深基坑双排桩结构受力变形机理及其计算模型研究

近年来,为了适应国内城市地下工程建设蓬勃发展带来的地下工程密集化、复杂化等方面的需要,深基坑开挖时双排桩围护结构因具有侧向刚度大、控制变形能力强、施工快速等特点在各种大型深基坑工程中得到了较为广泛的推广和应用。但实际设计过程中,由于该结构的变形机理与计算模型尚未有统一的理论,其设计方法比较杂乱,存在一定程度的保守设计。依托南京梅子洲青奥城地下空间工程及其现场监测数据,采用有限元计算模型对近年来在地下工程中逐渐得到推广使用的双排桩围护结构的变形机理、土压力分布规律等进行探讨和研究;在此基础上,结合与目前广为应用的理正双排桩模型和新规范双排桩模型的对比分析,研究并提出更吻合实际的、精确反映结构变形和力学特性的双排桩围护结构的修正设计计算模型,该模型架构清晰,准确性高,贴近实际工程设计,可以大力推广应用于双排桩结构的计算分析。     

电动汽车整车运行性能检测试验技术

电动汽车的生产和制造需要符合相关的标准,并且还要对整车的性能进行测试,只有这样才能更好的符合汽车上路的条件。本文主要是将国标要求作为基础来对电动汽车的最高车速、滑行能力、加速性能、制动性能和爬坡能力和能量消耗率和续航里程进行测试,通过实施一定的检测试验方法和配套的相关试验设备来做好检测,并且要对测试的结果进行分析,对电动汽车的运行性能进行进一步的优化,从而推进我国电动汽车行业的更好发展和进步。     

纯电动商用车异质队列的多目标控制

队列行驶的研究能有效解决商用车货运安全、能耗浪费和环境污染等问题,但现有研究多基于单一跟车目标控制的匀质队列,这在货运场景中无法达到很好的控制效果。本文中构造了纯电动异质商用车队列,为其设计了分布式非线性模型预测控制器。根据道路环境信息和车辆跟车、安全、舒适和节能等特性,分别建立了领航车和跟随车的控制器模型,实现异质队列的多目标控制。为验证所提出控制方法的有效性,由5辆动力学特性相异的商用车组成队列,并搭建了控制仿真平台进行Trucksim/Simulink联合仿真。结果表明,本文中提出的控制算法能有效实现异质商用车队列的多目标控制,与PID定速巡航控制相比,能耗可降低5.3%以上。     

基于改进IDM-GARCH模型的速度波动不确定性研究（双语出版）

为定量分析跟驰行为中由驾驶人感知不确定性产生的速度波动不确定性，基于改进IDM-GARCH模型研究了后车速度波动存在的异方差性。首先，提出在经典智能驾驶模型中加入速度差刺激项和非对称系数，以增强速度波动方程残差项的实际意义。在此基础上，为度量速度波动的不确定性引入异方差的思想，并验证速度波动方程残差项的异方差性，最后运用广义自回归条件异方差模型对其异方差性建模。实证分析中，采用了美国联邦公路管理局主导下的下一代仿真项目中真实有效的跟驰数据。研究结果表明：改进的IDM模型能有效地拟合实际跟驰行为中后车的速度变化，且较经典IDM模型在精度上有了很大提高；同时，GARCH类模型估计的条件方差也能准确反映后车速度波动的趋势和幅度，以及不同驾驶人驾驶行为的差异。     

城市轨道交通车辆能耗计量及管理系统

介绍了城市轨道交通车辆能耗计量及管理系统的结构、功能.城市轨道交通车辆能耗计量及管理系统采用六通道能耗计量装置和RFID(射频识别)列车定位技术,实现了对地铁车辆能耗的分类计量.建立GPRS(通用分组无线服务)无线传输数据机制和地铁车辆能耗管理平台,处理并存储能耗数据,自动生成曲线和统计报表,实现地铁车辆能耗信息化管理.该系统已在上海轨道交通1号线01A02车型上试点应用,基本功能已得到验证.     

城市轨道交通站点客流不确定性研究

为提高城市轨道交通站点客流预测的可靠性,在分析客流不确定性影响因素的基础上,基于ARIMA-GARCH模型,依据南京地铁珠江路站点客流数据对客流不确定性进行建模和预测,并从预测置信区间和无效覆盖率两方面与传统的时间序列进行对比分析,研究结果表明,ARIMA-GARCH能够较好地拟合客流波动情况,为城市轨道交通运营与管理提供理论依据。     

基于熵权-物元模型的轨道交通建设时序研究

结合轨道交通建设特点,基于物元可拓数学方法、熵权理论和关联度函数,建立轨道交通建设时序决策的熵权物元可拓模型。该方法首先结合熵权理论,根据指标差异度对评价指标进行客观赋权;其次通过客观标准对评价指标的经典域进行区间界定,利用综合关联度将多指标的评价模型转化为单目标决策;然后依据定量测算的加权综合关联度值综合判定建设时序,最后以成都市轨道交通线网进行实例分析。结果表明:该决策算法所确定的结果与实际建设时序一致,且该算法可以极大拓展研究范围,表征更多分异信息,有效支撑城市轨道交通线网建设时序的综合决策。     

Parameters optimisation of a vehicle suspension system using a particle swarm optimisation algorithm

The purpose of this paper is to determine the lumped suspension parameters that minimise a multi-objective function in a vehicle model under different standard PSD road profiles. This optimisation tries to meet the rms vertical acceleration weighted limits for human sensitivity curves from ISO 2631 [ISO-2631: guide for evaluation of human exposure to whole-body vibration. Europe; 1997] at the driver's seat, the road holding capability and the suspension working space. The vehicle is modelled in the frequency domain using eight degrees of freedom under a random road profile. The particle swarm optimisation and sequential quadratic programming algorithms are used to obtain the suspension optimal parameters in different road profile and vehicle velocity conditions. A sensitivity analysis is performed using the obtained results and, in Class G road profile, the seat damping has the major influence on the minimisation of the multi-objective function. The influence of vehicle parameters in vibration attenuation is analysed and it is concluded that the front suspension stiffness should be less stiff than the rear ones when the driver's seat relative position is located forward the centre of gravity of the car body. Graphs and tables for the behaviour of suspension parameters related to road classes, used algorithms and velocities are presented to illustrate the results. In Class A road profile it was possible to find optimal parameters within the boundaries of the design variables that resulted in acceptable values for the comfort, road holding and suspension working space.     

温州状元岙化工码头工程潮流泥沙数模研究

采用水动力泥沙条件、底床冲淤演变分析及二维潮流泥沙数值模拟手段,对拟建的温州港状元岙港区化工码头工程方案进行了研究。研究结果表明:(1)工程海区潮汐属于正规半日潮类型,为强潮海区;(2)工程海区潮流性质属于不规则半日浅海潮流,潮流运动呈往复流形式;(3)工程海域深槽多年来在波浪潮流作用下一直处于稳定状态;(4)规划的化工码头走向与涨落潮流走向基本一致;(5)规划的化工码头实施后工程附近海区的涨落潮流速呈增加趋势,码头前沿会略有冲刷;(6)化工码头建设对锚地流场没有影响;(7)化工码头工程方案是合理可行的。     

An easy procedure to determine Magic Formula parameters: a comparative study between the starting value optimization technique and the IMMa optimization algorithm

In 2004, a new searching algorithm for Magic Formula tyre model parameters was presented. Now, a summary of the results, for pure and combined slip, that this algorithm is able to achieve is presented. The Magic Formula tyre model needs a set of parameters to describe the tyre properties. The determination of these parameters is dealt with in this article. A new method, called IMMa Optimization Algorithm (IOA), based on genetic techniques, is used to determine these parameters. Here, we show the computational cost that has been used to obtain the optimum parameters of every characteristic of the Magic Formula tyre model, called Delft Tyre 96. The main advantages of the method are its simplicity of implementation and its fast convergence to optimal solution, with no need of deep knowledge of the searching space. Hence, to start the search, it is not necessary to know a set of starting values of the Magic Formula parameters (null sensitivity to starting values). The search can be started with a randomly generated set of parameters between [0, 1]. Nowadays, MF-Tool, an application developed by TNO, uses an optimization technique to fit Magic Formula parameters from Matlab toolbox [van Oosten, J.J.M. and Bakker, E., 1993, {Determination of magic tyre model parameters}. Vehicle System Dynamics, 21, 19–29; van Oosten, J.J.M., Savi, C., Augustin, M., Bouhet, O., Sommer, J. and Colinot, J.P., 1999, {Time, tire, measurements, forces and moments, a new standard for steady state cornering tyre testing}. EAEC Conference, Barcelona, 30 June–2 July.]. We refer to that algorithm as the starting value optimization technique. The comparison between the optimization technique employed by TNO and the proposed IOA method is discussed in this article. In order to give a relative idea of adjustment accuracy, the sum-squared error and the mean-squared error, from the curves of the tyre model with the parameters optimized by both applications compared with test data are evaluated.