大跨度钢管混凝土拱桥地震反应分析

利用有限元法分析大跨度钢管混凝土拱桥的地震反应，考虑了剪切变形的影响，用子空间迭代法分析了其振动规律和动力特性，应用反应谱法和时程分析法分析了该拱桥的地震反应，得出了一些有价值的结论。     

公共交通系统营运可靠性研究

优先发展公共交通是大城市解决交通拥堵,实现城市交通可持续发展的一项重要措施,然而,公交营运水平的低下制约着公交的发展。本文借鉴可靠性理论对公共交通营运可靠性进行定义,并对公交营运时间和乘客服务可靠性分别进行了描述,据此建立起公交系统营运可靠性模型,然后采用随机模拟技术(即Monte Carlo模拟)进行求解,通过算例说明模型的可行性,最后通过分析可靠性模型得出大型活动期间改善公交营运的途径。     

超大跨度斜拉桥施工过程力学行为

斜拉桥结构效应在施工过程中具有典型的时空变化特性，但目前对效应的时程特性及时空包络关注较少。建立精细的几何非线性分析模型，分析主跨1088m的苏通大桥施工过程力学行为，包括施工阶段效应增量、效应时程、效应包络及恒载效应。研究结果有助于结构设计和施工控制。     

大直径钢管桩承载力恢复过程试验研究

针对目前预制桩承载力恢复特性研究与工程应用中的不足,依托西非某海工工程,提出高应变法。采用对同一钢管桩进行初打与不同休止时间复打相结合的试验方法,研究了大直径钢管桩沉桩后的承载力恢复过程。结合地质情况、沉桩与试验结果,得到了钢管桩承载力、侧阻力及端阻力随时间变化的一般规律及影响因素,并通过静载试验对研究结果进行了验证。该研究在提高项目施工效率、降低成本的同时,还得到了有意义的规律与结论,可为后续类似项目提供参考。     

Modeling duration choice in space–time multi-state supernetworks for individual activity-travel scheduling

Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies and emerging modalities. However, duration choice of activities and home-stay has not been incorporated in this formalism yet. This study models duration choice in the state-of-the-art multi-state supernetworks. An activity link with flexible duration is transformed into a time-expanded bipartite network; a home location is transformed into multiple time-expanded locations. Along with these extensions, multi-state supernetworks can also be coherently expanded in space–time. The derived properties are that any path through a space–time supernetwork still represents a consistent activity-travel pattern, duration choice are explicitly associated with activity timing, duration and chain, and home-based tours are generated endogenously. A forward recursive formulation is proposed to find the optimal patterns with the optimal worst-case run-time complexity. Consequently, the trade-off between travel and time allocation to activities and home-stay can be systematically captured.     

Autonomous cars: The tension between occupant experience and intersection capacity

Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks.In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation.On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda.This paper concludes with a brief discussion of research needs to advance this line of inquiry.     

Tuning of transfer functions for analysis of wave–ship interactions

Transfer functions are often used together with a wave spectrum for analysis of wave–ship interactions, where one application addresses the prediction of wave-induced motions or other types of global responses. This paper presents a simple and practical method which can be used to tune the transfer function of such responses to facilitate improved prediction capability. The input to the method consists of a measured response, i.e. time series sequences from a given sensor, the 2D wave spectrum characterising the seaway in which the measurements are taken, and an initial estimate of the transfer function for the response in study. The paper presents results obtained using data from an in-service container ship. The 2D wave spectra are taken from the ERA5 database, while the transfer function is computed by a simple closed-form expression. The paper shows that the application of the tuned transfer function leads to predictions which are significantly improved compared to using the transfer function without tuning.     

基于ANN的船舶撞击高桩码头群桩损伤位置预测

本文采用有限元软件ABAQUS建立了船舶撞击高桩码头群桩的空间有限元模型。通过计算评估了撞击力、桩体刚度、撞击位置和撞击角度下对群桩结构损伤位置的影响。基于人工神经网络(ANN)方法,对不同参数组合下的群桩结构损伤位置进行了预测,并对ANN方法的可行性进行了评估。     

Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach

Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.