基于Holon的虚拟应急物流协同体系及可靠性分析

为了提高应急救援的效率,通过引入Holonic系统建模的思想,构建了虚拟应急物流协同体系.在此基础上,考虑到应急物流高可靠性的特征,以及构造复杂系统可靠性指标和参数间解析表达式的困难性,利用基于贝叶斯网络对其体系结构进行可靠性分析.最后,实例分析了该协同体系的合理性和科学性.     

A model of bus bunching under reliability-based passenger arrival patterns

If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustrate when bus bunching might occur. We show that non-uniform arrival patterns can significantly influence the bus bunching process. With case studies we find that, even without exogenous delay, bunching can arise when the boarding rate is insufficient given the level of overall demand. Further, in case of exogenous delay, non-uniform arrivals can either worsen or improve the bunching conditions, depending on the level of delay. We conclude that therefore such effects should be considered when service control measures are discussed.     

Improved reliability of public transportation using real-time transfer synchronization

Service reliability of public transportation (PT) systems is a dominant ingredient in what is perceived as the PT image. Unreliable service increases the uncertainties of simultaneous arrivals of vehicles at a transfer point. Implementing proper control actions leads to preventing missed transfers, one of the undesirable features of PT service and a major contributor to a negative image. The present work focuses on performance measurements of a PT system offering direct transfers on multi-legged trips. The method developed evaluates and improves system performance by applying selected operational tactics in real-time scenarios. In order to investigate the efficiency level of the PT system, five types of vehicle positional situations with reference to a transfer point are considered: considerably ahead of schedule, ahead of schedule, on schedule, behind schedule, and considerably behind schedule. Each situation contributes differently to the degree of system performance. The optimization framework developed results in selected operational tactics to attain the maximum number of direct (without waiting) transfers and minimize total passenger travel time. The implementation of the concept is performed in two steps: optimization and simulation. The optimization process searches for the best operational tactics, using the states of the five vehicle-position types, and the simulation serves to validate the optimal results under a stochastic framework using the concept of a multi-agent system. A case study of Auckland, New Zealand, is described for assessing the methodology developed. Results showed a 58% improvement in the system performance index compared to no-tactic operations.     

Finding the most reliable path with and without link travel time correlation: A Lagrangian substitution based approach

Path travel time reliability is an essential measure of the quality of service for transportation systems and an important attribute in travelers’ route and departure time scheduling. This paper investigates a fundamental problem of finding the most reliable path under different spatial correlation assumptions, where the path travel time variability is represented by its standard deviation. To handle the non-linear and non-additive cost functions introduced by the quadratic forms of the standard deviation term, a Lagrangian substitution approach is adopted to estimate the lower bound of the most reliable path solution through solving a sequence of standard shortest path problems. A subgradient algorithm is used to iteratively improve the solution quality by reducing the optimality gap. To characterize the link travel time correlation structure associated with the end-to-end trip time reliability measure, this research develops a sampling-based method to dynamically construct a proxy objective function in terms of travel time observations from multiple days. The proposed algorithms are evaluated under a large-scale Bay Area, California network with real-world measurements.     

地铁线网结构对连通可靠性影响评价

地铁是现代大城市最重要的公共交通系统之一,其线网连通可靠性不但受到运营故障、恐怖袭击、踩踏事故等不确定性因素影响,也与线网结构有密切关系.为评价线网结构(表示为网络的线路组成)对地铁线网连通可靠性的影响,基于传统的节点连通可靠度概念定义了“线路连通重要度”新概念及其计算模型,即线路增减/失效前后网络平均连通可靠度的变化(百分比).采用基于排序的ORDER 方法和网络连通判断算法求解上述模型.以广州规划年地铁线网为例验证了所提模型的有效性,并分析了地铁线路特征(站点类型和数量)对网络连通可靠性的影响.结果显示,3号线的线路连通重要度最大(99.84%)为关键线路.研究发现而线路连通重要度受到线路中换乘站数量和中间站数量的综合影响,且前者的影响高于后者.研究结论值得交通规划和管理决策者在制定地铁建设和维护优先政策时参考和借鉴.     

一种快速计算随机变量函数均值与标准差的新方法

船舶全海域大型化是一个发展趋势,因此船舶总纵极限强度可靠性计算中需要将极端波浪的影响参数考虑在内。一般的载荷计算方法并没有考虑极端海况中出现的特殊波浪载荷的影响;另外对于可靠性分析,极端载荷是更为复杂的随机变量,一般的船舶可靠性计算方法因为局限于某种特定分布,可能出现无法适用的问题。选取极端海况中上浪、砰击和大幅纵摇等对船舶总纵波浪弯矩有较大影响的因素,从航行界限的角度出发,将这些因素引入极端波浪弯矩的计算中,所得极端波浪海况下的波浪弯矩极值数据比常规波浪弯矩极值更大。参考实验数据表明,考虑极端波浪海况的波浪弯矩计算方法能在一定程度上更加真实地反映船舶所受波浪载荷;其次通过考察不同可靠性计算方法的特点,利用实例计算,给出极端海况下船舶总纵极限强度可靠性计算方法的选取建议。     

基于状态转移法的冷却水系统动态可靠性分析

  目的  对于共因失效（CCF）的可靠性分析,现有研究基本上都假设发生共因失效事件必将导致相关单元失效。该假设对于电子元器件是准确的,但是对于可靠度高、结构复杂的机械设备会出现状态缺失的问题。为此,通过理论推导,提出一种考虑概率共因失效（PCCF）的多状态可靠度计算方法。  方法  该方法将共因分为致命型和非致命型,且将每种共因的作用分解在各单元上,采用显式法建立各单元的通用生成函数（UGF）模型,分别采用现有方法和所提方法对单元独立失效与致命型概率及非致命型概率共因失效的计算结果进行对比。  结果  结果表明对概率共因失效假设具有正确性,提出的可靠度计算方法有效。  结论  相比传统的CCF分析法,采用PCCF分析法的可靠度计算结果准确度更高,能较好地解决单元和系统状态丢失的问题。     

边坡稳定性联合评价方法

借助MATLAB优化工具箱, 考虑土性参数变异性影响, 采用二次多项式序列响应面法求解边坡可靠指标和对应的安全系数, 并用可靠指标对应的失效概率对安全系数进行折减计算, 采用可靠指标与折减概率安全系数联合评价方法对边坡稳定性进行综合评价, 将计算结果和滑裂面图示与传统定值方法和二元指标方法的中值安全系数折减法进行对比分析。对比结果表明: 在土性参数变异性较大时, 即便传统定值方法计算出的安全系数明显大于1, 也会存在较大失稳风险; 但该方法利用失效概率对安全系数进行折减的过程, 实质是提取安全系数中可信部分的过程, 剔除了其中由于忽略不确定性因素而放大边坡稳定性的成分, 从而保证了评价结论的可靠性。     

随机动态交通网络可靠度分析与评价

为分析随机动态交通网络中出行者的旅行选择与停车行为, 利用网络均衡原理和不动点理论, 建立了供需相互作用下的不动点模型, 提出了计划可靠度和停车可靠度指标, 并对随机动态交通路网的可靠性进行了评价。发现停车设施的位置和步行距离对出行者的计划可靠度和停车可靠度水平影响较大, 停车费相当时, 出行者将优先选择距离目的地近的停车设施; 在早晨上班高峰期, 距离目的地较远的停车设施的停车可靠度较高。分析结果表明: 提出的可靠度指标能有效地衡量一天中不同时段道路网络和停车设施的服务水平。     

基于自适应变点的发动机性能退化预测

为有效利用监控大数据准确识别民机发动机性能的状态并预测其性能退化过程,针对民机发动机故障数据偏少且其性能退化过程呈现多阶段退化特性,提出了一种考虑民机发动机性能参数阶段不确定退化特性的可靠性评估模型;通过动态自适应窗宽改进了基于贝叶斯信息准则(BIC)的变点检测模型,利用改进自适应窗宽的BIC识别了自适应变点;根据识别出的自适应变点分阶段建立了不确定Liu过程的分布函数模型,结合民机发动机性能退化过程首达阈值的数学性质进行了可靠性评估,并通过对比民机发动机性能退化样本数据验证了模型的准确性和优越性。分析结果表明：利用改进自适应窗宽的BIC变点检测模型识别民机发动机性能退化过程的变点后,采用变点描述分阶段退化过程的均方误差为5.8×10^-28,在自适应窗宽具有不同变化规律的条件下,识别出的变点无明显变化,说明模型能够准确识别民机发动机性能退化过程的自适应变点,且具有较强的稳健性;利用阶段不确定Liu过程分析民机发动机性能参数的动态退化规律时,其平均评估误差比原Liu过程模型降低了约23.69%,得到的可靠性评估结果更加准确,且改进模型由于具有Lipschitz连续性,能够准确预测未来某段时间内民机发动机性能退化过程的可靠性水平。由此可见,建立的改进可靠性评估模型能够为实际工程中民机发动机的性能状态监控与健康管理应用提供理论方法。