长输管线末段储气系统的研究

主要研究长输管线末段管道储存天然气系统。介绍了长输管线末段管道储存天然气的两种方法，阐明了长输管线末段管道的工况特点，给出了末段管道在输气的情况下储气能力的计算方法及应用条件，设计了长输管线末段管道储存天然气与原有相结合的计算程序。根据长输管线的供气方式采用末段管道储存天然气更加经济合理，对工程施工具有现实意义。     

惠银线控制输送运行分析

惠安堡-银川长输原油管道于2017年7月1日至8月11日控制每日运行时间输送,但受炼厂恢复生产的不确定性影响,多次调整管道运行方式,保证管线输送平稳。通过控制启停输量,检验了管道的适应性,保证宁夏石化炼厂年检工作,并为"三高"原油长输管道低输量运行提供参考。     

大口径钢质管道内减阻涂层涂敷施工综述

在大口径长输天燃气管线上采用内涂层减阻技术，以达到降低管线摩阻、增加管输量、降低管线运行综合成本的目的，在我国首次应用于西气东输工程。根据实际施工经验，本文详细阐述了内减阻涂层的施工工艺流程，介绍了内涂敷设备和内涂敷质量控制，对内涂层的涂敷施工有一定的参考价值。     

大口径钢质管道内减阻涂层涂敷施工综述

在大口径长输天然气管线上采用内涂层减阻技术，以达到降低管线摩阻、增加管输量、降低管线运行综合成本的目的，在我国首次应用于西气东输工程。根据实际施工经验，本文详细阐述了内减阻涂层的施工工艺流程，介绍了内涂敷设备和内涂敷质量控制，对内涂层的涂敷施工有一定的参考价值。     

长呼输气管线的外防腐设计

在天然气长输管线的设计中，外腐蚀设计是至关重要的，它直接关系到长输管线的运行寿命。在长呼天然气输气管线设计中，根据管线的具体情况，进行经济、技术的比选，选用了煤焦油瓷漆作为管线的主要外防腐层。煤焦油瓷漆防腐性能好、价格合理，材料来源广泛，涂层厚，适用于螺旋焊缝管，电绝缘性好，吸水性低，使用寿命超过50a．全线共设置10座阴极保护站，采用“阴极保护参数在线自动监测系统”对管道的阴极保护参数进行在线监测。     

长呼线和马惠线夏季运行方式对比分析

长呼线和马惠线都是输送长庆油田原油的长输管道。马惠线采用裸管,夏季采用常温输送方式,而长呼线采用保温管道,夏季却采用加热输送方式。文中从所输油品物性,管道沿线地温、管线总传热系数、油品输送距离等方面对比分析长呼线和马惠线的差异,探讨限制长呼线夏季常温输送可行性的因素,提出了长呼线夏季运行方式的优化方案,建议长呼线夏季采用首站不加热、中间站加热的运行方式。     

管线球阀功能的规范要求及其结构设计

针对用于长输油气管道的API 6D球阀设计的特殊性及关注点,介绍了管线球阀阀座的活塞效应原理,分析了API 6D规范对管线球阀的密封结构、功能要求、结构设计要点及功能影响因素,与API 608球阀在结构、功能、受力状态等方面进行了对比,并通过工程实践,针对长输管道工程的特殊性,提出了管线球阀适应长输管道工况的结构设计方案及工艺措施。     

提升输气管道输气量改造方案

为解决已建长输管线输气能力不足的问题,以实际运行中的长-乌输气管道改造为例,介绍了提升输气管道输气量的改造方案。通过分析管线沿途场站的压力损失情况,分别从更换处理厂流量计与调节阀、更换末站调压阀、过滤器(分离器)降压、清管等4个方面采取了升压措施,并对改造的效果和投资效益进行了预测评估。经实际检验,采取了上述升压改造方案后,输气管道的输气量达到了预计效果,且经济上可行,从而为提升长输管道输气量提供了改造思路。     

PCM技术及其在兰成渝管道上的应用

长输管道腐蚀绝大部分为外部腐蚀,因此准确检测和评价外防腐层的状况,是保证管道安全运行的基础。文中介绍了用多频管中电流法（PCM）对防腐层进行检测的原理,结合兰成渝长输管线现场的应用,验证了该技术的准确性及科学性。同时,对其使用情况进行了总结,并展望PCM在应用中存在的不足之处。     

濮--临输油管线改输天然气前的物理化学清洗

长输原油管线改输天然气之前,必须对其内壁集结的大量含油蜡垢和机械杂质进行彻底清洗,以保证管线的输气质量和天然气的准确计量,主要介绍了采用物理与化学清洗技术相结合的方法,对濮-临输油管线聊城至临邑Ф377×7的121km管段进行不间断清洗一次成功的施工方案、实施过程及清洗效果,为国内长输原油管线清洗提供了有益的经验.     

A model for national freight flows,distribution centers,empty trucks and urban truck movements

Trucks travel both short distances for local deliveries and long distances for transporting goods across the country. Often their travel behavior is tour-based, they run under tight schedules and under curfew on selected roads. Despite these differences from personal travel, in practice truck models largely follow person travel methods. To overcome this shortcoming, a two-layer truck model is developed for the Chicago Metropolitan Area. Long-distance trucks are driven by commodity flows, with distribution centers, rail yards, marine ports and airports being represented explicitly. Empty trucks are accounted for as well. For the short-distance truck model, a novel parameter estimation method makes use of limited data to derive region-specific parameters. The model is fully operational and validates reasonably well against traffic counts.     

Taxi vacancy duration: a regression analysis

Taxi vacancy duration is a major efficiency measure for taxi services. A clear understanding of the various factors and their effect on vacancy duration is necessary for the optimal operational management of taxis. Previous research has only dealt with vacancy duration by assuming probability distributions and has not investigated heterogeneity in the data caused by various factors. We develop a parametric duration model using not only new operational characteristics but also variables associated with taxi demand, such as weather, land use, demographics, socioeconomic variables, and accessibility of public transportation. The model is applied to a large-scale New York City (NYC) taxi trip dataset that covers operations for 2013. The results show that all the attributes have significant associations with vacancy duration that follows a log-normal distribution. Our study is expected to help improve the efficiency of taxi operations by decreasing the time spent in vacant states.     

稠油掺稀后混油黏度计算方法的研究

稀释输送是传统的稠油降黏输送方法,因其工艺简单,降黏效果在管输过程中较稳定,一直在国内外得到广泛应用。但稠油中加入稀油后其混油黏度又是一个难点,混油黏温数据是摩阻计算的重要参数,是输油管道设计和运行管理的重要参数,其准确性对水力计算结果至关重要。对混合原油的黏度计算,国内外学者提出了不少经验公式、半经验公式以及计算图表,且大多是利用实验数据通过线性回归得到的,每种模型都有一定的适用范围。通过对Cragoe模型进行修正,得出稠油掺入稀油黏度计算需分段选择模型的结论。     

On the distribution of urban road space for multimodal congested networks

Transport systems in real cities are complex with many modes of transport sharing and competing for limited road space. This work intends to understand how space distributions for modes and interactions among modes affect network traffic performance. While the connection between performance of transport systems and general land allocation is the subject of extensive research, space allocation for interacting modes of transport is an open research question. Quantifying the impact of road space distribution on the performance of a congested multimodal transport system with a dynamic aggregated model remains a challenge. In this paper, a multimodal macroscopic fundamental diagram (MFD) is developed to represent the traffic dynamics of a multimodal transport system. Optimization is performed with the objective of minimizing the total passenger hours traveled (PHT) to serve the total demand by redistributing road space among modes. Pricing strategies are also investigated to provide a higher demand shift to more efficient modes. We find by an application to a bi-modal two-region city that (i) the proposed model captures the operational characteristics of each mode, and (ii) optimal dynamic space distribution strategies can be developed. In practice, the approach can serve as a physical dynamic model to inform space distribution strategies for policy makers with different goals of mobility.     

Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment

The paper proposes a first-order macroscopic stochastic dynamic traffic model, namely the stochastic cell transmission model (SCTM), to model traffic flow density on freeway segments with stochastic demand and supply. The SCTM consists of five operational modes corresponding to different congestion levels of the freeway segment. Each mode is formulated as a discrete time bilinear stochastic system. A set of probabilistic conditions is proposed to characterize the probability of occurrence of each mode. The overall effect of the five modes is estimated by the joint traffic density which is derived from the theory of finite mixture distribution. The SCTM captures not only the mean and standard deviation (SD) of density of the traffic flow, but also the propagation of SD over time and space. The SCTM is tested with a hypothetical freeway corridor simulation and an empirical study. The simulation results are compared against the means and SDs of traffic densities obtained from the Monte Carlo Simulation (MCS) of the modified cell transmission model (MCTM). An approximately two-miles freeway segment of Interstate 210 West (I-210W) in Los Ageles, Southern California, is chosen for the empirical study. Traffic data is obtained from the Performance Measurement System (PeMS). The stochastic parameters of the SCTM are calibrated against the flow-density empirical data of I-210W. Both the SCTM and the MCS of the MCTM are tested. A discussion of the computational efficiency and the accuracy issues of the two methods is provided based on the empirical results. Both the numerical simulation results and the empirical results confirm that the SCTM is capable of accurately estimating the means and SDs of the freeway densities as compared to the MCS.     

Travel demand model system for the information era

The emergence of new information technologies and recent advances in existing technologies have provided new dimensions for travel demand decisions. In this paper we propose a comprehensive travel demand modeling framework to identify and model the urban development decisions of firms and developers and the mobility, activity and travel decisions of individuals and households, and to develop a system of models that can be used by decision makers and planners to evaluate the effects of changes in the transportation system and development of information technologies (e.g. various tele-commuting, tele-services and Intelligent Transportation Systems).The implementation of an operational model system based on this framework is envisioned as an incremental process starting with the current best practice of disaggregate travel demand model systems. To this end, we present an activity-based model system as the first stage in the development of an operational model system.     

Validating the Passenger Traffic Model for Copenhagen

The paper presents a comprehensive validation procedure for the passenger traffic model for Copenhagen based on external data from the Danish national travel survey and traffic counts. The model was validated for the years 2000–2004, with 2004 being of particular interest because the Copenhagen Metro became operational in autumn 2002. We observed that forecasts from the demand sub-models agree well with the data from the 2000 national travel survey, with the mode choice forecasts in particular being a good match with the observed modal split. The results of the 2000 car assignment model matched the observed traffic better than those of the transit assignment model. With respect to the metro forecasts, the model over-predicts metro passenger flows by 10–50%. The wide range of findings from the project resulted in two actions. First, a project was started in January 2005 to upgrade the model’s base trip matrices. Second, a dialog between researchers and the Ministry of Transport has been initiated to discuss the need to upgrade the Copenhagen model, e.g. a switching to an activity-based paradigm and improving assignment procedures.     

Priority Berthing For Congested Ports: rationale and a model

Adverse effects on a national economy of port congestion are identified. The rationale underlying a system of priority berthing for awaiting vessels is described and contrasted with the operational system of first‐come, first‐served. A system of priority berthing is capable of minimizing the generalized social cost of congestion and this is structured mathematically as a multi‐attribute, decision‐making problem. A worked example is outlined and a computer program described.     

Optimizing train operational plan in an urban rail corridor based on the maximum headway function

The train operational plan (TOP) plays a crucial role in the efficient and effective operation of an urban rail system. We optimize the train operational plan in a special network layout, an urban rail corridor with one terminal yard, by decomposing it into two sub-problems, i.e., the train departure profile optimization and the rolling stock circulation optimization. The first sub-problem synthetically optimizes frequency setting, timetabling and the rolling stock circulation at the terminal without a yard. The maximum headway function is generated to ensure the service of the train operational plan without considering travel demand, then we present a model to minimize the number of train trips, and design a heuristic algorithm to maximize the train headway. On the basis of a given timetable, the rolling stock circulation optimization only involves the terminal with a yard. We propose a model to minimize the number of trains and yard–station runs, and an algorithm to find the optimal assignment of train-trip pair connections is designed. The computational complexities of the two algorithms are both linear. Finally, a real case study shows that the train operational plan developed by our approach enables a better match of train headway and travel demand, and reduces the operational cost while satisfying the requirement of the level of service.     

Modelling public transport on‐board congestion: comparing schedule‐based and agent‐based assignment approaches and their implications

Transit systems are subject to congestion that influences system performance and level of service. The evaluation of measures to relieve congestion requires models that can capture their network effects and passengers' adaptation. In particular, on‐board congestion leads to an increase of crowding discomfort and denied boarding and a decrease in service reliability. This study performs a systematic comparison of alternative approaches to modelling on‐board congestion in transit networks. In particular, the congestion‐related functionalities of a schedule‐based model and an agent‐based transit assignment model are investigated, by comparing VISUM and BusMezzo, respectively. The theoretical background, modelling principles and implementation details of the alternative models are examined and demonstrated by testing various operational scenarios for an example network. The results suggest that differences in modelling passenger arrival process, choice‐set generation and route choice model yield systematically different passenger loads. The schedule‐based model is insensitive to a uniform increase in demand or decrease in capacity when caused by either vehicle capacity or service frequency reduction. In contrast, nominal travel times increase in the agent‐based model as demand increases or capacity decreases. The marginal increase in travel time increases as the network becomes more saturated. Whilst none of the existing models capture the full range of congestion effects and related behavioural responses, existing models can support different planning decisions. Copyright © 2016 John Wiley & Sons, Ltd.