集中排烟隧道近火源顶板热参数理论预测

由于集中排烟模式能较好地控制上下游烟气的扩散范围,故被广泛应用于长大隧道设计中。文章针对小尺度火灾,建立了集中排烟隧道火源热烟羽受限发展理论模型,与已有火灾实验结果进行对比,完成了理论模型的验证,预测了顶板下方最高烟气温升、偏移距离等热参数。预测结果表明:火灾强度一定时,烟气最大温升随等效风速增加而急剧下降,且火灾强度对烟气温升的影响也较为显著;当等效风速超过1.5 m/s时,最大温升变化趋缓直至恒定;等效风速较小时,羽流未发生明显偏移,随着等效风速进一步增大,偏移距离明显增大,其变化速率随火灾强度的增大而减小。经回归整理得到了顶板下方烟气最大温升、偏移距离的无量纲准则关联式。     

车用柴油机NO_x形成及控制

相对汽油发动机污染物排放,柴油发动机CO和CH的排放较低,不到汽油机的10%,但NOX排放水平却高于汽油发动机。本文重点讨论柴油发动机排气污染物中NOx的成分及危害,分析了NO的生成机理及影响因素,提出了控制柴油机NO排放的技术和方法。     

探讨危旧桥梁加固的有关技术问题

随着国家经济建设脚步的加快,路桥的建设技术也在不断的进步,危旧桥梁的加固处理也成为桥梁建设的热点话题之一。因为公路车流量的增多,在上世纪末建设的桥梁一直都存在过载使用的问题,过多的重型车辆对危旧桥梁的使用也是一项巨大的考验。在一些使用年限比较久的桥梁中,出现了桥体老化现象。本文就危旧桥梁加固的有关技术问题进行了探讨。     

替代燃料的燃料消耗量计算方法

文章介绍了碳平衡原理的两个方面,燃烧和稀释前后的碳质量不变。介绍了完全燃烧后的CO2理论浓度和稀释倍数以及用稀释倍数校正稀释排气的方法,介绍了由碳质量分数推导替代燃料碳质量分数和当量分子式的方法,最后推导得出了可用于替代燃料的燃料消耗量计算公式。     

浅析内河航道节能现状及技术应用

内河航道在施工建设和运营管理期间会产生大量的能源消耗,抓好航道的节能减排对发展绿色交通具有重要作用。本文总结概况了目前我国内河航道节能减排现状及采用的关键技术,相关技术的推广将引导交通运输行业优化用能结构、促进产业协调发展。     

Bush-based sensitivity analysis for approximating subnetwork diversion

Subnetwork analysis is often used in traffic assignment problems to reduce the size of the network being analyzed, with a corresponding decrease in computation time. This is particularly important in network design, second-best pricing, or other bilevel problems in which many equilibrium runs must be solved as a subproblem to a master optimization program. A fixed trip table based on an equilibrium path flow solution is often used, but this ignores important attraction and diversion effects as drivers (globally) change routes in response to (local) subnetwork changes. This paper presents an approach for replacing a regional network with a smaller one, containing all of the subnetwork, and zones. Artificial arcs are created to represent “all paths” between each origin and subnetwork boundary node, under the assumption that the set of equilibrium routes does not change. The primary contribution of the paper is a procedure for estimating a cost function on these artificial arcs, using derivatives of the equilibrium travel times between the end nodes to create a Taylor series. A bush-based representation allows rapid calculation of these derivatives. Two methods for calculating these derivatives are presented, one based on network transformations and resembling techniques used in the analysis of resistive circuits, and another based on iterated solution of a nested set of linear equations. These methods are applied to two networks, one small and artificial, and the other a regional network representing the Austin, Texas metropolitan area. These demonstrations show substantial improvement in accuracy as compared to using a fixed table, and demonstrate the efficiency of the proposed approach.     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.     

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.     

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.     

Ridership drivers of bus rapid transit systems

We have collected information on 46 bus rapid transit (BRT) systems throughout the world to investigate the potential patronage drivers. From a large number of candidate explanatory variables (quantitative and qualitative), 11 sources of systematic variation are identified which have a statistically significant impact on daily passenger-trip numbers. These sources are fare, headway, the length of the BRT network, the number of corridors, average distance between stations; whether there is: an integrated network of routes and corridors, modal integration at BRT stations, pre-board fare collection and fare verification, quality control oversight from an independent agency, at-level boarding and alighting, as well as the location of BRT. The findings of this paper offer important insights into features of BRT systems that are positive contributors to growing patronage and hence should be taken into account in designing and planning BRT systems.