discrepancy is studied by taking unequal weights for the point set. The extended Koksma-Hlawka inequality is discussed. Thereby, a worst-case error estimate is provided by such defined GL2-discrepancy, whose dosed-form expression is available. The characteristic values of GL2-discrepancy are investigated. An optimal strategy for the selection of the representative point sets with a prescribed cardinal number is proposed by minimizing the GL2-discrepancy. The three typical examples of the multi-dimensional integrals are investigated. The stochastic dynamic response analysis of a nonlinear structure is then studied by incorporating the proposed method into the probability density evolution method. It is shown that the proposed method is advantageous in achieving tradeoffs between the efficiency and accuracy of the exemplified problems. Problems to be further studied are discussed.展开更多
基金Project(2023YFB4302500)supported by the National Key R&D Program of ChinaProject(52078485)supported by the National Natural Science Foundation of ChinaProjects(2021-Major-16,2021-Special-08)supported by the Science and Technology Research and Development Program Project of China Railway Group Limited。
文摘Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.
基金Project(52072412)supported by the National Natural Science Foundation of China。
文摘Traditional track dynamic geometric state(TDGS)simulation incurs substantial computational burdens,posing challenges for developing reliability assessment approach that accounts for TDGS.To overcome these,firstly,a simulation-based TDGS model is established,and a surrogate-based model,grid search algorithm-particle swarm optimization-genetic algorithm-multi-output least squares support vector regression,is established.Among them,hyperparameter optimization algorithm’s effectiveness is confirmed through test functions.Subsequently,an adaptive surrogate-based probability density evolution method(PDEM)considering random track geometry irregularity(TGI)is developed.Finally,taking curved train-steel spring floating slab track-U beam as case study,the surrogate-based model trained on simulation datasets not only shows accuracy in both time and frequency domains,but also surpasses existing models.Additionally,the adaptive surrogate-based PDEM shows high accuracy and efficiency,outperforming Monte Carlo simulation and simulation-based PDEM.The reliability assessment shows that the TDGS part peak management indexes,left/right vertical dynamic irregularity,right alignment dynamic irregularity,and track twist,have reliability values of 0.9648,0.9918,0.9978,and 0.9901,respectively.The TDGS mean management index,i.e.,track quality index,has reliability value of 0.9950.These findings show that the proposed framework can accurately and efficiently assess the reliability of curved low-stiffness track-viaducts,providing a theoretical basis for the TGI maintenance.
文摘在实际工程中,调谐质量阻尼器(Tuned Mass Damper,TMD)作为一种有效的被动控制装置已得到广泛运用,但相关研究表明,TMD的控制效果对其自身参数较为敏感。本文基于概率密度演化方法,分析研究了TMD不同随机参数、相同随机参数不同变异性对系统减震控制效果的影响规律,并对影响差异进行了比较。分析结果表明,TMD的减震性能与系统参数密切相关,在TMD系统优化设计和施工过程中,应考虑系统的随机性。
基金Projects(51708558,51878673,U1734208,52078485,U1934217,U1934209)supported by the National Natural Science Foundation of ChinaProject(2020JJ5740)supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(KF2020-03)supported by the Key Open Fund of State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures,ChinaProject(2020-Special-02)supported by the Science and Technology Research and Development Program of China Railway Group Limited。
文摘Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.
基金supported by the National Natural Science Foundation of China(Grant Nos.90715033,51261120374,51208374)
文摘A random medium model is developed to describe damage and failure of concrete.In the first place,to simulate the evolving cracks in a mesoscale,the concrete is randomly discretized as irregular finite elements.Moreover,the cohesive elements are inserted into the adjacency of finite elements as the possible cracking paths.The spatial variation of the material properties is considered using a 2-D random field,and the stochastic harmonic function method is adopted to simulate the sample of the fracture energy random field in the analysis.Then,the simulations of concrete specimens are given to describe the different failure modes of concrete under tension.Finally,based on the simulating results,the probability density distributions of the stress-strain curves are solved by the probability density evolution methods.Thus,the accuracy and efficiency of the proposed model are verified in both the sample level and collection level.
基金supported by the National Natural Science Foundation of China(Grant Nos.51538010&51261120374)the State Key Laboratory of Disaster Reduction in Civil Engineering(Grant No.SLDRCE14-B-17)the Fundamental Funding for Central Universities
文摘The numerical method for multi-dimensional integrals is of great importance, particularly in the uncertainty quantification of engineering structures. The key is to generate representative points as few as possible but of acceptable accuracy. A generalized L2（GL2）-discrepancy is studied by taking unequal weights for the point set. The extended Koksma-Hlawka inequality is discussed. Thereby, a worst-case error estimate is provided by such defined GL2-discrepancy, whose dosed-form expression is available. The characteristic values of GL2-discrepancy are investigated. An optimal strategy for the selection of the representative point sets with a prescribed cardinal number is proposed by minimizing the GL2-discrepancy. The three typical examples of the multi-dimensional integrals are investigated. The stochastic dynamic response analysis of a nonlinear structure is then studied by incorporating the proposed method into the probability density evolution method. It is shown that the proposed method is advantageous in achieving tradeoffs between the efficiency and accuracy of the exemplified problems. Problems to be further studied are discussed.
