城市轨道交通系统轨道结构随机动力响应分析

以随机振动理论为基础,考虑轨道不平顺的影响,采用Wilson-θ数值积分方法,得到了列车荷载作用下轻轨系统轨道、道床的垂向动力响应特征,并做了相应的功率谱密度估计.结果表明,钢轨的垂向振动能量主要集中在高频段区域,道床的振动能量则主要集中在100 Hz左右.     

基于ADAMS的随机路面不平度建模及参数选择

车辆的垂直运动和俯仰运动会影响乘客的舒适性和安全性,垂向振动的激励除了发动机的激励,还取决于路面轮廓的不平度.应用谐波叠加法对路面不平度的特征能较好的拟合,并对生成的路面与国际标准的分级路面进行对比,分析谐波的数目对路面不平度均方根值有很大影响,证明生成时域信号的功率谱密度与标准规定的路面等级一致,可以作为研究车辆垂向...     

基于频域法的冷凝器支架随机振动分析

频域法随机振动疲劳分析是使用功率谱密度函数(Power spectral density)进行结构疲劳计算的方法。首先对结构进行频率响应计算,得到结构的单位应力频率响应函数;利用此传递函数与输入的功率谱,获得结构的应力功率谱密度,再结合材料参数选择合适的疲劳损伤模型,利用频域方法计算结构的疲劳强度。本文应用频域法随机振动疲劳分析,对某卡车的冷凝器支架实际工程问题进行了结构改进研究。     

载重车道路多点随机激励输入的时空相关性建模研究

为解决载重车动力学分析和车辆动态设计的道路建模问题,基于对车辆道路随机不平顺性态的分析,结合其在频域内的统计表示方法———功率谱密度函数,导出了载重车六轮激励输入的关于道路高程的功率谱矩阵,进而通过白噪声滤波方程得到了与给定谱特征相对应的道路时延相关性数学模型,提出了一种新的模拟双轮辙的过程和方法。通过应用该方法可以再现随机道路高程的有代表性的时间样本,为载重车线性和非线性平顺性动力学分析、悬架系统优化及整车振动控制提供模型基础。     

发动机部件随机振动强化耐久试验

本文讨论发动机部件随机振动，不与燃烧室接触的发动机外部零件失效主要是由于发动机振动。发动机振劝是具有各态经历性的平稳随机振动。以随机振动的功率谱密度和功率谱来描述随机振动强度。从发动机上测量功率谱密度笔功率谱乘以强化系数作为标准来模拟部件强化试验。     

伪随机桥面不平顺时域模型仿真分析研究

桥面不平顺是车辆-桥梁耦合系统振动的主要影响因素之一,引入路面不平度来模拟桥面不平顺,假定路面不平度是具有零均值、各态历经的平稳随机过程,且服从高斯概率分布。基于FORTRAN平台编制了模拟桥面不平顺的仿真程序BDR,采用FFT法及谐波法模拟了按国家标准GB/T 7031-86划分的B、C级桥面不平顺曲线。结果表明:该模型能够描述复杂且不规则的路面形状,适用于任意谱密度函数的平稳随机过程,适应性良好。     

车辆荷载作用下大跨桥梁的随机振动

基于随机轨道粗糙度和车桥偶合单元,提出了大跨桥梁移动车辆荷载作用下随机振动的计算模式.采用功率谱密度函数生成随机的轨道粗糙度,车辆模拟为4轴模型,桥梁模拟为梁单元,考虑桥梁的几何非线性,对一座实际大跨斜拉桥的冲击效应进行了研究,并分析了随机样本数目、阻尼及车辆速度的影响.     

随机路面激励下车辆系统参数对汽车行驶平顺性的影响研究

基于汽车系统动力学和随机振动理论，建立了简化的人体-座椅、车身及车轮3-DOF车辆振动模型，采用线性滤波白噪声法建立了路面激励模型，并仿真分析了常见C级路面的不平度特性。以C级随机路面激励为车辆振动系统输入，运用变步长四阶Runge-Kutta法求解了车辆系统数学模型。在时域和频域两方面，仿真分析了座椅刚度、阻尼，悬架刚度、阻尼及轮胎刚度对座椅、悬架性能的影响，以及路面不平度和车速对座椅垂向加权加速度的影响。得出了座椅加速度、悬架动挠度、轮胎动载荷功率谱密度随座椅刚度、阻尼系数，悬架刚度、阻尼系数及轮胎刚度变化的规律。     

车辆荷载作用下大跨桥梁的随机振动

基于随机轨道粗糙度和车桥偶合单元，提出了大跨桥梁移动车辆荷载作用下随机振动的计算模式。采用功率谱密度函数生成随机的轨道粗糙度，车辆模拟为4轴模型，桥梁模拟为梁单元，考虑桥梁的几何非线性，对一座实际大跨斜拉桥的冲击效应进行了研究，并分析了随机样本数目、阻尼及车辆速度的影响。     

汽车对路面作用的随机动荷分析

从双轴汽车四自由度平面模型出发，将路面不平整度的功率谱密度函数作为输入，利用随机振动的方法分析了行驶车辆作用于路面的随机动压力。     

Application of the structural articulation method to dynamic impact loading of railway bridges – a case study

This article demonstrates a practical application of the structural articulation method. An existing prototype railway bridge was selected to compare our new method with the industry codes of practice. The response history and dynamic increment of the bridge were investigated through a variety of methods: lump sum mass analysis (LSMA) and suspension system analysis (SSA) for a single-axle force, and SSA for multi-axle forces. We considered both a local irregularity and a global sinusoidal irregularity. The dynamic impact load induced by either form of track irregularity increases approximately linearly with the vehicle speed up to a certain point, then tends to decrease gradually. This behaviour reveals that the dynamic impact load induced by track irregularities is dominated by the resonance of the bridge. If a bridge must support multiple axles, or if an especially accurate dynamic impact factor is required for safety reasons, then multi-axle SSA is recommended because this approach is the most accurate and likely to produce a weaker response than single-axle analysis. The random irregularity is generated by the stochastic track irregularity process. It is found that the dynamic impact load induced by the random irregularity is negligible, compared with the deterministic irregularity.     

Probabilistic assessment of railway vehicle-curved track systems considering track random irregularities

The randomness of track irregularities directly leads to the random vibration of the vehicle–track systems. To assess the dynamic performance of a railway system in more comprehensive and practical ways, a framework for probabilistic assessment of vehicle-curved track systems is developed by effectively integrating a vehicle–track coupled model (VTCM), a track irregularity probabilistic model (TIPM) with a probability density evolution method (PDEM). In VTCM, the railway vehicle and the curved track are coupled by the nonlinear wheel–rail interaction forces, and through TIPM, the ergodic properties of random track irregularities on amplitudes, wavelengths and probabilities can be properly considered in the dynamic calculations. Lastly, PDEM, a newly developed method for solving probabilistic transmissions between stochastic excitations and deterministic dynamic responses, is introduced to this probabilistic assessment model. Numerical examples validate the correctness and practicability of the proposed models. In this paper, the results of probabilistic assessment are presented to illustrate the dynamic behaviours of a high-speed railway vehicle subject to curved tracks with various radii, and to demonstrate the importance of considering the actual status of wheel–rail contacts and curve negotiation effects in vehicle-curved track interactions.     

Extended applications of track irregularity probabilistic model and vehicle–slab track coupled model on dynamics of railway systems

Track irregularities are inevitably in a process of stochastic evolution due to the uncertainty and continuity of wheel–rail interactions. For depicting the dynamic behaviours of vehicle–track coupling system caused by track random irregularities thoroughly, it is a necessity to develop a track irregularity probabilistic model to simulate rail surface irregularities with ergodic properties on amplitudes, wavelengths and probabilities, and to build a three-dimensional vehicle–track coupled model by properly considering the wheel–rail nonlinear contact mechanisms. In the present study, the vehicle–track coupled model is programmed by combining finite element method with wheel–rail coupling model firstly. Then, in light of the capability of power spectral density (PSD) in characterising amplitudes and wavelengths of stationary random signals, a track irregularity probabilistic model is presented to reveal and simulate the whole characteristics of track irregularity PSD. Finally, extended applications from three aspects, that is, extreme analysis, reliability analysis and response relationships between dynamic indices, are conducted to the evaluation and application of the proposed models.     

Simulation of Train-Track Interaction with Stochastic Track Properties

A numerical method to simulate vertical dynamic interaction between a moving train and a railway track was extended to account for stochastic properties in the track structure. The numerical simulations are carried out in the time-domain with a moving mass model. Full-scale measurements in the field and laboratory experiments were carried out to obtain data for the stochastic track model. The values of the stochastic variables are thus chosen to correspond to real tracks. To investigate the influence of the randomness of selected stochastic parameters in the track structure, the Latin Hypercube sampling method with correlation control was used to generate stochastic realisations.     

Simulation of Train-Track Interaction with Stochastic Track Properties

A numerical method to simulate vertical dynamic interaction between a moving train and a railway track was extended to account for stochastic properties in the track structure. The numerical simulations are carried out in the time-domain with a moving mass model. Full-scale measurements in the field and laboratory experiments were carried out to obtain data for the stochastic track model. The values of the stochastic variables are thus chosen to correspond to real tracks. To investigate the influence of the randomness of selected stochastic parameters in the track structure, the Latin Hypercube sampling method with correlation control was used to generate stochastic realisations.     

Sensitivity of the wheel–rail contact interactions and Dang Van Fatigue Index in the rail with respect to irregularities of the track geometry

This paper investigates the effects of the track geometry irregularities on the wheel–rail dynamic interactions and the rail fatigue initiation through the application of the Dang Van criterion, that supposes an elastic shakedown of the structure. The irregularities are modelled, using experimental data, as a stochastic field which is representative of the considered railway network. The tracks thus generated are introduced as the input of a railway dynamics software to characterise the stochastic contact patch and the parameters on which it depends: contact forces and wheelset–rail relative position. A variance-based global sensitivity analysis is performed on quantities of interest representative of the dynamic behaviour of the system, with respect to the stochastic geometry irregularities and for different curve radius classes and operating conditions. The estimation of the internal stresses and the fatigue index being more time-consuming than the dynamical simulations, the sensitivity analysis is performed through a metamodel, whose input parameters are the wheel–rail relative position and velocity. The coefficient of variation of the number of fatigue cycles, when the simulations are performed with random geometry irregularities, varies between 0.13 and 0.28. In a large radius curve, the most influent irregularity is the horizontal curvature, while, in a tight curve, the gauge becomes more important.     

A model for vehicle–track random interactions on effects of crosswinds and track irregularities

A stochastic mathematical model is developed to evaluate the dynamic behaviours and statistical responses of vehicle–track systems when random system excitations including crosswinds and track irregularities are imposed. In this model, the railway vehicle is regarded as a multi-rigid-body system, the track system is modelled by finite element theory. These two systems are spatially coupled by the nonlinear wheel–rail contact forces and unsteady aerodynamic forces. The high efficiency and accuracy of this stochastic model are validated by comparing to the robust Monte-Carlo method. Numerical studies show that crosswinds have a great influence on the dynamic performance of vehicle–track systems, especially on transverse vibrations. When the railway vehicle initially runs into the wind field, it will experience a severe vibration stage, and then stepping into a relatively steady state where the fluctuating winds and track irregularities will play deterministic roles in the deviations of system responses. Moreover, it is found that track irregularities should be properly considered in the safety assessment of the vehicle even in strong crosswinds.     

基于车激响应的桥梁支座脱空病害识别方法研究

为快速、准确地评估铁路简支梁桥的支座健康状态,分析各影响因素对识别结果的影响,以刚体动力学和结构有限元法为基础建立了车桥耦合动力分析模型,提出了一种以频谱相似性指标构建目标函数、以模型修正方法为主要技术手段的桥梁支座脱空病害识别方法,并在此基础上以某高速铁路32m简支梁桥为工程背景,采用数值模拟和现场试验的方式对所提方法进行了验证。结果表明:该方法可实现支座脱空病害的定位和定量识别,且计算效率和精度均较高,虚假损伤很小;列车行车速度、轨道不平顺谱及列车编组等因素对支座脱空病害识别结果影响较小;现场试验的加速度频谱分析实测值与理论值在低频段吻合良好,各支座识别结果均大于支座刚度限值,支座未发生脱空病害,与支座实际状态一致。     

Sensitivity of train stochastic dynamics to long-term evolution of track irregularities

The influence of the track geometry on the dynamic response of the train is of great concern for the railway companies, because they have to guarantee the safety of the train passengers in ensuring the stability of the train. In this paper, the long-term evolution of the dynamic response of the train on a stretch of the railway track is studied with respect to the long-term evolution of the track geometry. The characterisation of the long-term evolution of the train response allows the railway companies to start off maintenance operations of the track at the best moment. The study is performed using measurements of the track geometry, which are carried out very regularly by a measuring train. A stochastic model of the studied stretch of track is created in order to take into account the measurement uncertainties in the track geometry. The dynamic response of the train is simulated with a multibody software. A noise is added in output of the simulation to consider the uncertainties in the computational model of the train dynamics. Indicators on the dynamic response of the train are defined, allowing to visualize the long-term evolution of the stability and the comfort of the train, when the track geometry deteriorates.     

Simulation of vertical dynamic vehicle–track interaction using a two-dimensional slab track model

The vertical dynamic interaction between a railway vehicle and a slab track is simulated in the time domain using an extended state-space vector approach in combination with a complex-valued modal superposition technique for the linear, time-invariant and two-dimensional track model. Wheel–rail contact forces, bending moments in the concrete panel and load distributions on the supporting foundation are evaluated. Two generic slab track models including one or two layers of concrete slabs are presented. The upper layer containing the discrete slab panels is described by decoupled beams of finite length, while the lower layer is a continuous beam. Both the rail and concrete layers are modelled using Rayleigh–Timoshenko beam theory. Rail receptances for the two slab track models are compared with the receptance of a traditional ballasted track. The described procedure is demonstrated by two application examples involving: (i) the periodic response due to the rail seat passing frequency as influenced by the vehicle speed and a foundation stiffness gradient and (ii) the transient response due to a local rail irregularity (dipped welded joint).