兰渝铁路胡麻岭隧道第三系弱成砂岩蠕变特性试验研究

为掌握砂岩地层蠕变特性,保证施工和运营期间的结构安全,以兰渝铁路胡麻岭隧道第三系富水弱成段施工为依托,从采用改制的流变仪进行蠕变特性试验,得出了蠕变方程描述弱成砂岩蠕变特性随含水量的变化情况,分析了各种含水量状态下的蠕变特性,讨论了不同含水量情况下变形与持续时间的影响关系,并以试验数据为基础提出了相配套的设计原则和施工方法。     

Perspectives of English Language News

English isused more than any other languages, so all of usshould get a good command of it in order to be more competitive in thissociety. There're many waysto master this language, but through reading English language newspaper, with which we have so much contact everyday, is obviously more convenient and interesting. English language newspaper contain several parts, the features of each of them will be analyzed in this thesis together with a specific piece of news. Furthermore, some effective methods of reading and understanding English lan-guage newswill be proposed.     

非对称小净距隧道施工力学特性研究及方案优化

非对称小净距隧道合理的开挖顺序对隧道围岩稳定和支护措施优化有很大的影响。文章结合净距2.0 m非对称公路隧道工程实践,通过二维弹塑性有限元数值仿真模拟,研究分析了隧道开挖顺序对支护力学行为特性及围岩稳定性的影响,得出了先开挖较小断面隧道优于先开挖较大断面隧道的结论,为非对称小净距隧道优化设计和施工提供了科学依据。     

工程造价的动态管理

对工程造价的动态管理进行了阐述.     

基于组合深度学习的快速路车道级速度预测研究

随着物联网、云计算和大数据在智能交通领域的普及应用,传统的以道路断面为研究对象的预测方法已经无法满足智能网联技术发展的需求.本文以车道断面为研究对象,提出一种基于组合深度学习(Combined Deep Learning,CDL)的城市快速路车道级速度预测模型.该模型利用基于信息熵的灰色关联分析提取空间特征变量,采用长短期记忆神经网络提取空间特征变量的时间特征,并利用门限递归单元神经网络得到预测结果.通过北京市东二环路车道断面实测微波数据验证发现,提取车道交通流的时空特征,CDL模型能够很好地拟合不同车道不同时段的速度变化趋势,可有效地实现车道速度的单步及多步预测,且该模型的预测精度和稳定性均优于传统预测模型.     

某保护装置工作特性分析与国产化替代设计

通过对某自导系统保护装置中非周期性放大器、双带通滤波放大器、调制放大器以及带通滤波器等组成电路进行分析,获得保护装置选频放大等工作特性,并进行国产化替代设计,所得结论有利于全面解析该自导系统设计机理,同时可为该系统故障诊断及替代化研究奠定基础。     

Y型过滤器流动与阻力特性数值模拟分析

文中利用CFD软件,结合多孔介质模型对Y型过滤器进行了数值模拟研究,并与实验结果做了对比分析。得到了过滤器流动特性及不同部位压降情况,分析了滤网堵塞率对压降的影响规律,并提出了减小过滤器压力损失的建议方法。研究表明,Y型过滤器压降主要发生在入口滤座区、滤网区和滤芯环形间隙区,其中滤网区压降最大。滤网堵塞程度对压降影响很大,超过50%时压降快速增大。     

压差调节器静态特性试验研究

通过试验对压差调节器进行了整定,获得了它的静态特性曲线,结果表明压差调节器的性能可以满足要求.     

A discounted recursive logit model for dynamic gridlock network analysis

Emerging sensing technologies such as probe vehicles equipped with Global Positioning System (GPS) devices on board provide us real-time vehicle trajectories. They are helpful for the understanding of the cases that are significant but difficult to observe because of the infrequency, such as gridlock networks. On the premise of this type of emerging technology, this paper propose a sequential route choice model that describes route choice behavior, both in ordinary networks, where drivers acquire spatial knowledge of networks through their experiences, and in extraordinary networks, which are situations that drivers rarely experience, and applicable to real-time traffic simulations. In extraordinary networks, drivers do not have any experience or appropriate information. In such a context, drivers have little spatial knowledge of networks and choose routes based on dynamic decision making, which is sequential and somewhat forward-looking. In order to model these decision-making dynamics, we propose a discounted recursive logit model, which is a sequential route choice model with the discount factor of expected future utility. Through illustrative examples, we show that the discount factor reflects drivers’ decision-making dynamics, and myopic decisions can confound the network congestion level. We also estimate the parameters of the proposed model using a probe taxis’ trajectory data collected on March 4, 2011 and on March 11, 2011, when the Great East Japan Earthquake occurred in the Tokyo Metropolitan area. The results show that the discount factor has a lower value in gridlock networks than in ordinary networks.     

Parking space management via dynamic performance-based pricing

In congested urban areas, it remains a pressing challenge to reduce unnecessary vehicle circling for parking while at the same time maximize parking space utilization. In observance of new information technologies that have become readily accessible to drivers and parking agencies, we develop a dynamic non-cooperative bi-level model (i.e. Stackelberg leader–follower game) to set parking prices in real-time for effective parking access and space utilization. The model is expected to fit into an integrated parking pricing and management system, where parking reservations and transactions are facilitated by sensing and informatics infrastructures, that ensures the availability of convenient spaces at equilibrium market prices. It is shown with numerical examples that the proposed dynamic parking pricing model has the potential to virtually eliminate vehicle circling for parking, which results in significant reduction in adverse socioeconomic externalities such as traffic congestion and emissions.