喀什九道桥静载试验分析

文章以喀什九道桥为例,采用Midas梁格法建模对该桥的静力位移以及静力应变等参数进行静载试验分析,并通过与实测数据的比较,对该桥梁结构在荷载作用下的承载能力及工作能力作出综合评价。     

大跨度悬浇钢筋混凝土拱桥合龙施工技术研究

合龙段是悬浇钢筋混凝土拱桥施工的重点和难点,其直接关系到桥梁结构成桥后的线形以及受力状态,进而决定桥梁施工完成后是否达到合理成桥状态。文章以贵州木蓬特大桥为工程背景,以其合理成桥状态为目标,利用Midas/Civil有限元分析软件对结构进行静力计算,分析了不同合龙方案、合龙温度以及拱圈合龙后的拆索顺序对成桥后主拱圈的应力和挠度的影响,为以后同类型桥梁的合龙施工提供借鉴。     

东营市北外环桥少背索斜拉桥总体静力计算分析

本文以东营市北外环桥为例,详细介绍少背索斜拉桥受力特点,并通过有限元静力模型计算,分别对桥梁的挠度、应力、索力和稳定性进行数值分析,得到少背索斜拉桥总体静力计算结果。     

紫阳汉江特大桥主墩深水钢吊箱静动力分析

钢吊箱结构整体与局部应力计算和稳定性分析是桥梁深水施工的关键。文章借助大型通用有限元结构分析软件ANSYS8．1,采用空间梁单元Beam188单元和空间壳单元Shell63单元建立紫阳汉江特大桥主墩深水钢吊箱的空间有限元模型,对该钢吊箱进行静力和动力分析,为紫阳汉江特大桥主墩深水施工提供参数依据。     

跨越陡峭山谷高墩连续梁桥施工关键技术及结构稳定性研究

本文依托淄河主线桥工程对跨越陡峭山谷条件下的高墩连续梁桥施工关键技术和结构稳定性能进行研究,介绍了高墩连续梁桥的施工工艺以及结构稳定性的分析方法,并采用有限元软件Midas civil对淄河主线桥第五联左幅进行建模仿真。基于有限元模型与计算结果对此高墩连续梁桥各主要组成部分进行应力分布状态和结构稳定性的分析研究,通过有限元仿真计算和理论分析,得出成桥状态下高墩连续梁各部分处于最不利工况组合下的应力、位移与最大应力所在位置。     

拱形索塔景观斜拉桥设计分析

临连高速公路泉子坡天桥为拱形索塔景观斜拉桥,文章介绍了该桥设计要处理的重点问题与总体设计方案,并采用MIDAS结构分析软件建立全桥空间杆系模型进行了结构静力与稳定分析,验证了该桥设计方案的合理性。     

某大跨连续刚构桥静动载试验研究

某桥主桥为预应力混凝土连续钢构桥。为了检测桥梁结构的静力和动力性能,鉴定桥梁的承载能力,对该桥进行了静动载试验。     

新隧道爆破开挖对邻近隧道的影响分析

通过建立静力模型模拟既有隧道衬砌的现有受力状态并分析新隧道开挖时引起既有隧道的衬砌应力重分布;然后建立动力模型分析新隧道爆破时应力波在既有隧道二次衬砌中引起的应力状态;将静力模型和动力模型中隧道衬砌的应力进行矢量叠加,评判新隧道爆破开挖对既有隧道的影响。结果表明新建隧道爆破开挖对既有隧道的应力分布有较大影响,使得既有隧道二次衬砌近新隧道侧边墙处拉应力达到1.57MPa,超出混凝土抗拉强度,建议对新隧道施工采取必要的控制措施,从而保证既有隧道的安全。     

大跨径钢管混凝土斜靠式拱桥非线性几何稳定分析

针对斜靠式拱桥的非线性稳定问题,以拟建中的一座跨径100m的斜靠式拱桥为研究对象,采用通用程序ANSYS建立该桥的空间有限元计算模型,分工况对其成桥状态进行了线弹性和几何非线性稳定计算,对桥梁的失稳特征进行了分析,分析结果为此类桥梁的设计提供了参考。     

大跨径上承式箱型拱桥地震反应分析

文章以一座大跨径上承式箱型拱桥为例,通过阐述工程概况,建立成桥状态下的有限元模型,利用反应谱法和时程分析法计算分析其地震响应。结果表明,该桥抗震性能良好。     

基于荷载试验的刚架拱桥修正模型计算评估法

文章针对刚架拱桥的承载能力评估问题进行研究,提出刚架拱桥承载能力评估方法——动静载试验评估法,利用随机振动的动力测试的数据,通过基于敏感性设计参数模型修正法对刚架拱桥有限元模型进行修正,并结合动静载试验实测数据与修正后的模型理论计算值进行对比分析,使有限元模型更好地反映逼近损伤后的刚架拱桥整体结构受力特性,从而对钢筋混凝土刚架拱桥承载能力进行评估。     

TLNET和SPS在输油管道仿真中的应用

TLNET和SPS是两款常用的输油水力仿真软件。为了比较两者的使用特点和计算结果的准确性，分别从软件的基本模型元件和模型调试2个方面进行了介绍，并以某成品油管道为例，采用2种软件分别进行了稳态模拟和动态模拟。结果表明：TLNET和SPS稳态等温计算和动态计算的结果差别很小，但在稳态换热计算存在一定差异。建议在管道规划、方案比选等前期阶段采用TLNET；而在管道设计、生产运行等后期阶段采用SPS．     

The kinematic wave model with finite decelerations: A social force car-following model approximation

This paper derives a five-parameter social force car-following model that converges to the kinematic wave model with triangular fundamental diagram. Analytical solutions for vehicle trajectories are found for the lead-vehicle problem, which exhibit clockwise and counter-clockwise hysteresis depending on the model’s parameters and the lead vehicle trajectory. When coupled with a stochastic vehicle dynamics module, the model is able to reproduce periods and amplitudes of stop-and-go waves, as reported in the field. The model’s stability conditions are analysed and its trajectories are compared to real data.     

太平特大桥桩基自平衡法静载试验分析

文章结合广深沿江高速公路A2合同段太平特大桥工程实例,介绍了桩基自平衡法静载试验的原理及过程,并通过实例计算分析,论证了该试验方法的合理性与实用性。     

Online calibration for microscopic traffic simulation and dynamic multi-step prediction of traffic speed

Simulating driving behavior in high accuracy allows short-term prediction of traffic parameters, such as speeds and travel times, which are basic components of Advanced Traveler Information Systems (ATIS). Models with static parameters are often unable to respond to varying traffic conditions and simulate effectively the corresponding driving behavior. It has therefore been widely accepted that the model parameters vary in multiple dimensions, including across individual drivers, but also spatially across the network and temporally. While typically on-line, predictive models are macroscopic or mesoscopic, due to computational and data considerations, nowadays microscopic models are becoming increasingly practical for dynamic applications. In this research, we develop a methodology for online calibration of microscopic traffic simulation models for dynamic multi-step prediction of traffic measures, and apply it to car-following models, one of the key models in microscopic traffic simulation models. The methodology is illustrated using real trajectory data available from an experiment conducted in Naples, using a well-established car-following model. The performance of the application with the dynamic model parameters consistently outperforms the corresponding static calibrated model in all cases, and leads to less than 10% error in speed prediction even for ten steps into the future, in all considered data-sets.     

Transit technology investment and selection under urban population volatility: A real option perspective

This paper addresses transit technology investment issues under urban population volatility using a real option approach. Two important problems are investigated: which transit technology should be selected and when should it be introduced. A real option model is proposed to incorporate explicitly the effects of transit technology investment on urban spatial structure in terms of households’ residential location choices and housing market. The trigger population thresholds for investing in a transit technology project and for shifting from a transit technology to another are explored analytically. Comparative static analyses of the urban system and transit technology investment are also carried out. It was found that (i) transit technology investment can induce urban sprawl; (ii) ignoring the effects of transit technology investment on urban spatial equilibrium can lead to a late investment; and (iii) there is a significant difference in the trigger population thresholds for transit technology shift estimated by the net present value approach and the real option approach.     

Road pricing with complications

The rationale for congestion charges is that by internalising the marginal external congestion cost, they restore efficiency in the transport market. In the canonical model underlying this view, congestion is a static phenomenon, users are taken to be homogenous, there is no travel time risk, and a highly stylised model of congestion is used. The simple analysis also ignores that real pricing schemes are only rough approximations to ideal systems and that inefficiencies in related markets potentially affect the case for congestion charges. The canonical model tends to understate the marginal external congestion cost because it ignores user heterogeneity and trip timing inefficiencies. With respect to the relevance of interactions between congestion and congestion charges and tax distortions and distributional concerns, recent insights point out that there is no general case for modifying charges for such interactions. Therefore the simple Pigouvian rule remains a good first approximation for the design of road charging systems.     

广西三江波里一桥半幅施工方案内力分析

文章针对广西三江波里一桥改建施工的实际情况,提出了桥梁半幅施工方案,并借助不同施工条件下成桥内力计算结果,探讨了桥梁半幅施工方案结构体系转换前后的内力变化情况,对比分析了半幅施工方案和整幅施工方案的成桥内力.分析表明,波里一桥半幅施工方案是可行的.     

A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting

The k-nearest neighbor (KNN) model is an effective statistical model applied in short-term traffic forecasting that can provide reliable data to guide travelers. This study proposes an improved KNN model to enhance forecasting accuracy based on spatiotemporal correlation and to achieve multistep forecasting. The physical distances among road segments are replaced with equivalent distances, which are defined by the static and dynamic data collected from real road networks. The traffic state of a road segment is described by a spatiotemporal state matrix instead of only a time series as in the original KNN model. The nearest neighbors are selected according to the Gaussian weighted Euclidean distance, which adjusts the influences of time and space factors on spatiotemporal state matrices. The forecasting accuracies of the improved KNN and of four other models are compared, and experimental results indicate that the improved KNN model is more appropriate for short-term traffic multistep forecasting than the other models are. This study also discusses the application of the improved KNN model in a time-varying traffic state.     

Modeling schedule recovery processes in transit operations for bus arrival time prediction

Many existing algorithms for bus arrival time prediction assume that buses travel at free‐flow speed in the absence of congestion. As a result, delay incurred at one stop would propagate to downstream stops at the same magnitude. In reality, skilled bus operators often constantly adjust their speeds to keep their bus on schedule. This paper formulates a Markov chain model for bus arrival time prediction that explicitly captures the behavior of bus operators in actively pursuing schedule recovery. The model exhibits some desirable properties in capturing the schedule recovery process. It guarantees provision of the schedule information if the probability of recovering from the current schedule deviation is sufficiently high. The proposed model can be embedded into a transit arrival time estimation model for transit information systems that use both real‐time and schedule information. It also has the potential to be used as a decision support tool to determine when dynamic or static information should be used.