装配式码头灌浆连接节点压弯性能试验研究

对3组装配式码头灌浆连接节点试件进行压弯试验,研究不同灌浆长度和灌浆厚度下灌浆节点的压弯承载力、延性和破坏模式。结果表明,灌浆节点试件具有较好的延性和较高的承载力,灌浆节点受压弯荷载的破坏模式为钢管的压屈破坏;压弯构件的极限承载力随着灌浆长度的增大而增大;灌浆厚度的变化对构件的承载力影响不大,但灌浆厚度增大可以提高灌浆体底部的抗裂能力,建议实际应用时适当增大灌浆厚度。     

京杭运河穿黄及黄河北航道走向探析

近年来,京杭运河黄河以北段复航呼声越来越高,京杭运河穿黄及黄河北山东段走向成为目前需要迫切解决的问题。本文通过对东平湖周边防洪工程现状分析,提出了穿黄位置、穿黄方案及穿黄线路走向;根据黄河北河系水网布置,提出了京杭运河黄河北山东段航道初步走向,为京杭运河黄河以北段复航工程提供技术参考。     

油库工业控制系统信息安全防护措施简析

本文结合某港油库的工业控制系统信息安全升级项目,介绍了该港根据《工业控制系统信息安全防护指南》、《工业控制系统信息安全行动计划(2018-2020)》以及国内外相关标准规范的要求,通过多角度评估,建立健全油库工业控制系统的安全保障体系,实现对其全方位的防护。     

张紧器的结构参数对顶张式立管动力响应的影响研究

本文针对带液压气动式张紧器的顶张式立管,综合考虑浮式平台-张紧器-立管之间的运动关系、液压气柱的张力-冲程非线性关系、立管的真实截面布置以及采油树的作用,建立更加符合工程实际的三维有限元分析模型,并通过与实验结果对比验证了该模型的正确性。基于该有限元模型,研究了张紧器的结构参数对顶张式立管动力响应的影响。结果表明:活塞和活塞杆的直径以及高压气体的初始压强对立管的动力响应影响最大;低压气体的初始压强以及液压气柱和立管之间的夹角对立管的动力响应也有重要影响;在相同的环境条件下,高压气体和低压气体的初始体积对立管的动力响应的影响较小。     

大型地下空间的结构分割转换工法研究

为解决当下地下空间开发难题,依托中铁工程装备集团地下停车场项目,提出建造大型地下空间的结构分割转换工法（CC工法）,并成功应用。文章从传统各工法的特点出发,阐述CC工法的设想。基于工程实践过程,首先,从地下结构的分割与转换2个角度,重点介绍大型地下空间的形成过程、型钢和钢筋混凝土组合结构管节、节点处理措施等创新内容; 然后,针对B类节点的处理措施、整体背土现象等工程问题进行解决与优化; 最后,探讨该工法拓展应用的可能性,分别介绍多层、曲线、长距离、装配式结构大型地下空间的初步方案。CC工法的成功研发,旨在为城市大型地下空间开发提供一套新的解决思路。     

矩形顶管隧道群施工对后背土体扰动规律的初步研究

为更准确地计算矩形顶管隧道施工所需顶推力,揭示小间距顶管隧道群施工中后背土体在顶推力多次叠加作用扰动后的变化情况。首先,基于现有顶管顶推力相关计算公式推导出适用于矩形顶管的顶推力计算公式。然后,整理分析某顶管隧道群工程施工中后背土体水平位移、土压力实测数据,论证矩形顶管顶推力计算公式的正确性与合理性,得到后背土体受顶推力作用产生的水平位移是以隧道中心处为最大值的弓形分布、土体在顶推力二次作用下会产生更为显著的变化且存在残余应力现象等结论。最后,采用统计方法对顶推压力与后背土体水平位移、土压力之间的数据进行处理,取得后背土在顶推压力作用下产生水平位移与土压力的经验公式。     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

Multi‐objective highway alignment optimization using a genetic algorithm

The available highway alignment optimization algorithms use the total cost as the objective function. This is a single objective optimization process. In this process, travel‐time, vehicle operation accident earthwork land acquisition and pavement construction costs are the basic components of the total cost. This single objective highway alignment optimization process has limited capability in handling the cost components separately. Moreover, this process cannot yield a set of alternative solutions from a single run. This paper presents a multi‐objective approach to overcome these shortcomings. Some of the cost components of highway alignments are conflicting in nature. Minimizing some of them will yield a straighter alignment; whereas, minimizing others would make the alignment circuitous. Therefore, the goal of the multiobjective optimization approach is to handle the trade‐off amongst the highway alignment design objectives and present a set of near optimal solutions. The highway alignment objectives, i.e., cost functions, are not continuous in nature. Hence, a special genetic algorithm based multi‐objective optimization algorithm is suggested The proposed methodology is demonstrated via a case study at the end.     

The Alternative Motor Fuels Act, alternative-fuel vehicles, and greenhouse gas emissions

The corporate average fuel economy (CAFE) standard is the major policy tool to improve the fleet average miles per gallon of automobile manufacturers in the US. The Alternative Motor Fuels Act (AMFA) provides special treatment in calculating the fuel economy of alternative-fuel vehicles to give manufacturers CAFE incentives to produce more alternative-fuel vehicles. AMFA has as its goals an increase in the production of alternative-fuel vehicles and a decrease in gasoline consumption and greenhouse gas emissions. This paper examines theoretically the effects of the program set up under AMFA. It finds that, under some conditions, this program may actually increase the production of fuel-inefficient gasoline vehicles, gasoline consumption and greenhouse gas emissions.