化学成分对亚稳态奥氏体不锈钢车体板材均匀变形及加工硬化行为的影响

基于化学成分对奥氏体不锈钢稳定性和层错能的影响,通过对2 mm厚的冷轧、退火态的304不锈钢板材试样及2种不同标准的301LN不锈钢板材试样在应变速率为3×10~(-4)/s的拉伸实验和应变诱导α′-马氏体转变量的分析测定,研究化学成分对奥氏体不锈钢应变诱导α′-马氏体相变及均匀塑性变形和加工硬化行为的影响,分析冷轧对稳定性和层错能不同的奥氏体不锈钢变形行为的影响.结果表明:随镍当量、层错能和稳定性的增加,拉伸过程中的应变诱导α′-马氏体转变开始的应变量增大,转变速度降低,转变量减小;两种化学成分不同、强度等级相同的301LN冷轧不锈钢板材试样的变形行为差异很大,冷轧预变形对其拉伸过程力学行为的影响也很大,304板材试样的亚稳态奥氏体不锈钢变形特征只在后期有所体现,但由于马氏体转变量少,流变应力相对较低.所得结论为制造不锈钢轻量车体选材和优化塑性成型工艺提供基础数据.     

生活线建设在铁路安全生产中的地位和作用

结合2008年西安铁路局管内自然灾害发生的实际,对生活线建设的地位进行论述,阐述生活线建设在运输安全生产中的作用,认为生活线建设工作是改善职工居住条件,激发职工工作热情,体现以人为本,实现铁路科学发展、和谐发展的具体体现,对铁路安全生产具有重要作用。     

纳米碳纤维混凝土力学性能的试验研究

纳米碳纤维作为一种新型材料,具有高强度,高弹性模量等力学上的优异特性.通过单轴抗压试验和劈裂试验,测试了掺加3种类型纳米碳纤维的普通混凝土和自密实混凝土的基本力学性能,并讨论其最优掺量.实验结果表明:适当掺量且纤维分散良好的纳米碳纤维混凝土28 d抗压强度和劈裂强度均有不同程度的提高,表明纳米碳纤维对于混凝土材料力学性...     

动车组真空断路器隔声罩自然对流研究

建立了轨道交通动车组真空断路器隔声罩内部自然对流传热计算模型,通过基于有限体积法的计算流体动力学(CFD)计算器进行流固耦合传热计算,得到隔音罩内部温度场和流场数据。计算结果表明,发热电阻内部最高温度可达到99℃,已超出真空断路器发热电阻的工作温度范围。提出了两种改进方法,并进行了计算对比。其中将原模型不锈钢材料替换为导热性能更优的铝合金材料的改进方法可以将发热电阻温度降为52℃左右,能满足发热电阻工作温度范围要求。     

高速动车组轮盘用紧固螺栓仿真分析

高速动车组轮装制动盘通过多个螺栓与车轮固定,制动过程中,由于制动盘和螺栓产生热变形,导致螺栓承受较大拉应力,存在失效可能。利用有限元软件ABAQUS,建立了与实际相符的高速动车组轮装制动盘、车轮、联接件、螺栓套的有限元模型,螺栓施加相应的预紧力。计算得到300km/h高速动车组制动盘和螺栓联接件的温度场和应力场结果,校核了螺栓强度,为不同时速的动车组轮装制动盘用螺栓提供了模拟计算方法。在1∶1台架试验上,验证了模型温度场计算的准确性。     

慢性盐缺乏、盐负荷对血清内源性哇巴因水平的影响

目的观察慢性盐缺乏和盐负荷对内源性哇巴因(EO)分泌的影响,探讨在慢性盐缺乏或盐负荷状态下EO对SD大鼠钠代谢和血压的调节作用。方法以含0.02%(低盐)、0.5%(普食)及8%(高盐)的普通加碘盐饲料喂养SD大鼠8周,原子吸收分光光度法检测尿液中钠离子、钾离子浓度,酶联免疫吸附法(ELISA)检测EO水平。结果高盐组SD大鼠血压较同期普食组和低盐组显著性升高(P<0.01)。高盐组24 h尿钠排泄量较普食组和低盐组显著增加(P<0.01)。高盐组24 h尿钾排泄量显著低于对照组和低盐组(P<0.01)。高盐组与普食组比较血清EO水平无统计学差异,低盐组于第4周开始血清EO水平高于普食组和高盐组,有统计学差异(P<0.01)。结论慢性盐缺乏时SD大鼠EO水平升高,提示其为慢性盐缺乏状态下维持血压的调节因子;而慢性盐负荷时血压明显升高,但未发现EO显著升高。     

基于MTSP的机车周转图编制模型与算法

为了提高机车的工作效率，探讨了机车周转图编制模型与算法．对于给定的列车运行图，综合考虑机车使用台数最少和图形均衡性，提出了一种编制机车周转图的新算法．将机车周转图编制问题转化为多旅行商问题（MTSP）并建立数学模型，从而求得问题的最优解．最后，用列车运行图实际数据进行了验证，证明了该算法的有效性．     

基于IECP的CTCS-3列控车载TSM曲线完备性测试用例集生成方法研究

作为CTCS-3级列控系统的核心安全功能,速度-距离模式曲线具有参数输入域规模大、故障模式复杂等特点,如何完备地测试列控车载设备速度-距离监控曲线功能异常困难。提出了一种基于输入等价类划分测试理论的CTCS-3级列控车载目标速度监控曲线完备性测试用例生成方法。首先,结合CTCS-3级列控系统需求规范,建立了满足司机制动优先和设备制动优先两种不同制动优先级情况下的TSM有限状态机模型,并利用反应式状态迁移系统的形式化语义,描述了不同输入情况下模型的内部状态迁移过程。其次,利用I/O等价原理和等价类划分理论,得到了两种不同制动优先情况下的输入等价类划分。在此基础上,通过引入了被测系统的故障模型和故障域范围,采用W-method测试用例集生成方法,在满足模型故障域的条件下,最终得到两种不同制动优先的目标速度监控曲线模型完备测试集。设备制动优先情况生成的测试用例数量高于司机制动优先约33.3%,且所需测试时间和内存消耗更多。     

Implications of path tolerance and path characteristics on critical vehicle manoeuvres

Path planning and path following are core components in safe autonomous driving. Typically, a path planner provides a path with some tolerance on how tightly the path should be followed. Based on that, and other path characteristics, for example, sharpness of curves, a speed profile needs to be assigned so that the vehicle can stay within the given tolerance without going unnecessarily slow. Here, such trajectory planning is based on optimal control formulations where critical cases arise as on-the-limit solutions. The study focuses on heavy commercial vehicles, causing rollover to be of a major concern, due to the relatively high centre of gravity. Several results are obtained on required model complexity depending on path characteristics, for example, quantification of required path tolerance for a simple model to be sufficient, quantification of when yaw inertia needs to be considered in more detail, and how the curvature rate of change interplays with available friction. Overall, in situations where the vehicle is subject to a wide range of driving conditions, from good transport roads to more tricky avoidance manoeuvres, the requirements on the path following will vary. For this, the provided results form a basis for real-time path following.     

Distributed and self-adaptive vehicle speed estimation in the composite braking case for four-wheel drive hybrid electric car

Considering the controllability and observability of the braking torques of the hub motor, Integrated Starter Generator (ISG), and hydraulic brake for four-wheel drive (4WD) hybrid electric cars, a distributed and self-adaptive vehicle speed estimation algorithm for different braking situations has been proposed by fully utilising the Electronic Stability Program (ESP) sensor signals and multiple powersource signals. Firstly, the simulation platform of a 4WD hybrid electric car was established, which integrates an electronic-hydraulic composited braking system model and its control strategy, a nonlinear seven degrees-of-freedom vehicle dynamics model, and the Burckhardt tyre model. Secondly, combining the braking torque signals with the ESP signals, self-adaptive unscented Kalman sub-filter and main-filter adaptable to the observation noise were, respectively, designed. Thirdly, the fusion rules for the sub-filters and master filter were proposed herein, and the estimation results were compared with the simulated value of a real vehicle speed. Finally, based on the hardware in-the-loop platform and by picking up the regenerative motor torque signals and wheel cylinder pressure signals, the proposed speed estimation algorithm was tested under the case of moderate braking on the highly adhesive road, and the case of Antilock Braking System (ABS) action on the slippery road, as well as the case of ABS action on the icy road. Test results show that the presented vehicle speed estimation algorithm has not only a high precision but also a strong adaptability in the composite braking case.