沥青混合料水稳性与粘附性实验方法相关性的灰关联分析

用灰关联理论分析了不同的沥青与集料粘附性实验方法与沥青混合料水稳性的相关关系,结果表明在水煮法、水浸法、光电比色法及SHRP净吸附法中,水浸法试验结果与沥青混合料水稳性相关关系最好,而水煮法最差。虽然SHRP净吸附法能够量化评定沥青与集料的兼容性,试验结果与沥青混合料水稳定性相关关系也比较好,但该法试验条件较严格,试验操作亦较复杂。鉴于此,建议在工程中应优先考虑水浸法作为沥青与集料粘附性的评价指标。     

Shared versus private mobility: Modeling public interest in autonomous vehicles accounting for latent attitudes

Emerging autonomous vehicles (AVs) and shared mobility systems per se will transform urban passenger transportation. Coupled together, shared AVs (SAVs) can facilitate widespread use of shared mobility services by providing flexible public travel modes comparable to private AV. Hence, it may be conjectured that future urban mobility is likely an on-demand service and AV private ownership is unappealing. Nonetheless, it is still unclear what observable and latent factors will drive public interest in (S)AVs, the answer to which will have important implications on transportation system performance. This paper aims to jointly model public interest in private AVs and multiple SAV configurations (carsharing, ridesourcing, ridesharing, and access/egress mode) in daily and commute travels with explicit treatment of the correlations across the (S)AV types. To this end, multivariate ordered outcome models with latent variables are employed, whereby latent attitudes and preferences describing traveler safety concern about AV, green travel pattern, and mobility-on-demand savviness are accounted for using structural and measurement equations. Drawing from a stated preference survey in the State of Washington, important insights are gained into the potential user groups based on the socio-economic, built environment, and daily/commute travel behavior attributes. Key policies are also offered to promote public interest in (S)AVs by scrutinizing the marginal effects of the latent variables.     

Real time transit demand prediction capturing station interactions and impact of special events

Demand for public transportation is highly affected by passengers’ experience and the level of service provided. Thus, it is vital for transit agencies to deploy adaptive strategies to respond to changes in demand or supply in a timely manner, and prevent unwanted deterioration in service quality. In this paper, a real time prediction methodology, based on univariate and multivariate state-space models, is developed to predict the short-term passenger arrivals at transit stations. A univariate state-space model is developed at the station level. Through a hierarchical clustering algorithm with correlation distance, stations with similar demand patterns are identified. A dynamic factor model is proposed for each cluster, capturing station interdependencies through a set of common factors. Both approaches can model the effect of exogenous events (such as football games). Ensemble predictions are then obtained by combining the outputs from the two models, based on their respective accuracy. We evaluate these models using data from the 32 stations on the Central line of the London Underground (LU), operated by Transport for London (TfL). The results indicate that the proposed methodology performs well in predicting short-term station arrivals for the set of test days. For most stations, ensemble prediction has the lowest mean error, as well as the smallest range of error, and exhibits more robust performance across the test days.     

浅析0116号台风"百合"路径异常的原因

分析了0l16号台风期间的天气形势，认为500hPa环境流场的急剧调整导致引导气流不稳定，以及双台风的相互作用是该台风路径异常的原因。对船舶驾驶员学习使用高空天气图分析和预测台风路径有一定的指导作用。     

船用燃机性能降级新型预测模型建立及应用分析

船用燃气轮机气路维护是舰船动力系统健康管理当中必要的环节,采用视情维护的方法是当前十分先进的维护手段,其中对气路降级趋势的预测是维护方法的核心。气路降级数据具有明确的增长趋势与不规律的波动性,符合灰色系统的特征。本文采用无偏灰色预测模型改进灰色马尔科夫模型,在此基础上扩大原始数据的维数,采用灰色关联度模型,将类似于当前序列的参考序列引入,最终构成了一种新的混合预测模型。最后,选择燃气轮机压气机结垢的过程作为实例来验证这一新的模型。通过研究模型参数和预测准确性之间的关系,为实例提出了建议的最佳参数。从预测准确性与对波动性的预测角度与不同的预测模型的比较结果表明,新的模型优于一些其他序列预测模型。     

城市居民个人属性与出行方式链相关性分析

首先引出基于活动理论的出行需求预测方法,将活动—出行理论和传统的出行方式相结合,提出出行方式链的概念,并明确出行方式链的两大特性:一致性和转换性;然后阐述城市居民个人属性与出行方式链相关性分析方法,并以2006年4月上虞市的居民出行调查数据为基础,对城市居民个人属性与出行方式链之间的相关性进行实例分析;最后,说明个人属性对出行方式链的选择起着至关重要的作用。     

水平管路气液两相段塞流电导探针信号分析

利用自制电导探针采集了气水两相管路中段塞流的液位数据，并对数据进行了统计学分析。实验中发现，环状探针的测量数据要优于双平行探针的测量数据，而探针信号与压力信号一样，可以反映两相流动流型的统计特征，为电导探针的应用做了实验验证，并为流型的识别提供了依据。     

动态环境下基于FFT实现伪码快速捕获

无线电导航系统中，载体动态性引入的多普勒频移对扩频信号捕获造成了很大困难。针对全数字化实现的扩频接收机，提出了一种新的捕获方案，即基于FFT算法实现对多普勒进行一定程度的补偿，解决了高动态环境下伪码序列的快速捕获问题。理论分析和计算机仿真结果表明，该方法简单有效。     

发动机关联性参数的数据流分析

数据流分析法在电控发动机的故障诊断中越来越多地被采用。但在分析过程中,更多进行的是单一数据分析,而疏忽了数据流的关联性,这样导致漏诊、误诊时有发生。对于非关联性参数,通过单一数据流的直接分析,大都可以判断故障的原因和故障点。但关联性参数必须同时读取多个数据流,并通过相互关系进行计算确定关联性参数,然后进行综合分析,才能判断故障点和故障原因。     

Journal of Marine Science and Application 2014 Sum. Contents

正~~