大体积承台施工阶段温度场分析及控制方法研究

为了研究大体积承台施工阶段的温度场及相应的裂缝控制方法,文章基于水化热温度传导理论,采用有限元分析方法,以某大跨度连续刚构桥的大体积混凝土桩承台为工程实例,分别考虑冷却水管作用、保温层作用,对施工期间的大体积混凝土水化热温度场进行了分析研究,结果表明:承台冷却管布置方案能够保证各控制点内外温差在合理范围内,温度变化产生的拉应力在允许范围内,有效控制了承台开裂,保证了施工质量,理论计算结果可为同类桥梁的大体积混凝土施工提供借鉴和参考。     

桥梁工程大体积混凝土水化热控制施工技术研究

大体积混凝土由于体积大、混凝土用量多、水泥水化热相对较高,因此施工控制不当极易造成温度裂缝问题的发生,控制大体积混凝土水化热对于桥梁工程结构施工具有重要的作用。针对桥梁大体积混凝土水化热控制,首先分析了大体积混凝土结构特点,进而介绍了大体积混凝土温度计算方法,并系统的论述了大体积混凝土水化热施工控制技术,可以为大体积混凝土结构施工作业管理提供合理的技术参考。     

燃气加臭计量泵标定校验

介绍了我国现阶段采用的加臭技术及现状，介绍了加臭计量设施的工作原理，阐述对加臭计量泵手动控制模式和自动控制模式采用容积法进行标定校验所需的材料设备，以及校验原理和校验的过程方法。     

桥梁大体积混凝土水化热温度与裂纹控制

大体积混凝土的施工技术难点在于混凝土体积厚大，由于水泥水化热而引起的温度裂纹对工程的危害是十分巨大的。在工程实际中，采取“蓄热”法和冷凝管降温法等综合温控措施，可有效控制大体积混凝土温度裂纹。     

洒水车类罐体容积液位刻度的参数化设计计算方法

对于洒水车类罐体,很多时候需要知道在某个液位高度时水的体积的具体数值。针对洒水车类的罐体液位刻度的实际需要,文章介绍了不同形状的常见罐体确定容积液位刻度的计算方法,并针对这些计算方法的不足,提供了一种参数化设计计算的方法,即使用三维设计软件CATIA的优化设计模块,可以快速准确地进行容积液位刻度的计算,提高设计效率,减少设计成本。     

软基处理钉形双向搅拌桩施工技术——以G105野寨至桃花铺段改建工程钉形双向搅拌桩施工为例

在公路建设中,处理软基的方法很多,钉形双向搅拌桩是近几年软基处理的一种新型的地基加固方法。重点介绍钉形搅拌桩布置方式、施工工艺和质量检测标准。通过与常规水泥土搅拌桩施工相比较,钉形水泥土双向搅拌桩的成桩质量和软基处理效果均有较大提高,软基处理总成本有所下降,值得在软基处理中推广。     

沉管隧道测量技术

文章针对大型曲线沉管隧道的特点,论述了曲线沉管隧道的平面及高程控制测量、管段特征点标定测量、管段沉放测量,以及管内测量的方法,并给出了相应的计算公式.     

巴巴奥约河大桥主墩承台水化热分析

文章采用有限元结构软件对巴巴奥约河大桥主墩承台的水化热进程进行分析,并介绍了大体积混凝土温度和应力的电算方法,对主墩承台温度分布变化规律进行了探讨,为承台大体积混凝土施工提供参考。     

水泥混凝土拌和楼的计量标定

结合江苏省锡宜高速陆马公路预制厂拌和楼的计量标定,从集料、水泥与外加剂、拌和用水量三个方面分别阐述了对拌和楼计量标定的重要性与必要性,计量标定的标准与依据,提出了计量标定的程序控制和验证.     

固液两相流管道水击防护措施的计算分析

针对固液两相流的特点，建立了水击计算的运动方程及连续方程，并采用新方程对矿山常采用的容积泵输送，使用的储气缸缸、等减缓水电击压力的防护措施进行了计算分析。得出容积泵输送中的储气罐、泄压阀减压效果最好的结论。     

Simulating pedestrian movements at signalized crosswalks in Hong Kong

This paper presents a new pedestrian simulation (PS) model for signalized crosswalks in Hong Kong. This PS model is capable of estimating the variations of walking speed particularly on the effects of bi-directional pedestrian flows so as to determine the minimum required duration of pedestrian crossing time. Video records taken from the observational surveys at the selected crosswalk in urban area were used to extract the required data for model calibration. It was found that the design walking speed for signalized crosswalks should be varied by the effects of the bi-directional pedestrian flows. It was also interesting to note that the negative impact of the bi-directional flow effects (ranging from uni-directional to bi-directional pedestrian flows) on the chance of pedestrian crossing the crosswalk is increasing from free-flow to at-capacity flow conditions. The new PS model is also validated using an independent data set so as to examine the reliability of the simulation results. The validation results show that the new PS model can provide an accurate evaluation on the changes of walking speed and its standard deviation under different scenarios with particular emphasis on the effects of the bi-directional pedestrian flows. The advancement of this PS model can be applied to assess the effects of each improvement measure and to evaluate the benefits of each scenario in practice.     

Willingness to board: A novel concept for modeling queuing up passengers

This paper addresses an innovative concept, termed as queuing passengers’ willingness to board (WTB) the transit vehicles. In the peak hours, some queuing passengers cannot board a crowded bus/train, but when the same vehicle arrives at the next stop, some other passengers could still get on. This phenomenon reflects that passengers at different queuing locations have heterogeneous level of ambitions to board. A methodological framework is proposed for the quantitative investigation of WTB. First, a general model is proposed, together with a new least square method (LSM) for the calibration. Then, a parametric model is developed, which is also calibrated by the LSM. To refine the calibration method and deal with the biasness of survey data, a weighted least square method is further developed. Based on real survey data, the calibration results clearly support the existence of WTB, which can be used to estimate the capacity of transit vehicles. This paper also sheds some lights on the practical applications of the quantitative WTB.     

A generalised function for modeling bi-directional flow effects on indoor walkways in Hong Kong

This paper examines the relationships between walking speed and pedestrian flow under various bi-directional flow conditions at indoor walkways in Hong Kong. The effects of bi-directional pedestrian flows are investigated empirically with particular emphasis on their effects on walking time for different directions of flow at pedestrian walkways in Hong Kong. Flow measurements were conducted at selected indoor walkways in urban areas. A generalized walking time function that takes bi-directional flow distributions (or flow ratios) into account is proposed for these pedestrian facilities and calibrated for various flow conditions ranging from free-flow to congested-flow (at-capacity) situations. The bi-directional flow effects on free-flow walking speed, effective capacity and at-capacity walking speed are validated with observed data. It was found that the bi-directional flow ratios have significant impacts on both the at-capacity walking speeds and the maximum flow rates of the selected walkways but not on the free-flow walking speeds. The findings and study methodology provide better insight into the effects of bi-directional pedestrian flow characteristics and will assist engineers/planners in improving the design and operation of pedestrian facilities not only in Hong Kong, but also in other countries as well.     

An anisotropic continuum model considering bi-directional information impact

In traffic flow with naturalistic driving only, stimulus information pre-dominantly comes from the preceding vehicles with drivers occasionally responding to the following vehicles through the inspection of rear-view mirrors. Such one-sided information propagation may potentially be altered in future connected vehicle environment. This brings new motivations of modeling vehicle dynamics under bi-directional information propagation. In this study, stemming from microscopic bi-directional car-following models, a continuum traffic flow model is put forward that incorporates the bi-directional information impact macroscopically but can still preserve the anisotropic characteristics of traffic flow and avoid non-physical phenomenon such as wrong-way travels. We then analyze the properties of the continuum model and respectively illustrate the condition that guarantees the anisotropy, eradicates the negative travel speed, preserves the traveling waves and keeps the linear stability. Through a series of numerical experiments, it is concluded that (1) under the bi-directional looking context only when the backward weight ratio belongs to an appropriate range then the anisotropic property can be maintained; (2) forward-propagating traffic density waves and standing waves emerge with the increasing consideration ratio for backward information; (3) the more aggressive driving behaviors for the forward direction can delay the backward-propagating and speed up the forward-propagating of traffic density waves; (4) positive holding effect and negative pushing effect of backward looking can also be observed under different backward weight ratios; and (5) traffic flow stability varies with different proportion of backward traffic information contribution and such stability impact is sensitive to the initial traffic density condition. This proposed continuum model may contribute to future development of traffic control and coordination in future connected vehicle environment.     

Automatic calibration of fundamental diagram for first‐order macroscopic freeway traffic models

Despite its importance in macroscopic traffic flow modeling, comprehensive method for the calibration of fundamental diagram is very limited. Conventional empirical methods adopt a steady state analysis of the aggregate traffic data collected from measurement devices installed on a particular site without considering the traffic dynamics, which renders the simulation may not be adaptive to the variability of data. Nonetheless, determining the fundamental diagram for each detection site is often infeasible. To remedy these, this study presents an automatic calibration method to estimate the parameters of a fundamental diagram through a dynamic approach. Simulated flow from the cell transmission model is compared against the measured flow wherein an optimization merit is conducted to minimize the discrepancy between model‐generated data and real data. The empirical results prove that the proposed automatic calibration algorithm can significantly improve the accuracy of traffic state estimation by adapting to the variability of traffic data when compared with several existing methods under both recurrent and abnormal traffic conditions. Results also highlight the robustness of the proposed algorithm. The automatic calibration algorithm provides a powerful tool for model calibration when freeways are equipped with sparse detectors, new traffic surveillance systems lack of comprehensive traffic data, or the case that lots of detectors lose their effectiveness for aging systems. Furthermore, the proposed method is useful for off‐line model calibration under abnormal traffic conditions, for example, incident scenarios. Copyright © 2015 John Wiley & Sons, Ltd.     

Optimization-based assisted calibration of traffic simulation models

Use of traffic simulation has increased in recent decades; and this high-fidelity modelling, along with moving vehicle animation, has allowed transportation decisions to be made with better confidence. During this time, traffic engineers have been encouraged to embrace the process of calibration, in which steps are taken to reconcile simulated and field-observed performance. According to international surveys, experts, and conventional wisdom, existing (non-automated) methods of calibration have been difficult or inadequate. There has been extensive research on improved calibration methods, but many of these efforts have not produced the flexibility and practicality required by real-world engineers. With this in mind, a patent-pending (US 61/859,819) architecture for software-assisted calibration was developed to maximize practicality, flexibility, and ease-of-use. This architecture is called SASCO (i.e. Sensitivity Analysis, Self-Calibration, and Optimization). The original optimization method within SASCO was based on “directed brute force” (DBF) searching; performing exhaustive evaluation of alternatives in a discrete, user-defined search space. Simultaneous Perturbation Stochastic Approximation (SPSA) has also gained favor as an efficient method for optimizing computationally expensive, “black-box” traffic simulations, and was also implemented within SASCO. This paper uses synthetic and real-world case studies to assess the qualities of DBF and SPSA, so they can be applied in the right situations. SPSA was found to be the fastest method, which is important when calibrating numerous inputs, but DBF was more reliable. Additionally DBF was better than SPSA for sensitivity analysis, and for calibrating complex inputs. Regardless of which optimization method is selected, the SASCO architecture appears to offer a new and practice-ready level of calibration efficiency.     

A study of the bi-directional pedestrian flow characteristics at Hong Kong signalized crosswalk facilities

This paper investigates the bi-directional flow characteristics at signalized crosswalk facilities in Hong Kong. Pedestrian flow measurements were conducted at selected signalized crosswalks in Hong Kong urban area with and without the Light Rail Transit (LRT) railway tracks in the median of the carriageway. The pedestrian speed-flow functions for these crosswalk facilities were calibrated. The relationships between the walking speed at capacity and directional distribution of pedestrian flow (or flow ratio) are determined. The effects of different flow ratio on the effective capacity are also investigated. The bi-directional pedestrian flow effects on signalized crosswalk facilities with LRT tracks are found more significant than those without LRT tracks. The result could be used as a basis to improve the assessment of the crosswalk's capacity and to determine the design walking speeds under different flow ratios at signalized crosswalks in Hong Kong and in other Asian cities with similar environments.     

Camera calibration and vehicle tracking: Highway traffic video analytics

We describe a real-time highway surveillance system (RHSS), which operates autonomously to collect statistics (speed and volume) and generates incident alerts (e.g., stopped vehicles). The system is designed to optimize long-term real-time performance accuracy. It also provides convenient integration to an existing surveillance infrastructure with different levels of service. Innovations include a novel 3-D Hungarian algorithm which is utilized for object tracking and a practical, hands-off mechanism for camera calibration. Speed is estimated based on trajectories after mapping/alignment with respect to dominant paths learned based on an evolutionary dynamics model. The system, RHSS, is intensively evaluated under different scenarios such as rain, low-contrast and high-contrast lightings. Performance is presented in comparison to a current commercial product. The contribution is innovation of new technologies that enable hands-off calibration (i.e., automatic detection of vanishing points) and improved accuracy (i.e., illumination balancing, tracking via a new 3-D Hungarian algorithm, and re-initialization of background detection on-the-fly). Results indicate the capability and applicability of the proposed system in real-time and real-world settings.     

Integrating mesoscopic dynamic traffic assignment with agent-based travel behavior models for cumulative land development impact analysis

A number of approaches have been developed to evaluate the impact of land development on transportation infrastructure. While traditional approaches are either limited to static modeling of traffic performance or lack a strong travel behavior foundation, today’s advanced computational technology makes it feasible to model an individual traveler’s response to land development. This study integrates dynamic traffic assignment (DTA) with a positive agent-based microsimulation travel behavior model for cumulative land development impact studies. The integrated model not only enhances the behavioral implementation of DTA, but also captures traffic dynamics. It provides an advanced yet practical approach to understanding the impact of a single or series of land development projects on an individual driver’s behavior, as well as the aggregated impacts on the demand pattern and time-dependent traffic conditions. A simulation-based optimization (SBO) approach is proposed for the calibration of the modeling system. The SBO calibration approach enhances the transferability of this integrated model to other study areas. Using a case study that focuses on the cumulative land development impact along a congested corridor in Maryland, various regional and local travel behavior changes are discussed to show the capability of this tool for behavior side estimations and the corresponding traffic impacts.     

Using geometric primitives to calibrate traffic scenes

In this paper, we address the problem of recovering the intrinsic and extrinsic parameters of a camera or a group of cameras in a setting overlooking a traffic scene. Unlike many other settings, conventional camera calibration techniques are not applicable in this case. We present a method that uses certain geometric primitives commonly found in traffic scenes, such as straight and curved lanes, lane markings, and poles in order to recover calibration parameters. We show experimentally that these primitives provide the needed redundancy and are capable of achieving accurate results suitable for most traffic monitoring applications.