基于多时间尺度的城市轨道交通短时OD估计

基于状态空间模型构建了城市轨道交通短时OD估计的多模型组合方法,估计早晚高峰期间15 min内进站客流的去向目的站.组合模型以不同时间尺度下的进站客流分流率为状态变量,并利用历史数据预估其中通勤客流的分流率,然后通过交互多模型算法加权融合不同时间尺度下的分流率估计结果.以北京地铁为案例,研究表明:早高峰期间的15 min分流率估计误差的平均值和最大值分别为16.4%和21.8%,晚高峰期间分别为22.7%和24.6%,比既有文献的估计误差减小了约一半.本文的研究成果可为实时的线网客流分布预测提供更准确的输入数据,以辅助运营管理部门实现客流预警和应急响应.     

两种单相桥式整流电路的比较研究

研究了单相桥式全控和不控两种整流电路,首先分析了单相桥式全控整流电路带反电动势电路的工作原理,然后分析了单相桥式不控整流电路带电容滤波的工作原理,最后在Matlab/Simulink中对两种电路进行了建模和仿真,通过对仿真结果的比较分析得出两种整流电路的负载电压都不会出现为零的情况。     

浅析内河航道节能现状及技术应用

内河航道在施工建设和运营管理期间会产生大量的能源消耗,抓好航道的节能减排对发展绿色交通具有重要作用。本文总结概况了目前我国内河航道节能减排现状及采用的关键技术,相关技术的推广将引导交通运输行业优化用能结构、促进产业协调发展。     

铺缆船用电缆埋设犁土壤挖掘阻力计算

传统的计算埋设犁土壤挖掘阻力的方法一般采用经验公式计算。经验公式依赖丰富的试验数据，且只能适应特定形状和尺寸的埋设犁。由于埋设犁的形状和尺寸各不相同，基于经验公式计算土壤挖掘阻力的方法准确性不高。根据土力学基本原理，在力学分析的基础上，运用数学方法进行公式推导，得到用于计算不同形状尺寸埋设犁挖掘阻力的理论方法，解决依赖经验公式计算土壤挖掘阻力的局限性。     

LNG码头应急通道与应急锚地研究

本文针对LNG应急逃离情况以及国内LNG应急锚地使用现状,总结分析国内、外LNG应急锚地布置情况;结合江苏滨海LNG码头通航条件,提出LNG应急通道及应急锚地三种布置方案,通过操船模拟试验论证比选并得出结论,供类似工程参考。     

不同空间结构的有轨电车超级电容热行为

为了减轻有轨电车超级电容模组因温度引起的性能衰减，基于超级电容器的单体结构，研究单体不同空间结构对超级电容模组热行为的影响. 首先，建立超级电容电化学-热耦合模型，并搭建实验平台验证模型的有效性；其次，定义“自然对流换热比表面积”，通过最高温度、最大温差、单体温度波动率和空间利用率4个指标对截面为3 × 6、2 × 9的长方体结构、截面为4 × 4的正方体结构和六面体结构的超级电容模组的温度特性和体积特征进行评估. 研究表明:气流路径的长度、对流换热比表面积以及强制对流换热的单体数量会影响散热的效果，具有短而宽流动路径的空间结构冷却效果更好；正方体结构是冷却效果和均温方面的最优选择；对于空间利用率和冷却效率而言，六面体结构是最佳选择.      

The value of options for time charterparty extension: an artificial neural networks (ANN) approach

The most frequently associated options in the physical shipping market are options to extend the charter period on time charters and additional shipment options on contracts of affreightment. The value of freight options, in practice, is estimated mostly by referring to forward curves. An option on freight has different properties from its financial counterparts, and the straightforward adoption of theoretical models does not produce promising results. In this paper, extension options, which have the property of options on futures, were transformed into regular European options before the application of the Black-Scholes model (BSM). The efficient market hypothesis, which justifies the parity of the performance of a long-term charter to that of repetitive short-term charters, worked as the basis for the transformation. The option values determined by the BSM were compared with actual realized values. Additionally, the artificial neural networks (ANN) was employed to derive the option values. This study is meaningful as the first-time application of both the closed-form solution and the ANN to the valuation of physical freight options. The research results can contribute to the quality of chartering decisions. The results could also be used in quantifying credit risk, as extension options tend to be granted to charterers with more creditability.     

Reliability Modeling and Maintenance Policy Optimization for Deteriorating System Under Random Shock

Performance degradation and random shock are commonly regarded as two dependent competing risks for system failures. One method based on effective service age is proposed to jointly model the cumulative effect of random shock and system degradation, and the reliability model of degradation system under Nonhomogeneous Poisson processes (NHPP) shocks is derived. Under the assumption that preventive maintenance (PM) is imperfective and the corrective maintenance (CM) is minimal repair, one maintenance policy which combines PM and CM is presented. Moreover, the two decision variables, PM interval and the number of PMs before replacement, are determined by a multi-objective maintenance optimization method which simultaneously maximizes the system availability and minimizes the system long-run expect cost rate. Finally, the performance of the proposed maintenance optimization policy is demonstrated via a numerical example.     

Occupant injury risk analysis at NASS/CDS database

Injury information for vehicle occupants from the body regions of the head, thorax, abdomen, and upper and lower extremities, due to the restraints and interior parts of the vehicle, were extracted from the 2009 ~ 2012 NASS/CDS database. For those cases with high occurrence frequency, a detailed and comprehensive data analysis was performed to find the relationship between the accident, occupant, vehicle, and injury data. A numerical frontal impact sled model with the Hybrid III dummy and the GHBMC human body model was constructed to simulate and identify those injury risks according to NASS/CDS. Among the 5,734 injuries to the aforementioned body regions from frontal crashes are, listed by frequency of occurrence, the lower extremity (27.8 %), upper extremity (21.3 %), thorax (15.1 %), face (10.9 %), spine (8.7 %), head (7.3 %), and abdomen (6.9 %). The main injury sources to the head were the windshield, side structure, and steering wheel. For the thorax and abdomen they were the seat belt and steering wheel. For the lower extremity it was the instrument panel. The main injury patterns for the head were the concussion and the contusion. For the thorax they were vessel laceration and lung contusion. For the abdomen they were laceration and contusion of the organs. For the lower extremity they were bone fracture and ligament rupture. The steering wheel and seat positions were main factors affecting head and thorax injury risks. From the sled impact simulation, high injury risks of the head and thorax were assessed respectively at conditions of steering column tilt down and rear most seat position, which correlated well with the findings from the NASS/CDS data analysis.     

Approximate optimal AUTOSAR software components deploying approach for automotive E/E system

The AUTOSAR has been developed as the worldwide standard for automotive E/E software systems, making the electronic components of different suppliers to be employed universally. However, as the number of component-based applications in modern automotive embedded systems grows rapidly and the hardware topology becomes increasingly complex, deploying such large number of components in automotive distributed system in manual way is over-dependent on experience of engineers which in turn is time consuming. Furthermore, the resource limitation and scheduling analysis make the problems more complex for developers to find out an approximate optimal deploying approach in system integration. In this paper, we propose a novel method to deploy the AUTOSAR components onto ECUs with the following features. First, a clustering algorithm is designed for deploying components automatically within relatively low time complexity. Second, a fitness function is designed to balance the ECUs load. The goal of our approach is to minimize the communication cost over all the runnable entities while meeting all corresponding timing constraints and balancing all the ECUs load. The experiment results show that our approach is efficient and has well performance by comparing with other existing methods in specific and synthetic data set.