A mesoscopic integrated urban traffic flow-emission model

Due to the noticeable environmental and economical problems caused by traffic congestion and by the emissions produced by traffic, analysis and control of traffic is essential. One of the various traffic analysis approaches is the model-based approach, where a mathematical model of the traffic system is developed/used based on the governing physical rules of the system. In this paper, we propose a framework to interface and integrate macroscopic flow models and microscopic emission models. As a result, a new mesoscopic integrated flow-emission model is obtained that provides a balanced trade-off between high accuracy and low computation time. The proposed approach considers an aggregated behavior for different groups of vehicles (mesoscopic) instead of considering the behavior of individual vehicles (microscopic) or the entire group of vehicles (macroscopic). A case study is done to evaluate the proposed framework, considering the performance of the resulting mesoscopic integrated flow-emission model. The traffic simulation software SUMO combined with the microscopic emission model VT-micro is used as the comparison platform. The results of the case study prove that the proposed approach provides excellent results with high accuracy levels. In addition, the mesoscopic nature of the integrated flow-emission model guarantees a low CPU time, which makes the proposed framework suitable for real-time model-based applications.     

Using a stages of change approach to explore opportunities for increasing bicycle commuting

Given the potential benefits of bicycling to the environment, the economy, and public health, many U.S. cities have set ambitious goals for increasing the bicycle share of commute trips. The Transtheoretical Model of Behavior Change, which seeks to describe how positive and permanent change can be fostered in individuals, may shed light on how cities can most effectively increase bicycle commuting. We use the model’s “stages of change” framework to explore the potential for increased bicycle commuting to the UC Davis campus in Davis, California. Our analysis uses data from the 2012 to 2013 UC Davis Campus Travel Survey, an annual online survey that is randomly administered to students and employees at UC Davis. Based on their responses to questions about current commute mode and contemplation of bicycle commuting, respondents are divided into five stages of change: Pre-contemplation, Contemplation, Preparation, Action, and Maintenance. We construct a Bayesian multilevel ordinal logistic regression model to understand how differences in socio-demographic characteristics, travel attributes, and travel attitudes between individuals explain their membership in different stages of change. In addition, we use this model to explore the potential of various intervention strategies to move individuals through the stages of change toward becoming regular bicycle commuters. Our results indicate that travel attitudes matter more to progression toward regular commute bicycling than travel attributes, tentatively supporting the efficacy of “soft” policies focused on changing travel attitudes.     

大秦铁路煤炭运输需求分析与预测

随着国家优化存量资源配置、能源结构调整、"公转铁"等政策的相继出台,以及浩吉铁路开通、唐呼铁路能力逐步释放,重载铁路运输需求分布发生变化,大秦铁路作为"西煤东运"的主要重载铁路运输通道,其需求情况也随之发生变化。在阐述大秦铁路上、下游行业发展和运输需求现状的基础上,从宏观经济、市场供需、竞争环境及铁路内部等方面分析影响大秦铁路煤炭运输需求的关键因素,结合大秦铁路煤炭运输需求关键影响因素,构建人工神经网络模型,预测大秦铁路煤炭运输需求。研究大秦铁路煤炭运输需求变化,对决策项目投入、保障货运增量具有重要意义。     

最优组合预测方法在内河港口吞吐量预测中的应用

港口吞吐量的预测是港口规划过程中最为基础也最为关键的一步,只有对港口吞吐量做出准确、稳定的预测,才能做出科学合理的港口发展规划。由于内河港吞吐量历史数据有限,文中采用GM(1,1)和Verhulst模型的最优组合模型对港口吞吐量进行预测。该组合模型充分利用GM(1,1)模型“少数据,短期预测准确”的优点,又针对GM(1,1)预测量的无限增大趋势,引入了Verhulst模型进行组合修正,进而提高预测值的准确、稳健性。     

Online distributed cooperative model predictive control of energy-saving trajectory planning for multiple high-speed train movements

The cooperative energy-efficient trajectory planning for multiple high-speed train movements is considered in this paper. We model all the high-speed trains as the agents that can communicate with others and propose a local trajectory planning control model using the Model Predictive Control (MPC) theory. After that we design an online distributed cooperative optimization algorithm for multiple train trajectories planning, under which each train agent can regulate the trajectory planning procedure to save energy using redundancy trip time through tuning ACO’s heuristic information parameter. Compared to the existing literature, the vital distinctions of our work lies not only on the online cooperative trajectory planning but also on the distributed mechanism for multiple high-speed trains. Experimental studies are given to illustrate the effectiveness of the proposed methods with the practical operational data of Wuhan-Guangzhou High-speed Railway in China.     

深厚砂卵石地层超深竖井施工降水模型试验研究北大核心CSCD

富水砂卵石地层中基坑降水始终是工程界较大的难题,文章针对兰州强透水深厚砂卵石地层超深竖井降水进行了理论计算和模型试验研究,研制了一套有效的模型试验系统,配置了砂卵石土体相似材料,并重点研究了基底注浆加固对基坑降水的影响。研究结果表明:(1)黄河对基坑降水有重要的影响,靠近黄河一侧降水漏斗曲线陡直,远离黄河一侧降水漏斗曲线平缓;(2)基底注浆降低了水力梯度,提高基坑施工安全性,可有效减少基坑内抽水量,但对于坑外抽水量作用不大;(3)基底加固区渗透系数存在最优值,对于该工程,建议取1×10^(-6)m/s为加固区目标渗透系数。     

黄土地区地铁隧道不同湿陷变形方式模型试验系统的研制及应用研究

为研究不同湿陷变形方式下黄土地区地铁隧道周围土体的沉降量变化规律,研制出一种测量黄土在均匀湿陷、不均匀湿陷时沉降量的模型试验装置。该装置由模型箱、流速控制系统和沉降量测量系统组成。通过室内模型试验对黄土在遇水后的湿陷变形规律进行总结,并对黄土地层在两种不同浸水方式下隧道围岩土体的变形规律进行分析。试验结果表明:不均匀湿陷最终累计沉降量大于均匀湿陷最终累计沉降量,说明不均匀湿陷对地铁结构物的危害更大;两种湿陷变形方式均为隧道中线附近沉降最大,因此,施工时应该重点加强隧道中线的位移监测。通过室内模型试验,分析了均匀与不均匀湿陷对黄土地铁隧道变形影响,研究结果对湿陷性黄土地区地铁隧道建设中施工把控及灾害规避具有重要意义。     

Modeling and analysis of thin-walled Al/steel explosion welded transition joints for shipbuilding applications

The study presents an analysis of S355J2+N steel and AA5083 aluminum alloy welded structural joints using explosion welded transition joints of reduced thickness. The transition joint thickness reduction significantly hinders the welding of the joints due to the risk of damage to the Al/steel interface as a result of the high temperatures during welding. Numerical modeling of the welding process is performed to determine safe welding parameters for the transition joint. The numerical analysis is supported by measurements of the temperature areas by a thermographic method. Welded structural joints are analyzed to determine the welding influence on the mechanical properties and microstructure of the transition joints. On this basis, a number of tests are carried out, including microhardness distribution measurements, strength tests of joints in two welding configurations and strength tests of the microspecimens of transition joints. Moreover, an experimental and numerical analysis of strain and stress distributions is carried out in combination with the use of the finite element method and digital image correlation, which allow us to identify the critical areas of the joints with regards to their strength. The results of the microstructural and strength tests carried out using macro- and microspecimens show softening of the aluminum alloy layers. However, the AA5083 and AA1050 layer softening as a result of welding did not reduce the load capacity of the transition joints, which could determine the strength of the dissimilar Al/steel welded structural joints.     

基于实测应力的动车组制动盘盘毂服役特性

针对仿真或仅考虑紧急制动状态下动车组制动盘盘毂安全性分析中存在的不足,基于盘毂应力在线测试,分析动车组高速运行和不同制动方式下盘毂的频谱特性和成分特性;考虑应力集中,根据静力等效原则进行毂齿根部的应力线性化,分析不同制动方式对盘毂疲劳损伤的影响;采用指数模型拟合和核密度估计相结合的方法,推理97.5%置信度下的盘毂实测应力谱,并考虑车轮镟修前后盘毂损伤演化和材料强度退化,评估盘毂服役安全性。结果表明:盘毂载荷振动频率主要分布在0~71 Hz和341~680 Hz频带,车轮镟修可有效降低341~518 Hz频带内的载荷振动、消除518~680 Hz频带内的载荷振动;动车组高速运行和车轮状态不良是造成盘毂损伤的主要原因;若按盘毂服役寿命为1500万km计算,盘毂疲劳薄弱区的等效应力为37.4 MPa,累积损伤为0.61,该结果可为盘毂的结构设计和检修维护策略制定提供依据。