长联公铁两用钢桁梁桥采用速度锁定器装置减震性能研究

长联公铁两用钢桁梁桥固定墩地震响应大,抗震设计困难。通过设置速度锁定装置,并对各种速度锁定器布置方案进行比选分析,研究该类桥梁桥墩采用速度锁定器装置后的减震性能。由于设置速度锁定器装置的活动墩的分担,各方案整体减震率可达到20.5%～47.1%。如锁定墩(设置速度锁定器装置的活动墩)墩高相比固定墩和其他锁定墩墩高矮很多,或者锁定墩一侧未采用速度锁定器装置的活动墩较多,则该锁定墩的地震响应可能超过原固定墩。该类桥梁确定锁定器布置方案时应综合考虑内力和位移的减震效果、锁定力大小,并同时兼顾公路层和铁路层梁-墩相对位移的大小等因素的影响。对长联公铁两用钢桁梁桥,采用速度锁定器装置并优化其布置方案后,可取得较好的减震效果。     

某型舰船阀门内漏温差检测法可行性研究

文章针对某型舰船阀门的使用环境状况和内漏特性，提出一套方便可行的温差检测方法及检测系统，通过检测高温介质断流后阀门发生内漏时其前后温度的差异值，来确定阀门的内漏情况，使阀门内漏得到及时监控和处置。     

桥梁下部结构稳定性分析

在桥梁施工过程中，下部结构位置的准确性对上部结构乃至全桥都有重要的作用。文章以大足朝阳桥为研究对象，采用空间实体有限元模型，分析桥墩发生偏心后下部结构的稳定性，提出了在正常运营过程中要加强桥梁养护、在施工过程中要严格控制定位误差的建议。     

Application of social force model to pedestrian behavior analysis at signalized crosswalk

Limited pedestrian behavior models shed light on the case at signalized crosswalk, where pedestrian behavior is characterized by group or individual evasion with surrounding pedestrians, collision avoidance with conflicting vehicles, and response to signal control and crosswalk boundary. This study fills this gap by developing a microscopic simulation model for pedestrian behavior analysis at signalized intersection. The social force theory has been employed and adjusted for this purpose. The parameters, including measurable and non-measurable ones, are either directly estimated based on observed dataset or indirectly derived by maximum likelihood estimation. Last, the model performance was confirmed in light of individual trajectory comparison between estimation and observation, passing position distribution at several cross-sections, collision avoidance behavior with conflicting vehicles, and lane-formation phenomenon. The simulation results also concluded that the model enables to visually represent pedestrian crossing behavior as in the real world.     

使用30°楔形防松螺纹安装扭矩的建议

为明确30°楔形防松螺纹在同样的施加扭矩下所获得的轴力。试验了30°楔形防松螺纹和普通螺纹经振动防松试验轴力的衰减情况和同扭矩下扭矩系数及轴力的比对试验。从而获得在施加相同扭矩下,30°楔形防松螺纹所获得的轴力比普通螺纹所获得的轴力低。     

A planar quasi-static constraint mode tyre model

The fast-paced, iterative, vehicle design environment demands efficiency when simulating suspension loads. Towards that end, a computationally efficient, linear, planar, quasi-static tyre model is developed in this work that accurately predicts a tyre's lower frequency, reasonably large amplitude, nonlinear stiffness relationship. The axisymmetric, circumferentially isotropic, stiffness equation is discretised into segments, then parameterised by a single stiffness parameter and two shape parameters. The tyre's deformed shape is independent of the overall tyre stiffness and the forces acting on the tyre. Constraint modes capture enveloping and bridging properties and a recursive method yields the set of active constraints at the tyre–road interface. The nonlinear stiffness of a tyre is captured by enforcing unidirectional geometric boundary conditions. The model parameters are identified semi-empirically; simulated cleat test loads match experiments within 7% including nonlinear stiffness when simulating a flat plate test and a discontinuous stiffness when simulating a cleat test.     

单缸摩托车发动机曲柄过量配重的计算与校核

B，θ，C是确定不平衡惯性力椭圆的3个要素，（θ、B／C）决定椭圆的形态，C决定椭圆的大小，而B／C≤cosθ是使M＋N=C的充分必要条件。设计过程中，通过选取合适的θ、B／C值，可以获得理想的椭圆形态，而尽量减小往复力C，如采用轻量化活塞组件，可获得较小的惯性力幅值但要注意（B，θ，C）的变化关系中，避免出现B／C〉cosθ的情况，以防惯性力无端增大。     

A reduced-order nonlinear sliding mode observer for vehicle slip angle and tyre forces

In this paper, a reduced-order sliding mode observer (RO-SMO) is developed for vehicle state estimation. Several improvements are achieved in this paper. First, the reference model accuracy is improved by considering vehicle load transfers and using a precise nonlinear tyre model ‘UniTire’. Second, without the reference model accuracy degraded, the computing burden of the state observer is decreased by a reduced-order approach. Third, nonlinear system damping is integrated into the SMO to speed convergence and reduce chattering. The proposed RO-SMO is evaluated through simulation and experiments based on an in-wheel motor electric vehicle. The results show that the proposed observer accurately predicts the vehicle states.