高速公路红砂岩路堤边坡水毁机制现场试验研究

为探究红砂岩路堤边坡在冲刷作用下的水毁机制,文章以广西南湛高速公路红砂岩路堤边坡为工程背景,设计了以冲刷量和压实度为变量的试验方案,通过现场足尺模型试验研究了红砂岩边坡在不同压实度和不同冲刷量下的边坡冲刷深度和宽度的关系,探讨了红砂岩路堤边坡的稳定性和路基水毁机理。结果表明：降雨及径流作用是影响红砂岩边坡水毁及失稳的关键因素;边坡的冲刷宽度和深度受出水流量和边坡压实度的影响;红砂岩路堤边坡水毁演绎过程具有链式特点,可分为坡面水流冲刷阶段、土体侵蚀阶段、边坡坍塌阶段、路面塌陷阶段。研究成果可为红砂岩路基边坡冲刷防治提供理论支撑。     

公路工程土质边坡稳定性影响因素分析

公路工程土质边坡稳定性问题一直是我国公路建设关注的重点。在我国进行的公路建设中,往往因为开挖路堑而形成边坡。原本处于稳定状态的自然边坡受到人为削坡卸载、爆破震动等影响,临空面又受到地表水侵蚀、地下水浸润等影响,再结合边坡自身特殊的地质条件,很可能导致边坡发生过大的变形、坡体表面出现裂缝、坡体内部逐渐形成滑裂面,进而导致边坡的稳定性不断降低。主要分析了公路工程土质边坡现状和影响其稳定性的因素,并介绍提高其稳定性的防治措施,以期为同行提供借鉴。     

湿陷性黄土地区水毁的危害及防治

以西宁机场专线为例,针对湿陷性黄土地区易出现的边坡冲沟、坡面冲刷、边坡坍塌、基底陷穴、地基湿陷等水毁病害进行了成因分析,并在此基础上,从边坡防护与加固、排水系统完善、加强路政管理等方面提出了六项防治措施。     

基于强度折减法的多级边坡稳定性分析

对于高边坡,因主观原因准许不能准确地把握滑动面及坡体的实际变形状态,不利于边坡稳定性设计。本文大型通用有限元分析软件ABAQUS作为分析平台,采用强度折减法,建立坡体安全系数与失稳机理的边坡稳定性有限元模型。该模以迭代计算不收敛作为边坡失稳判断依据,分析坡体初始设计的稳定性。通过改变坡体设计方案,来提高坡体整体的安全系数。结果表明:通过分层降低设计坡比,可实现提高坡体的安全系数,但是提高效果有限;基于强度折减法的有限元数值迭代不收敛判决有助于坡体稳定性初步设计。     

路基边坡坡面冲刷机理与加固材料研究

为了提高公路路基建设水平,文章从干土溅散、泥浆溅散、层状侵蚀等方面分析了路基边坡冲刷机理,提出一种新型纤维加筋土固坡技术.以抗剪强度和渗透系数为评价指标,开展室内剪切试验、变水头试验、电镜扫描试验,研究了加固土抗冲刷性能,并依托某公路路基边坡,探讨了降雨对加固土径流强度和产沙量的影响规律及加固土对边坡整体稳定性的提升效...     

基于边坡平台宽度对边坡稳定性影响的分析

计算黄土高边坡稳定性时,常采用圆弧法来计算边坡的稳定性。传统的圆弧法计算边坡稳定性时并没有考虑到边坡平台宽度对边坡稳定性的影响。从而计算得出的安全系数与实际情况会有一定的误差,因此,本文建立黄土边坡破坏模型,研究得出了坡顶面坡率及层状黄土的台阶宽度对边坡稳定性的影响规律,对公路边坡建设具有十分重要的指导意义。     

白龙核电站厂区道路2~#边坡稳定性综合评价

文章根据白龙核电站厂区道路2#边坡的工程实际情况、坡体结构和岩体结构,采用工程地质类比法、赤平投影图解分析法、强度折减法及极限平衡法对边坡稳定性进行了定性与定量分析,揭示了边坡合理的综合开挖坡角,并提出了相应的边坡排水和防护措施。     

基于有限元强度折减理论的某路堑边坡加固设计

针对不稳定路堑边坡影响道路安全问题,根据规范要求应采取有效的边坡支护方法保证边坡及环境安全。文章结合具体路堑边坡工程实例,按照工程建设要求以及地质条件,将该路堑边坡分为8阶,采取弱层削除、坡面喷浆以及锚杆支护的加固方式提高边坡稳定性。基于强度折减原理和有限元法分析理论,以数值模拟结果证明该加固方法有效提升路堑边坡稳定性及其使用年限。     

降雨强度、降雨历时对高速公路边坡稳定性的影响

为探究不同强度降雨在不同降雨历时下对边坡稳定性的影响,采用数值模拟软件Geo-studio的Seep/W和Slope/W模块,进行了边坡在四种不同降雨强度下的二维渗流与稳定性分析。将Seep/W计算所得孔隙水压力与体积含水率分布导入Slope/W,从而计算出边坡的稳定安全系数。数值计算结果显示:降雨历时、降雨强度对坡体稳定性均有不同程度的影响,在此基础上有针对性地提出了增设平台排水沟、植草灌等防排水及防冲刷措施。     

郑石高速公路黄庄边坡稳定性分析

文章根据郑石高速公路黄庄边坡的岩体结构、坡体结构和工程实际情况,采用极限平衡理论和模糊数学方法对右侧边坡进行赤平极射投影分析和模糊综合评判,综合分析该边坡的稳定性,并采用有限单元法对路堑开挖全过程进行模拟,揭示边坡变形破坏机理,为边坡处治提供依据。     

The effects of on‐street parking on the service rate of nearby intersections

An on‐street parking maneuver can often start a temporary bottleneck, leading to additional delay endured by the following vehicles. If the maneuver occurs near a signalized intersection, the service rate of the intersection might be reduced. In this paper, a model is built to analyze the effects of parking maneuvers on the intersection service rate. Based on the hydrodynamic theory of traffic flow, the perturbation caused by the parking maneuver is analyzed. Using dimensional analysis, we illustrate the relation between the background conditions, the distance from the parking area to the intersection, and the intersection service rate. Based on this relation, one can compute the service rate reduction caused by existing on‐street parking areas. A minimum distance between the parking area and the intersection to avoid such reduction can be accordingly found. Numerical examples based on empirical data from the city of Zurich, Switzerland, are provided to illustrate the practical applications. Although the analysis is based on streets with a single lane per direction, the findings can provide some insights regarding different situations. We hope such findings can be used as a basis for developing on‐street parking design guidelines. Copyright © 2015 John Wiley & Sons, Ltd.     

Passenger conveyor economics

Operating and capital costs for a high speed conveyor are estimated from cost data for low speed conveyors and from estimates for high speed designs. Unit costs are developed with reference to theoretical and practical conveyor capacities, and to the effect of traffic peaking on average utilization. User benefits are modelled as the change in consumers surplus arising from the introduction of a conveyor on a linear street as an alternative to walking. Cost and benefits vary widely depending on system design and location and on characteristics of travellers. Benefit measurements should reflect the effects on travel demand of a proposed installation, changes in value of time with changes in mode, and the effects of benefit “dilution” associated with limitations on access to the conveyor.     

广佛线盾构隧道管片处理中冻结法封水的监测分析

珠江三角洲城际快速轨道交通广州至佛山段普君北路站—朝安站区间在管片处理冻结封水工程施工中,对冻结盐水温度、冻土温度、冻胀压力等方面进行了跟踪监测。通过对监测结果进行分析研究,获得了冻结盐水温度、冻土温度、冻胀压力的变化规律,在此基础上对冻结施工过程提出了建议。     

Identification of vehicle sensor locations for link-based network traffic applications

Information on link flows in a vehicular traffic network is critical for developing long-term planning and/or short-term operational management strategies. In the literature, most studies to develop such strategies typically assume the availability of measured link traffic information on all network links, either through manual survey or advanced traffic sensor technologies. In practical applications, the assumption of installed sensors on all links is generally unrealistic due to budgetary constraints. It motivates the need to estimate flows on all links of a traffic network based on the measurement of link flows on a subset of links with suitably equipped sensors. This study, addressed from a budgetary planning perspective, seeks to identify the smallest subset of links in a network on which to locate sensors that enables the accurate estimation of traffic flows on all links of the network under steady-state conditions. Here, steady-state implies that the path flows are static. A “basis link” method is proposed to determine the locations of vehicle sensors, by using the link-path incidence matrix to express the network structure and then identifying its “basis” in a matrix algebra context. The theoretical background and mathematical properties of the proposed method are elaborated. The approach is useful for deploying long-term planning and link-based applications in traffic networks.     

呼包鄂地区农村道路国防功能探讨

文章根据呼包鄂三地区的地域特征和经济地位,结合目前农村道路国防功能建设要求,提出当前修建农村道路时增强其国防功能的几点建议,以期对内蒙古乃至全国农村道路的建设和国防交通事业有所帮助。     

高低塔斜拉桥主塔承台优化及其结构计算分析

文章在对拟建南宁外环公路大冲邕江特大桥的自然条件、水文、地质、航道等因素进行分析研究的基础上,对原方案大桥主塔承台进行优化设计,并采用有限元软件建立全桥和局部有限元模型进行结构计算分析及验算,确定优化方案的合理性及可行性,为类似工程设计提供参考。     

Learning aircraft operational factors to improve aircraft climb prediction: A large scale multi-airport study

Ground-based aircraft trajectory prediction is a major concern in air traffic control and management. A safe and efficient prediction is a prerequisite to the implementation of new automated tools.In current operations, trajectory prediction is computed using a physical model. It models the forces acting on the aircraft to predict the successive points of the future trajectory. Using such a model requires knowledge of the aircraft state (mass) and aircraft intent (thrust law, speed intent). Most of this information is not available to ground-based systems.This paper focuses on the climb phase. We improve the trajectory prediction accuracy by predicting some of the unknown point-mass model parameters. These unknown parameters are the mass and the speed intent. This study relies on ADS-B data coming from The OpenSky Network. It contains the climbing segments of the year 2017 detected by this sensor network. The 11 most frequent aircraft types are studied. The obtained data set contains millions of climbing segments from all over the world. The climbing segments are not filtered according to their altitude. Predictive models returning the missing parameters are learned from this data set, using a Machine Learning method. The trained models are tested on the two last months of the year and compared with a baseline method (BADA used with the mean parameters computed on the first ten months). Compared with this baseline, the Machine Learning approach reduce the RMSE on the altitude by 48% on average on a 10 min horizon prediction. The RMSE on the speed is reduced by 25% on average. The trajectory prediction is also improved for small climbing segments. Using only information available before the considered aircraft take-off, the Machine Learning method can predict the unknown parameters, reducing the RMSE on the altitude by 25% on average.The data set and the Machine Learning code are publicly available.     

Stability of transportation networks under adaptive routing policies

Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic Equilibria” (MTE), in which users update their route choice at each intersection of the road network based on traffic conditions, to the case of non-equilibrium conditions, while preserving consistency with known existence and uniqueness results on MTE. We then exhibit sufficient conditions on the network topology and the latency functions for those MTEs to be stable in the sense of Lyapunov for a single destination problem. For various more restricted classes of network topologies motivated by the observed properties of travel patterns in the Singapore network, under certain assumptions we prove local exponential stability of the MTE, and derive analytical results on the sensitivity of the characteristic time of convergence to network and traffic parameters. The results proposed in this work are illustrated and validated on synthetic toy problems as well as on the Singapore road network with real demand and traffic data.     

Impact of weather on urban transit ridership

Utilizing daily ridership data, literature has shown that adverse weather conditions have a negative impact on transit ridership and in turn, result in revenue loss for the transit agencies. This paper extends this discussion by using more detailed hourly ridership data to model the weather effects. For this purpose, the daily and hourly subway ridership from New York City Transit for the years 2010–2011 is utilized. The paper compares the weather impacts on ridership based on day of week and time of day combinations and further demonstrates that the weather’s impact on transit ridership varies based on the time period and location. The separation of ridership models based on time of day provides a deeper understanding of the relationship between trip purpose and weather for transit riders. The paper investigates the role of station characteristics such as weather protection, accessibility, proximity and the connecting bus services by developing models based on station types. The findings indicate substantial differences in the extent to which the daily and hourly models and the individual weather elements are able to explain the ridership variability and travel behavior of transit riders. By utilizing the time of day and station based models, the paper demonstrates the potential sources of weather impact on transit infrastructure, transit service and trip characteristics. The results suggest the development of specific policy measures which can help the transit agencies to mitigate the ridership differences due to adverse weather conditions.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.