Vertical random vibration analysis of vehicle–track coupled system using Green's function method

A vertical vehicle–track coupled dynamic model, consisting of a high-speed train on a continuously supported rail, is established in the frequency-domain. The solution is obtained efficiently by use of the Green's function method, which can determine the vibration response over a wide range of frequency without any limitations due to modal truncation. Moreover, real track irregularity spectra can be used conveniently as input. The effect of the flexibility of both track and car body on the entire vehicle–track coupled dynamic response is investigated. A multi-body model of a vehicle with either rigid or flexible car body is defined running on three kinds of track: a rigid rail, a track stiffness model and a Timoshenko beam model. The results show that neglecting the track flexibility leads to an overestimation of both the contact force and the whole vehicle vibration response. The car body flexibility affects the ride quality of the vehicle and the coupling through the track and can be significant in certain frequency ranges. Finally, the effect of railpad and ballast stiffness on the vehicle–track coupled vibration is analysed, indicating that the stiffness of the railpad has an influence on the system in a higher frequency range than the ballast.     

Speed variation during peak and off-peak hours on urban arterials in Shanghai

Increased speed variation on urban arterials is associated with reductions in both operational performance and safety. Traffic flow, mean speed, traffic control parameters and geometric design features are known to affect speed variation. An exploratory study of the relationships among these variables could provide a foundation for improving the operational and safety performance of urban arterials, however, such a study has been hampered by problems in measuring speeds. The measurement of speed has traditionally been accomplished using spot speed collection methods such as radar, laser and loop detectors. These methods can cover only limited locations, and consequently are not able to capture speed distributions along an entire network, or even throughout any single road segment. In Shanghai, it is possible to acquire the speed distribution of any roadway segment, over any period of interest, by capturing data from Shanghai’s 50,000+ taxis equipped with Global Positional Systems (GPS). These data, hereafter called Floating Car Data, were used to calculate mean speed and speed variation on 234 road segments from eight urban arterials in downtown Shanghai. Hierarchical models with random variables were developed to account for spatial correlations among segments within each arterial and heterogeneities among arterials. Considering that traffic demand changes throughout the day, AM peak, Noon off-peak, and PM peak hours were studied separately. Results showed that increases in number of lanes and number of access points, the presence of bus stops and increases in mean speed were all associated with increased speed variation, and that increases in traffic volume and traffic signal green times were associated with reduced speed variation. These findings can be used by engineers to minimize speed differences during the road network planning stage and continuing through the traffic management phase.     

Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

地铁车站结构随机振动响应分析

基于地震反应的随机非确定性,运用基于概率统计方法的随机振动理论进行结构抗震分析,考察结构的动力可靠度,是一种合理的设计方法。运用虚拟激励法对青岛地铁五四广场站进行随机振动分析,避免了传统方法计算的冗繁,得到了具有统计意义的结构动力响应。考虑x向功率谱输入时,弯矩分布较为均匀;地铁结构体型变化较大的部位剪力明显增大;柱底剪力较小,边跨柱剪力小于中跨柱底剪力。考虑y向功率谱函数输入时,沿梁轴向剪力值逐渐增大,柱底剪力明显大于x向输入时的柱底剪力,边跨柱柱底剪力大于中跨柱底剪力。所得结论为地铁站这一复杂结构形式进行基于可靠度理论的设计提供了依据,可以作为同类设计的参考指导。     

实Banach空间中一类非线性算子不动点的收敛定理

在Banach空间中给出算子的带误差项的Krasnoselskij（以下简写K）迭代序列，Mann迭代序列的收敛定理，此结果对当前该领域中某些结果的推广和概括。     

随机响应约束下的桁架结构拓扑优化

研究随机响应约束下的桁架结构拓扑优化问题具有重要的工程应用前景.文章采用自适应遗传算法(AGA)求解了随机响应约束下的桁架结构拓扑优化问题.通过引入海明距离生成高质量的初始种群、采用自适应的交叉和变异算子以及对适应度函数进行线性标定这三个步骤改进了遗传算法的搜索效率以及收敛性.在拓扑优化列式中考虑杆件以及各自由度的拓扑变量以精确地模拟优化过程中杆件和结点的删除.建立了随机载荷作用下结构均方响应的表达式,并以此作为拓扑优化问题的约束条件.另外,提出了一些启发式算法来引导杆件和结点的删除.最后,通过对随机激励下的二维桁架以及三维桁架进行拓扑优化计算,证明了本文方法的实用性和有效性.     

桥梁结构随机振动分析

桥梁结构的随机振动有别于其他结构。由于车辆在桥上的位置是不断变化的,因此,即使作为输入的随机激励是平稳随机过程,车桥的动力响应也超出平稳随机过程的范围,即质量在梁上不断的运动,使系统运动方程组成为一个时变系数的二阶微分方程组,一般只能采用逐步积分的数值方法,也可以用频域法,假定其频率响应函数在瞬间不随时间变化,近似的处理这种时变性问题。     

随机减量法识别转向架构架的频率

随机减量法是一种随机激扰下的模态参数识别方法。在实际线路上对CW-200转向架构架的振动加速度进行了测量,并依据随机减量法对测得的加速度数据进行了构架的三阶刚体模态的识别,得到了三阶刚体模态对应的频率。证实了随机减量法识别构架模态参数的可行性。     

靠船墩可靠性设计方法

通过对靠船墩三维结构随机力学分析,提出基于可靠度理论下的靠船墩设计方法,可直接应用于工程实践