Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

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.     

On the income elasticity of the value of travel time

Transport infrastructure is long-term and in appraisal it is necessary to value travel time savings for future years. This requires knowing how the value of time (VTT) will develop over time as incomes grow. This paper investigates if the cross-sectional income elasticity of the VTT is equal to inter-temporal income elasticity. The study is based on two identical stated choice experiments conducted with a 13 year interval. Results indicate that the relationship between income and the VTT in the cross-section has remained unchanged over time. As a consequence, the inter-temporal income elasticity of the VTT can be predicted based on cross-sectional income elasticity. However, the income elasticity of the VTT is not a constant but increases with income. For this reason, the average income elasticity of the VTT in the cross-sections has increased between the two survey years and can be expected to increase further over time.     

输气管道置换优化研究

置换是输气管道投产试运过程中的重要工艺环节,是复杂的扩散、对流过程。文中介绍了输气管道投产前用氮气置换空气的几种方法,阐述了它们的工作原理与实施步骤,对比分析了它们的优缺点,优选了置换方式,并采用Fluent流体模拟软件建立了输气管道氮气置换数学模型,进行了三维稳态和非稳态数值计算,研究了置换过程中混气段长度随管径、管长、流速变化规律,将理论推导、数值计算和现场数据进行了对比,验证了理论结果的正确性,为现场施工提供了科学依据。     

U型管式换热器的质量控制

U型管式换热器属于列管换热器的一种,被广泛应用在循环水冷却高温气体装置中。根据U型管式换热器的结构特点和技术原理,针对设备在使用过程中可能出现的问题,在整个材料采购和制造过程中,对换热器中管板制造加工、U型管成形及换热管与管板的焊接等制造的关键和难点予以质量控制,保证产品质量,使设备按设计要求制造完毕后安全有效地运行。     

穿越古滑坡川主寺隧道围岩破坏特征及稳定性研究

文章以川主寺隧道所处的工程地质条件为基础,通过现场调研分析了隧道围岩变形破坏形式主要为坍塌、掉块以及剥落.围岩稳定性三维有限元数值模拟结果显示,碎裂围岩自稳能力差,围岩变形以弹塑性变形、松弛变形为主;H型钢拱架支护结构对碎裂围岩稳定性起到积极的作用,并通过典型洞段现场位移监测数据分析结果得以证实.     

轴对称解对隧道衬砌水压力计算的适用性研究

文章根据渗流理论推导了隧道衬砌水压力的轴对称解,并利用数值分析方法研究了轴对称解对不同形状隧道断面与浅埋隧道的适用性.研究结果表明:轴对称解适用于非圆形隧道断面衬砌水压力的估算;隧道断面形状对衬砌水压力折减系数的影响较小,可以忽略不计,其影响大小主要由衬砌与围岩的渗透系数比值决定.对于浅埋低水头隧道,用轴对称解计算的毛洞流量Qm与数值解比较,其误差较大,最大误差为36.5％;但用来计算衬砌水压力p1以及衬砌后水流量Q1时,误差相对较小,最大误差为6.3％,特别是利用轴对称解得出的衬砌水压力值与利用数值解得出的衬砌水压力特征值最大误差仅为3.4％.     

基于Bayes判别分析方法的叙岭关隧道溶洞水源识别

基于Bayes判别方法,选取水化学常量组分作为判别指标,利用叙岭关隧道地区9个动态监测点的53个水样样本建立了该地区的水源判别模型.模型检验结果表明,其回判准确率为96.23％,具有较高的识别精度和工程推广能力.利用建立的判别模型,对叙岭关隧道1号溶洞内两个出水点RQ1和RQ2的水源进行了识别,并结合其流量动态变化特征、同位素分析结果,以及1号溶洞发育位置,推断1号溶洞内两个出水点的水源为P1m+q含水层中的岩溶地下水.根据判别结果,建议1号溶洞采取“以排为主”的原则加以处治,并尽量保留溶洞水的过水通道.     

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.     

Modelling the impact of weather conditions on active transportation travel behaviour

Three weather sensitive models are used to explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data are restricted to non-captive commuters who have the option of selecting among five basic modes of auto driver, auto passenger, transit, bike and walk. Daily trip rates in various weather conditions are assessed. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.