行人过街需要分析研究

通过调查分析研究,运用心理学需要理论和交通工程理论,分析了行人过街过程中的各种需要,包括心理需要、时间和空间需要、环境和其他需要。对过街过程中需要的具体内容进行了阐述。最后总结了各种需要之间的联系。     

大跨度斜拉桥与T构协作体系的动力特性分析

协作体系的动力特性主要包括体系的自振频率和主振型,它是协作体系结构动力分析的基础和前提。通过建立空间有限元模型,对金马大桥这种独特的协作体系结构进行了动力特征分析,给出了前20阶频率和相应的振型,并且对同等跨径的普通斜拉桥和剪力铰方案做了相应的动力特征比较分析,同时分别计算了各种结构参数变化对协作体系结构动力特性的影响,对其影响规律作了详细的讨论,本文的结果为协作体系的固有振动分析和抗震设计提供了理论依据。     

基于路网子图空间的交通流平衡分析方法

通过定义路网子图空间,提出了基于路网子图空间的Wardrop平衡原理,建立了相应的交通流平衡分析模型,并通过实例阐释了偏态均衡路网交通流的形成机理与演化过程。研究表明:该模型能够很好地解释包括新路开通期的路网交通流、换乘子图空间路网交通流、收费道路偏好子图空间路网交通流等多种情形下由于网络结构被差异性地认知所形成的偏态均衡路网交通流现象,为多标准下交通流的平衡分析建立了新途径;该分析方法有助于道路网络结构设计与道路网络管理方案的优化。     

基于Takens理论和SVM的滑坡位移预测

针对滑坡变形时序非线性,数据量少的特点,引入Takens理论,采用支持向量机(SVM)建立其预测模型,建模过程中,比较了由不同核函数获得的SVM模型的性能,同时将SVM与RBF、El-man神经网络模型进行外推7步预测试验比较。结果表明:RBF核函数具有更好的工程实用价值;在有限样本情况下,SVM预测模型具有更好的准确性和泛化性,其7步预测平均误差率控制在5%以内,可见该方法在滑坡变形预测方面极具潜力。     

基于子波能量和神经网络分类器的机动车车型识别

为了使交通管理系统能进行可靠的机动车分类,研究了轿车、轻型越野车和货车3种机动车目标的声信号,提出了一种采用子波分解后不同尺度上声信号能量作为特征向量的特征提取算法,并设计了kNN(k近邻)分类器和改进BP神经网络分类器用于目标分类。目标识别和分类试验结果表明:所提出的特征提取算法能够很好地体现不同类型目标之间的差异,提取的特征向量稳健;设计的改进BP神经网络分类器的分类精度可达92.6%,且分类效果优于kNN分类器。     

桥梁工程设计数据库管理系统的研究

基于关系数据库理论的观点，结合工程的实际需要，研究开发了“桥梁工程设计数据库管理系统”。本文讨论了系统分析、数据模型选择、系统的总体设计、一般应用模块、高级应用模块以及系统软件实现等有关的技术问题。     

煌水河双曲拱桥的病害诊断与力学性能研究

以某四孔钢筋混凝土空腹式连续双曲拱桥为例,结合目前既有双曲拱桥的典型病害调研和国内外旧桥承载力的评定方法,对其进行了全面的健康检测,根据现场拱肋线形的实测结果,建立了该桥原设计与现行状态的全三维有限元分析模型,从理论上分析了该桥产生病害的主要原因,理论分析结果得到了现场调研数据的验证。得到了桥梁长期单方向超载以及拱肋横向联系弱、横向分布效应差,造成一侧拱肋应力长期处于高水平而产生徐变变形,主拱肋偏离原悬链线拱改变了其主要承压设计思想,加之年久失修造成恶性循环,从而成为“危桥”的结论,为该桥的加固设计提供了科学依据。     

连续梁拱桥空间计算分析

就一个连续梁拱桥方案论证过程,运用ansys有限元软件建立空间模型,对该桥的静力、动力及稳定性等控制因素进行了计算分析.结果表明,该连续梁拱桥各项特性均满足规范要求.     

街道设计理念下工程实践的若干思考

“完整街道”、“街道设计”等城市道路改造设计理念开始广泛应用于城市道路旧改等实际工程项目。然而，街道设计理念与传统的设计习惯、道路管理模式及使用者的接受程度，依然在现实应用以及工程实施上存在较大的分歧。以深圳市罗湖区道路设施品质提升工程和深圳市罗湖区精品示范路工程两个项目为工程背景，分别从宏观的街道空间改造和部分微观细节设计两个角度，分析项目实施过程中存在的难点和优化处置方案，为后续工程实践以及相关街道设计导则优化提供借鉴。     

The impacts of changing flight demands and throughput performance on airport delays through the Great Recession

Several significant events between 2007 and 2009 impacted flight demands and the abilities of the three major New York area airports to handle demand. This paper assesses the results of applying a probabilistic simulation method – which isolates the individual contributions of changes in flight demand and changes in airport throughput performance to changes in flight delays – to diagnose how these different events may have caused operational changes at these airports, and in turn, how the results may be used to inform policies for appropriate countermeasures. The analysis revealed two key observations. Firstly, certain patterns in throughput performance shifts caused the most significant delays, and were more likely to have been caused by controller staffing issues rather than caps. Secondly, relatively constant average delays from one year to the next may result from significant demand drops accompanied by large throughput performance degradations at an airport. This suggests that not only operational limitations on capacity encourage airlines to reduce schedules, but that changed demands can also impact throughput performance. Overall, the analysis indicates that caps may not have provided their fully intended delay benefits. Although they successfully reduced overall flight demands at LGA and JFK, they also directly limited throughput performance at critical times, in turn limiting delay benefits. In addition, demands at the busiest times of the day appear to be relatively inelastic to these operational limitations, insofar as demand profiles at EWR and JFK remained “peaky” in 2008 and 2009. Also, the recession was largely responsible for reducing demands at the airports in 2009, but the delay benefits of this were dampened by a corresponding throughput performance degradation. Based on the above observations, a more direct demand management policy combined with policies that focus on maintaining high staffing capabilities at critical times of the day may be considered, to reduce the likelihood of major queue formation on days that do experience sustained demands. The results also suggest that a more flexible caps system, particularly during times of heavy queues, could be explored. Although airport practitioners have keen understandings of how their airports operate, without the support of quantitative analysis tools, it can be more difficult to argue the need for appropriate countermeasures. An analysis such as the one presented here can provide the detailed quantitative substantiation required to build cases for these targeted policy directives and infrastructure investments.