英语中关于音节划分规律的分析

本文分析了英语学习中正确划分音节的重要意义,由音节的历史发展阐明了现代英语中音节的确切定义和结构分类,并给出了音节划分的具体规律。这些规律是单词正确发音的关键。     

基于可靠度的斜坡软弱地基路堤稳定性极限平衡法分析

通常以确定性分析获得的稳定安全系数作为评价斜坡软弱地基路堤稳定性的指标,忽略实际工程中诸多不确定性因素,无法真实全面反映斜坡软弱地基路堤的稳定性。基于垂直条分极限平衡法Slide软件平台,运用全局最小可靠度分析方法,综合分析路堤和斜坡软弱层土体参数、地下水位、路堤顶部张拉裂缝水分充填量、微型桩纵向桩距和抗剪强度及水平向地震荷载等因素的变异性对斜坡软弱地基路堤稳定性的影响,讨论这些随机变量的敏感性,阐释了室内斜坡软弱地基路堤与水平软弱地基路堤土工离心模型试验现象差异性的机理。使用可靠度能更客观地反映斜坡软弱地基路堤的安全性;可根据各因素对斜坡软弱地基路堤稳定性影响敏感性的正负、强弱采取相应合理工程对策。     

基于蒙特卡洛法的抛锚撞击海管概率分析

针对船舶抛锚撞击海底管道事故频发,撞击概率计算过程较复杂且适用范围有限的问题,对现有方法进行改进,基于蒙特卡洛方法建立抛锚统计试验模型,对某一条件下船舶抛锚对海底管道的撞击概率进行计算,结果表明:对现有方法进行改进或利用蒙特卡洛方法能较好地反映船舶抛锚对海底管道的撞击概率变化特性,可应用于危险区域的抛锚预警和海上禁锚区的设置。     

基于故障树的HX_D3型电力机车牵引变流器可靠性设计

文章介绍了HXD3型电力机车牵引变流器的基本组成、主要部件的技术参数,按照故障树的结构对引起牵引变流器故障的原因进行了分析,将故障进行了分级,说明基础设计、例行试验和维护检查几方面进行全方位的可靠性设计方法。     

极端荷载作用下公路桥梁荷载概率模型研究

我国桥梁设计规范中对极端荷载组合系数没有明确的规定,在以结构可靠度为基础的概率极限状态设计法中,由于公路桥梁各种作用比较多且大多随时间变化的范围比较大,各种作用的组合也比较复杂,所以必须选择合理的概率模型才能保证计算出真实合理的结构可靠度。通过查阅文献并结合WIM系统统计的车辆数据分析,建立了公路桥梁永久荷载及其效应概率分布模型;基于Matlab软件,在汽车车重总体服从多峰分布的基础上对实测数据进行训练拟合,建立了汽车荷载效应的概率模型并确定了汽车荷载分级加载方式,为公路桥梁可靠度研究和求解极端荷载组合系数奠定了基础。     

应用交通仿真软件PARAMICS验证交通分配模型

为了考察交通分配模型能够在多大程度上反映现实的交通状况，需要对交通分配模型进行验证，本文阐述了利用微观交通仿软件PARAMICS对交通分配模型进行验证的研究思路。通过建模工具Modeller提供的图形界面，研究者不但能够非常直观地观察交通分配模型的效果，而且可以利用其分析工具Analyser对结果全面分析。因此RARAMICS是一个验证交通分配模型性能优良的平台。     

Development and calibration of a long-distance passenger traffic assignment model

This paper studies the assignment of long-distance passenger traffic on a highway corridor network. First, we propose a traditional model for the long-distance traffic assignment considering interactions with local commuter traffic. It addresses the effect of local networks on highway corridors. An iterative algorithm is developed to solve for the exact solution. Then, to address the potential computational issues that arise therein, a decomposition method is proposed by introducing a new concept of corridor elasticity. An assignment procedure for long-distance passenger traffic is developed accordingly. Numerical tests show that the proposed decomposition method makes significant improvements in computational performance at a small loss of optimality. This decomposition method well approximates the exact assignment from the traditional formulation, especially when the highway corridors are near-saturation. The proposed decomposition method appears practical for application.     

Tradable network permits: A new scheme for the most efficient use of network capacity

Akamatsu et al. (2006) proposed a new transportation demand management scheme called “tradable bottleneck permits” (TBP), and proved its efficiency properties for a single bottleneck model. This paper explores the properties of a TBP system for general networks. An equilibrium model is first constructed to describe the states under the TBP system with a single OD pair. It is proved that equilibrium resource allocation is efficient in the sense that the total transportation cost in a network is minimized. It is also shown that the “self-financing principle” holds for the TBP system. Furthermore, theoretical relationships between TBP and congestion pricing (CP) are discussed. It is demonstrated that TBP has definite advantages over CP when demand information is not perfect, whereas both TBP and CP are equivalent for the perfect information case. Finally, it is shown that the efficiency result also holds for more general demand conditions.     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.     

Integrated airline planning: Robust update of scheduling and fleet balancing under demand uncertainty

The airline schedule planning problem is defined as the sequence of decisions that need to be made to obtain a fully operational flight schedule. Historically, the airline scheduling problem has been sequentially solved. However, there have already been many attempts in order to obtain airline schedules in an integrated way. But due to tractability issues it is nowadays impossible to determine a fully operative and optimal schedule with an integrated model which accounts for all the key airline related aspects such as competitive effects, stochastic demand figures and uncertain operating conditions. Airlines usually develop base schedules, which are obtained much time in advance to the day of operations and not accounting for all the related uncertainty. This paper proposes a mathematical model in order to update base schedules in terms of timetable and fleet assignments while considering stochastic demand figures and uncertain operating conditions, and where robust itineraries are introduced in order to ameliorate miss-connected passengers. The proposed model leads to a large-scale problem which is difficult to be solved. Therefore, a novel improved and accelerated Benders decomposition approach is proposed. The analytical work is supported with case studies involving the Spanish legacy airline, IBERIA. The presented approach shows that the number of miss-connected passengers may be reduced when robust planning is applied.