青藏铁路大风天气运输组织方法

青藏高原大风天气多,空气密度小,大风对铁路运输安全的影响与低海拔地区差异较大。利用车辆动力学原理建立列车临界翻车风速模型,分别计算青藏铁路海拔3 000 m和4 000 m冻土和非冻土地区的临界翻车风速和危险翻车风速,以及给定风速条件下车辆限制速度。计算结果表明,青藏铁路临界翻车风速随海拔升高而增大,随冻土路基病害出现而降低。参考英、日等国大风标准,结合青藏铁路的特点,根据危险翻车风速和临界翻车风速,初步提出青藏铁路海拔4 000 m地区安全行车标准及特定运行条件、冻土地区线路出现病害情况下的安全行车标准及特定运行条件。提出列车限速运行、增加车辆载重、提高列车编组水平、提高司机操作水平、改善棚车顶部外形、加强货运检查、注意车辆防溜和风沙地区线路检查等大风天气运输组织措施。     

Q355GNHD高耐候钢在动车组中的焊接运用

详细介绍了出口突尼斯动车组车体钢结构的特点,通过各部位焊接工艺试验,结合车体钢结构组装焊接工艺,选取了与之匹配的焊接材料Q355GNHD高耐候钢,确定了合适的焊接工艺参数,并制定出该车的生产工艺方案,满足了产品设计的制造需要。     

Comparing different contour methods with response-based methods for extreme ship response analysis

Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. They facilitate approximate long term analysis of critical structural responses in situations where computationally heavy and time-consuming response calculations makes full long-term analysis infeasible. The environmental contour method identifies extreme environmental conditions that are expected to give rise to extreme structural response of marine structures. The extreme responses can then be estimated by performing response calculations for environmental conditions along the contours.Response-based analysis is an alternative, where extreme value analysis is performed on the actual response rather than on the environmental conditions. For complex structures, this is often not practical due to computationally heavy response calculations. However, by establishing statistical emulators of the response, using machine learning techniques, one may obtain long time-series of the structural response and use this to estimate extreme responses.In this paper, various contour methods will be compared to response-based estimation of extreme vertical bending moment for a tanker. A response emulator based on Gaussian processes regression with adaptive sampling has been established based on response calculations from a hydrodynamic model. Long time-series of sea-state parameters such as significant wave height and wave period are used to construct N-year environmental contours and the extreme N-year response is estimated from numerical calculations for identified sea states. At the same time, the response emulator is applied on the time series to provide long time-series of structural response, in this case vertical bending moment of a tanker. Extreme value analysis is then performed directly on the responses to estimate the N-year extreme response. The results from either method will then be compared, and it is possible to evaluate the accuracy of the environmental contour method in estimating the response. Moreover, different contour methods will be compared.     

Through the storm: Transit agency management in response to climate change

The increase in extreme weather events due to climate change poses serious challenges to public transit systems. These events disrupt transit operations, impair service quality, increase threats to public safety, and damage infrastructure. Despite the growing risk of extreme weather and climate change, little is known about how public managers recognize, experience and address these risks. Using data from a national study of public transit agencies we investigate the types of extreme weather events transit agencies are experiencing, the associated risks, and how agencies are preparing for them. We find that while extreme events are commonly experienced by transit agencies across states and transit managers perceive increased risks from these events, most agencies rely on the traditional emergency management approach to address extreme weather ex post rather than taking a proactive approach to mitigating the adverse weather impact on transit assets and infrastructure ex ante. Managers report that a lack of access to financial resources is the greatest challenge for undertaking adaptation and preparation. We conclude with a discussion of what these findings mean for understanding organizational adaptation behavior as well as climate adaptation policy making.     

Delivering improved alerts,warnings, and control assistance using basic safety messages transmitted between connected vehicles

When vehicles share their status information with other vehicles or the infrastructure, driving actions can be planned better, hazards can be identified sooner, and safer responses to hazards are possible. The Safety Pilot Model Deployment (SPMD) is underway in Ann Arbor, Michigan; the purpose is to demonstrate connected technologies in a real-world environment. The core data transmitted through Vehicle-to-Vehicle and Vehicle-to-Infrastructure (or V2V and V2I) applications are called Basic Safety Messages (BSMs), which are transmitted typically at a frequency of 10 Hz. BSMs describe a vehicle’s position (latitude, longitude, and elevation) and motion (heading, speed, and acceleration). This study proposes a data analytic methodology to extract critical information from raw BSM data available from SPMD. A total of 968,522 records of basic safety messages, gathered from 155 trips made by 49 vehicles, was analyzed. The information extracted from BSM data captured extreme driving events such as hard accelerations and braking. This information can be provided to drivers, giving them instantaneous feedback about dangers in surrounding roadway environments; it can also provide control assistance. While extracting critical information from BSMs, this study offers a fundamental understanding of instantaneous driving decisions. Longitudinal and lateral accelerations included in BSMs were specifically investigated. Varying distributions of instantaneous longitudinal and lateral accelerations are quantified. Based on the distributions, the study created a framework for generating alerts/warnings, and control assistance from extreme events, transmittable through V2V and V2I applications. Models were estimated to untangle the correlates of extreme events. The implications of the findings and applications to connected vehicles are discussed in this paper.     

Impact assessment of extreme weather events on transport networks: A data-driven approach

The present paper presents a data-driven method for assessing the resilience of the European passenger transport network during extreme weather events. The method aims to fill in the gap of current research efforts regarding the quantification of impacts attributed to climate change and the identification of substitutability opportunities between transport modes in case of extreme weather events (EWE). The proposed method consists of three steps concerning the probability estimation of an EWE occurring within a transportation network, the assessment of its impacts and the passengers’ flow shift between various transport modes. A mathematical formulation for the proposed data-driven method is provided and applied in an indicative European small-scale network, in order to assess the impacts of EWE on modal choice. Results are expressed in passenger differentiated flows and the paper concludes with future research steps and directions.     

Estimation of extreme significant wave heights and the associated uncertainties: A case study using NORA10 hindcast data for the Barents Sea

The reliability of an offshore structure is dependent on its response to the extreme wave climate; therefore, an adequate knowledge of the wave climate at a location is a prerequisite during design as well as in marine operations. This study aims to contribute to the knowledge of the extreme wave climate in the Norwegian Sector of the Barents Sea, using wave hindcast datasets from the Norwegian Reanalysis 10 km (NORA10) database for four locations.We have considered three commonly used methods for the estimation of extreme wave heights, that is, the initial distribution method, the peak over threshold method, and the annual maxima method. The parametric bootstrap concept is considered in the estimation of the epistemic uncertainty related to sample size. The estimated 100-year significant wave heights obtained from the three methods differ, and the degree of variability in the estimates varies, depending on the dataset. The epistemic uncertainty due to sample size is wider when considering the annual maxima method.The estimates obtained from the three methods show the importance of considering different methods and their associated uncertainties when estimating extreme wave values for design. While it is difficult to single out the best method among the three, the estimated values give knowledge of the possible range of the extreme significant wave heights at the locations. Generally, the datasets considered in this study suggest that the wave climate is less harsh further north compared to the southern region of the Barents Sea. The datasets do not suggest any temporal trends in the historical significant wave heights at any of the locations.     

污水管网系统节点流量模拟计算

污水管网系统节点流量模拟计算是城市污水管网系统规划设计和运行管理的基础性工作。该文从污水管网系统规划设计和运行管理两个方面阐述了污水管网系统节点流量模拟计算的内涵,并对该领域的未来发展作了展望。     

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.