军港磁谐振式无线供电动态调谐技术分析

磁谐振式无线电能传输具有高效率、灵活性和安全性的优势,利用它来实现军港无线供电具有广阔的应用前景。本文首先建立了磁谐振式无线电能传输系统的互感电路模型,分析了系统特性;在此基础上系统分析了磁谐振式无线电能传输动态调谐技术;最后立足于实际应用提出磁谐振式无线电能传输技术的军港应用亟待解决的几个问题。     

桩基建模方法对自升式钻井平台动力响应的影响

随着海洋油气开采作业水深的不断增加,海洋平台固有频率随之降低,易与相同频率成分的波浪产生共振,因此对平台动力响应特性研究是非常有必要的,而桩基模型在平台动力响应分析中发挥着关键作用。以某400英尺自升式钻井平台研究对象,基于等效建模的思想,分别建立了固支桩基、铰接桩基、线性弹簧桩基及非线性弹簧桩基四种有限元模型,并对其进行静力分析、模态分析及瞬态动力学分析,通过对比得到的振动频率、动力放大因子及波流惯性力,得出弹簧桩基模型在平台动力响应分析中的有效性及合理性结论。     

Large-scale dynamic transportation network simulation: A space-time-event parallel computing approach

This paper describes a computationally efficient parallel-computing framework for mesoscopic transportation simulation on large-scale networks. By introducing an overall data structure for mesoscopic dynamic transportation simulation, we discuss a set of implementation issues for enabling flexible parallel computing on a multi-core shared memory architecture. First, we embed an event-based simulation logic to implement a simplified kinematic wave model and reduce simulation overhead. Second, we present a space-time-event computing framework to decompose simulation steps to reduce communication overhead in parallel execution and an OpenMP-based space-time-processor implementation method that is used to automate task partition tasks. According to the spatial and temporal attributes, various types of simulation events are mapped to independent logical processes that can concurrently execute their procedures while maintaining good load balance. We propose a synchronous space-parallel simulation strategy to dynamically assign the logical processes to different threads. The proposed method is then applied to simulate large-scale, real-world networks to examine the computational efficiency under different numbers of CPU threads. Numerical experiments demonstrate that the implemented parallel computing algorithm can significantly improve the computational efficiency and it can reach up to a speedup of 10 on a workstation with 32 computing threads.     

铁路路基动态变形模量的数值模拟分析

介绍铁路路基动态变形模量理论计算公式的推导及动态变形模量的测试原理,采用有限元软件模拟动态变形模量的测试过程,分析承载板与土体接触压力、路基动态变形模量的影响因素,并计算动态变形模量的有效测试深度.结果表明:在承载板中心一定范围内,接触压力模拟结果较理论计算值大;土体的动弹性模量对接触压力影响很小,可以忽略;路基动态变形模量测试冲击荷载作用下,土体只发生弹性变形;动态变形模量与土体动弹性模量呈线性关系,路基动态变形模量的模拟结果大于理论计算值;土体的泊松比对动态变形模量影响较小;动态变形模量有效测试深度建议取0.5~0.6 m.     

考虑收益管理的高铁平行车次动态差别定价

基于RP(Revealed Preference)和SP(Stated Preference)调查数据，利用潜在类别模型对高铁旅客进行细分，得到旅客对平行车次不同服务属性，如列车运行时间、发车时段和舒适度的偏好程度，并对其进行量化；引入收益管理，以多列车整体收益最大为目标，构建平行车次动态差别定价模型，并设计模拟退火算法进行求解；最后，通过京沪高铁进行实例验证.结果表明：与固定票价进行客票销售相比，所提方案能够适应高峰期和平峰期不同客流特点，提高铁路客票总收益，为高铁平行车次灵活定价提供参考.     

一种基于动态分析的突变和异常波动预警方法

针对模拟量的突变和异常波动预警,给出一种基于动态分析的、可以应用于各种模拟量的统一预警方法,该方法已被应用于CSM-TH型集中监测程序和智能分析系统中,在多条线700余站现场运行的7年中,收到良好效果,得到用户认可。     

基于客流需求的城市轨道交通动态时刻表优化模型

为使城市轨道交通列车运行时刻表更贴合客流需求,依据不断变化的客流需求确定每列车的发车时刻和停站时间,采用多目标优化方法构建以乘客出行时间费用和列车运行时间费用最小为目标、列车发车时刻和停站时间为决策变量的城市轨道交通动态时刻表优化模型,并采用粒子群算法求解。以广州地铁13号线为例进行验证,结果表明优化后的时刻表更满足客流需求,能有效地提高乘客出行效率,具有更好的动态适应性。     

Bottleneck congestion and distribution of work start times: The economics of staggered work hours revisited

Since the seminal work of Henderson (Henderson, J.V., 1981. The economics of staggered work hours. Journal of Urban Economics 9 (3), 349–364), a number of studies have examined the effect of staggered work hours by analyzing models of work start time choice that consider the trade-off between negative congestion externalities and positive production externalities. However, these studies employed flow congestion models to describe traffic congestion. This study develops a model of work start time choice with bottleneck congestion and discloses the intrinsic properties of the model. To this end, this study extends Henderson’s model to incorporate bottleneck congestion. By utilizing the properties of a potential game, we characterize equilibrium and optimal distributions of work start times. We also show that Pigouvian tax/subsidy policies generally yield multiple equilibria and that the first-best optimum must be a stable equilibrium under Pigouvian policies, whereas the second-best optimum in which policymakers cannot eliminate queuing congestion can be unstable.     

Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles

Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.     

考虑移步需求的无桩型共享单车动态调度研究

共享单车系统自发的不均衡性导致单车数量分布与用户需求分布之间产生偏移，降低了系统服务能力，需要调度实现再平衡. 现有动态调度算法缺乏考虑起点车辆供给不足，用户在出行过程中“再次”取车的移步需求，难以准确识别用户真实的出行需求分布，降低了调度效果. 本文提出以用户出行选择行为为下层，以调度车辆路径规划为上层的双层规划模型框架，设计结合仿真系统的启发式求解算法. 算例场景基于上海市虹口、杨浦区共享单车历史出行数据搭建，并进行网格化处理. 算例结果表明，模型能有效识别移步需求，提高共享单车的供需匹配能力. 针对各类调度资源配置情况，共享单车的供需匹配率提升18.07%~ 19.89%，提高了共享单车系统的管理效率.