基于事件触发的无线传感器网络动态分簇

针对由目标事件激发的无线传感器网络动态分簇问题,提出了一种动态分簇协议。着重研究了簇头竞选,成员招募和簇重组等关键环节,在簇头竞选机制中,提出了一种综合考虑了节点接收信号强度,剩余能量以及与汇聚节点的距离等因素的竞选方案。在簇成员招募阶段,提出了一种基于任务需求的自适应簇范围划分方法,约束了簇的规模,降低了簇内通信的能耗。仿真结果表明：该协议能够有效地节省节点能量,延长网络寿命,尤其适用于汇聚节点距离网络较远的情况。     

集中式自适应网格IMMJPDA算法

现有的集中式交互多模型联合概率数据互联( IM MJPDA)算法在多模型这个意义上都是基于固定结构的,而固定结构多模型算法存在的缺陷这些算法都不可避免的存在.为此,将一种变结构多模型算法——自适应网格交互多模型( AGIMM)算法和联合概率数据互联(JPDA)算法相结合,提出了用于多传感器多目标跟踪的集中式自适应网格IMMJPDA( AGIMMJPDA)算法.该算法通过自适应网格实现模型集合自适应调整来克服固定结构IMMJPDA存在的缺陷.仿真结果显示,该算法可以有效克服固定结构IMMJPDA算法存在的缺陷,并提高IMMJPDA算法的费效比.     

基于石墨烯的柔性薄膜电极进展

石墨烯具有诸多优异的物理、化学特性,在电化学储能领域得到了广泛的关注。本文综述了石墨烯薄膜以及石墨烯复合材料薄膜在锂离子电池以及超级电容器柔性电极中的应用进展。根据石墨烯在柔性电极中作用的不同分为三个部分结合研究实例分别论述,并对石墨烯基薄膜电极材料在柔性电化学储能器件中的应用前景进行了分析和展望。     

南海某FPSO STP单点系泊系统的再评估

本文针对一艘中国南海北部服役的STP(Submerged Turret Production)内转塔单点FPSO在极端环境条件下单点静密封失效问题进行了分析。STP浮筒静密封主要依靠浮筒上端液压大钳的预紧力、浮筒与舱壁的静摩擦力等来抵抗系泊系统的载荷,从而保证浮筒与船体舱壁的紧密贴合。本文进行了新旧百年一遇环境条件作用下系泊系统载荷评估分析,比较结果可以发现：在新的百年一遇条件作用下,单点系泊系统的最大系泊缆张力增加31%,相应地系泊系统作用在锚链盘的平面载荷增加33%,垂向载荷增加12%。进一步地进行了新环境条件下两百年一遇极端环境作用下的系泊系统响应分析,比较结果可以发现：两百年一遇环境条件作用下,平台平面位移、系泊缆最大张力以及系泊载荷均出现了不同程度的增加,此时系泊缆已不能满足系泊系统完整状态的安全系数要求。分析结果表明：该FPSO的STP静密封系统在新的环境条件下存在较大失效风险,有必要对液压锁紧装置进行优化和加强设计,浮筒与舱壁有必要重新进行结构强度评估。     

凝水泵出口压力波动问题机理研究

针对某凝给水系统部分工况下出现的凝水泵出口压力波动问题开展相关研究工作,通过调研系统实际运行参数,采用数值仿真和理论计算进行分析,推导系统汽蚀余量特性方程,获取系统参数对凝水泵运行情况边界条件的影响,进而获取导致凝水泵出口压力波动的原因,并提出相应的控制措施。     

二灰碎石基层冷再生施工技术应用

利用旧路面基层获取铣刨料,添加新鲜骨料、结合料后进行再生混合料级配组成及配合比设计。利用二灰比、集料含量与28d劈裂强度关系方程,对配合比进行验证。着重阐述了混合料拌和工艺及连续式拌和设备成品料仓的改进。在拌和、摊铺、压实、养生等工艺上对再生混合料的施工提出控制要点及质量控制措施。     

Enhanced traffic information dissemination to facilitate toll road utilization: a nested logit model of a stated preference survey in Texas

This paper investigates the effects of the provision of traffic information on toll road usage based on a stated preference survey conducted in central Texas. Although many researchers have studied congestion pricing and traffic information dissemination extensively, most of them focused on the effects that these instruments individually produce on transportation system performance. Few studies have been conducted to elaborate on the impacts of traffic information dissemination on toll road utilization. In this study, 716 individuals completed a survey to measure representative public opinions and preferences for toll road usage in support of various traffic information dissemination classified by different modes, contents, and timeliness categories. A nested logit model was developed and estimated to identify the significant attributes of traffic information dissemination, traveler commuting patterns, routing behavior, and demographic characteristics, and analyze their impacts on toll road utilization. The results revealed that the travelers using dynamic message sign systems as their primary mode of receiving traffic information are more likely to choose toll roads. The potential toll road users also indicated their desire to obtain traffic information via internet. Information regarding accident locations, road hazard warnings, and congested roads is frequently sought by travelers. Furthermore, high-quality congested road information dissemination can significantly enhance travelers’ preferences of toll road usage. Specifically the study found that travelers anticipated an average travel time saving of about 11.3 min from better information; this is about 30 % of travelers’ average one-way commuting time. The mean value of the time savings was found to be about $11.82 per hour, close to ½ of the average Austin wage rate. The model specifications and result analyses provide in-depth insights in interpreting travelers’ behavioral tendencies of toll road utilization in support of traffic information. The results are also helpful to shape and develop future transportation toll system and transportation policy.     

Safety modeling for two‐way left‐turn lanes and a procedure to identify two‐way left‐turn lane segments with safety concerns

In the past, two‐way left‐turn lane (TWLTL) median treatments have been frequently used in Florida to inexpensively improve traffic and safety performances. In order to identify factors that may have significant impacts on safety operations in TWLTL sections and to identify TWLTL locations that present existing and future safety concerns, a research project was carried out and results are summarized in the paper. In the research, a three‐year crash history database with crashes and section characteristics from a total of 1688 TWLTL sections all over Florida was developed and used. A negative binomial regression model was developed to determine the statistical relationship between the number of crashes per mile per year and several variables such as traffic volume, access density, posted speed, and number of lanes. In regard to the methodology, in order to identify locations with safety concerns, several steps are needed: development of real crash data distribution, determination of statistical distribution models that better represent the actual crash data, determination of percentile values for the average number of crashes, estimation of crash rates for sections with the same characteristics, estimation of critical values for the variables corresponding to the percentile values for average number of crashes, calculation of tables of critical average annual daily traffic values, and generation of a list of TWLTL locations with critical safety concerns. Results presented in the paper have been used in real applications. Copyright © 2012 John Wiley & Sons, Ltd.     

可拓理论在高等级公路隧道围岩分级中的应用研究

根据可拓理论在解决不相容问题及不确定问题等方面的突出特点,文章对其进行了适当的改进,得出高等级公路隧道围岩分级系统可拓评价体系,并应用于广东省惠深高速公路牛湖山隧道的围岩质量评价当中.且通过与灰色关联分析方法、专家经验方法等评价结果相比较,证明了高速公路隧道围岩分级系统可拓评价体系的科学性、合理性和经济性.     

Hybrid model for prediction of bus arrival times at next station

Effective prediction of bus arrival times is important to advanced traveler information systems (ATIS). Here a hybrid model, based on support vector machine (SVM) and Kalman filtering technique, is presented to predict bus arrival times. In the model, the SVM model predicts the baseline travel times on the basic of historical trips occurring data at given time‐of‐day, weather conditions, route segment, the travel times on the current segment, and the latest travel times on the predicted segment; the Kalman filtering‐based dynamic algorithm uses the latest bus arrival information, together with estimated baseline travel times, to predict arrival times at the next point. The predicted bus arrival times are examined by data of bus no. 7 in a satellite town of Dalian in China. Results show that the hybrid model proposed in this paper is feasible and applicable in bus arrival time forecasting area, and generally provides better performance than artificial neural network (ANN)–based methods. Copyright © 2010 John Wiley & Sons, Ltd.