火灾高温下盾构隧道衬砌结构热力耦合模型试验

为研究火灾高温下盾构隧道衬砌结构的热力耦合行为,利用自主研制的温度加载设备和衬砌管环外压加载设备,分别设计并开展整环衬砌结构的无外压受热模型试验和热力耦合模型试验。试验使用不考虑接头效应的钢纤维混凝土匀质管片。首先,介绍2种试验设备的原理、主要构造和各类参数;在此基础上,针对模型试验过程进行细致的说明。然后,通过对衬砌管片结构形式的分析确定试验的火灾加载工况;详尽描述不同试验的相关结果,重点分析衬砌结构内表面各处温度场的变化过程、分布情况、管片的变形结果及破坏模式。研究结果表明：温度加载设备和衬砌管环外压加载设备能够较好的满足整环衬砌热力耦合研究的模型试验要求;试验初期底部管片的升温速率相对顶部管片有所滞后,但各部分间的温差数值随加热的持续进行会逐渐减小,衬砌结构内部能够形成稳定的温度场;无外力作用下匀质管片的破坏形式表现为沿幅宽方向的贯穿裂缝,各管片结构的裂缝发展路径存在差异;衬砌管片由于外压作用产生的压应变随温度的升高而减小;外压荷载对衬砌结构在高温下产生的膨胀变形存在抑制效果。研究结果可为盾构隧道整环衬砌结构热力耦合研究的进一步发展提供参考。     

薄壁墩墩顶拉力简化计算

针对薄壁墩、花瓶墩等结构,提出墩顶带拉杆的Y形墩模型,给出了墩顶拉力的简化计算公式。     

多方式多类型交通分配模型(MMA)在收费型公路网中的应用研究

在对收费型公路运营模式进行研究的基础上,利用交通规划软件建立了基于广义费用的交通流量分配模型即多方式多类型交通分配模型,通过对模型参数的科学标定和网络的合理设置,得到各类车型在特定网络上的流量分配、路段饱和率以及通行费用,并对此模型的应用效果进行分析,最终为区域高速公路网规划、路段交通量预测提供依据。     

Comparative analysis of household car,motorcycle and bicycle ownership between Osaka metropolitan area,Japan and Kuala Lumpur,Malaysia

The interactions among different types of vehicle ownership including car, motorcycle and bicycle are examined by developing simultaneous vehicle ownership models in this study. Large scale person trip survey data for Osaka metropolitan area, Japan and Kuala Lumpur, Malaysia are used for empirical analysis. The results suggest that population density at residential area significantly and negatively affects car ownership for both areas, and that the effects are larger for Osaka metropolitan area than for Kuala Lumpur. Also, bicycle ownership becomes higher at higher population density area for Osaka area, while higher at lower population density area for Kuala Lumpur, which represents the different usage patterns of bicycle between the two areas.

An adaptive information fusion model to predict the short-term link travel time distribution in dynamic traffic networks

As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions.     

Understanding members' carsharing (activity) persistency by using econometric model

Carsharing is an innovative travel alternative that has recently experienced considerable growth and become part of sustainable transportation initiatives. Although carsharing is becoming increasingly a popular alternative transportation mode in North America, it is still an under‐researched area. Current research is aimed at better understanding of the behavior of carsharing users. For every member, a two‐stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility‐based model. The model is estimated using empirical data from one of the largest carsharing companies in North America. The model estimates reveal that the activity persistency of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. It also shows that some attributes of the traveler (gender, age, and language spoken at home) impact his or her behaviors. Copyright © 2010 John Wiley & Sons, Ltd.     

A latent class accelerated hazard model of social activity duration

Over the past decade, activity scheduling processes have gained increasing attention in the field of transportation research. However, still little is known about the scheduling of social activities even though these activities account for a large and growing portion of trips. This paper contributes to this knowledge. We analyze how the duration of social activities is influenced by social activity characteristics and characteristics of the relationship between the respondent and the contacted person(s). To that end, a latent class accelerated hazard model is estimated, based on social interaction diary data that was collected in the Netherlands in 2008. Chi-square tests and analyses of variance are used to test for significant relations between the latent classes and personal and household characteristics. Findings suggest that the social activity characteristics and the characteristics of the relationship between the socializing persons are highly significant in explaining social activity duration. This shows that social activities should not be considered as a homogenous set of activities and it underlines the importance of including the social context in travel-behavior models. Moreover, the results indicate that there is a substantial amount of latent heterogeneity across the population. Four latent classes are identified, showing different social activity durations, and different effects for both categories of explanatory variables. Latent class membership can be explained by household composition, socio-economic status (education, income and work hours), car ownership and the number of interactions in 2 days.     

偏压连拱隧道施工方法研究

文章采川三维有限元数值模拟研究了偏压连拱隧道不同施工顺序下拱顶下沉、中墙稳定性及初期支护受力特征.研究结果表明,先开挖浅埋侧时,拱顶沉降较小,中墙在施工中的稳定安全系数较大、弯矩较小,初期支护受力较大;对于浅埋偏压连拱隧道,围岩变形及中墙在施工中的稳定性控制更为重要.所以,从有利于围岩变形、中墙稳定性控制以及中墙受力的角度出发,宜采用先开挖浅埋侧的施工方法.     

Logit模型在南广高铁线客流分担预测中的应用

对分担率进行科学的预测是交通运输规划的基础性工作,是制定运输决策的重要依据。文章经过比较选取多项Logit模型为分担率预测模型,介绍了模型建立与求解的方法,并运用该模型对南广高铁沿线客流分担率进行预测分析。     

管线敷设与风机室布置对综合管廊通风阻力影响研究

为准确估算管线敷设与风机室内气流相互作用对压降损失的影响,基于武汉市江夏区谭鑫培路地下综合管廊项目建立典型数值分析模型与分析流程。通过建立典型管线布置的GIL舱、高压舱与综合舱的计算流体动力学三维模型,分别对入口段与稳定段进行分析,并使用循环边界条件来考虑稳定段流体的充分发展,得到阻力系数随流量的变化规律;通过建立GIL舱典型排风口三维模型,分析风机室中不同风机的压降损失,并与规范估算值进行比较。研究结果表明： 管线敷设对压降损失的影响不可忽视;风机室风机相互作用显著,规范不能准确估算该相互作用导致的压降损失。