基于ADAMS和AMESim软件的舰艇某装置启闭建模及优化

采用液压系统驱动的舰艇某装置在完全开启时, 其盖板会与止挡板发生碰撞,并产生较大噪声。针对此问题,采用ADAMS和AMESim软件建立了该装置的参数化启闭模型,计算了其盖板在开启时与止挡板发生碰撞所受到的冲击加速度和冲击力,并与试验结果进行对比,验证了模型的准确性。在此基础上,以实现开启时该舰艇装置所受到的冲击加速度和冲击力最小化为目标,对其液压系统进行了优化设计。结果表明：该方法可明显降低该装置在开启时所受到的冲击加速度和冲击力。

     

小型船用PEM燃料电池仿真特性分析

随着能源的逐渐枯竭和环境污染的持续加重,燃料电池的发展越来越受到世界各国的重视,燃料电池具有高效、清洁和环保等特点,特别是质子交换膜(PEM)燃料电池已经得到了广泛的应用。文章基于Matlab/Simulink软件平台,建立PEM燃料电池动态模型,以输入信号源作为外加负载,分析了随负载电流变化时,电池工作温度变化和阴阳极进气压力对PEM燃料电池输出电压和输出功率的影响。仿真结果与实际燃料电池特性曲线基本一致,所搭建的动态模型也能较好的反映PEM燃料电池的动态特性。     

基于EHPN的A-SMGCS机场滑行道运行控制建模

针对先进机场场面引导与控制系统(A-SMGCS)中滑行道运行控制建模, 提出一种基于扩展层次Petri网(EHPN)的建模方法。将滑行道分为交叉口和直线段模块, 然后对模块内部的航空器行为进行封装, 形成基于扩展Petri网的过程层通用模块, 并进一步采用同步合成技术建立过程层模型。利用面向Agent的着色赋时Petri网建立决策层通用模块, 同时将场面运行控制知识与模块的库所和变迁集成, 增强模型的智能决策能力。采用某机场12 h滑行道运行数据进行了仿真试验。研究结果表明: 基于EHPN模型的仿真, 其直线段和交叉口冲突次数分别为6次和11次, 滑行道系统总延误为346 s, 与SIMMOD仿真模型效果相近, 因此, 该建模方法有效。     

公路风吹雪灾害缓解技术研究

针对公路风吹雪灾害危害现状,提出风吹雪雪害防治“标本兼治、以本为主”的原则。采取多种形式,特别是研究并利用挡雪墙这一工程措施治理风吹雪灾害,为公路建设、养护、管理提供技术支持与保障。     

高速公路动态交通流Elman神经网络模型

为了提高高速公路交通流建模的精度, 分析了离散的高速公路动态交通流数学模型, 基于Elman网络原理, 建立了回归神经网络交通流模型。回归神经网络的输入层、上下文层、隐含层和输出层的节点数目分别选为8、30、30和2, 采用Levenberg-Marquardt算法对回归神经网络进行训练, 并对一条5路段的高速公路进行仿真。结果表明: 回归神经网络平均相对误差为8.683 7×10^-5, 最大相对误差为4.237 1×10^-4, 与BP神经网络和RBF神经网络相比较, Elman回归神经网络能更好地逼近交通流数学模型, 真实地描述交通流基本特性, 能准确地建立动态交通流模型, 适应交通状况的变化。     

(Unintended) Transport impacts of an energy-environment policy: The case of CNG conversion of vehicles in Dhaka

Motor vehicles are one of the major sources of air pollution in Dhaka, the capital of Bangladesh. The government took various policies to convert the petroleum vehicles on road to run on compressed natural gas (CNG), which allows both air quality improvements and energy security benefits. One of the market friendly policies to encourage the fuel switch was to increase the price differential between CNG and petrol and diesel. This has allowed a wide-scale adoption of CNG as the fuel of choice. However, several years into the policy, there is now a widespread belief among the policymakers that the CNG conversion may have increased car ownership and car travel due to their lower running costs, resulting in more congestion and a reversal of the strategy is on the cards. It is therefore important to test the hypothesis whether CNG conversion had genuinely increased car ownership and car travel in Dhaka city. This paper presents the results of a questionnaire survey and an econometric intervention analysis to understand the impact of CNG conversion on car ownership and car travel in Dhaka. Attention is also given to disentangle the self-selection and price-induced travel effects of CNG conversion. Results show that ownership did not increase, but travel of on-road vehicles increased due to the CNG policy. However, additional congestion costs are still around one half of the health benefits brought about by the policy.     

Within day rescheduling microsimulation combined with macrosimulated traffic

The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Mathematical properties and constraints representation for bottom-up approaches to the evaluation of GHG mitigation policies

Bottom-up models, including MARKAL, MESSAGE and AIM, are widely used when analyzing the effect of greenhouse gas (GHG) abatement policies. These bottom-up models are mostly formulated as a linear programming (LP) optimization model to find both the minimal cost combination of abatement technologies and energy flows while satisfying demands. It is not unusual that the bottom-up modeling involves a great number of technical, industrial, socioeconomic and environmental constraints. Investigating representative constraints needed for analyzing GHG abatement policies, this study proposes how to implement these constraints in bottom-up modeling.     

A survey on planning semi-flexible transit systems: Methodological issues and a unifying framework

When demand for transportation is low or sparse, traditional transit cannot provide efficient and good-quality service, due to its fixed structure. New transportation alternatives are therefore increasingly proposed, combining on-demand service adjustment capabilities to the regular route and schedule characteristics of traditional transit. Such so-called semi-flexible systems require careful planning, but no formalization of the corresponding decisions problems, nor any comprehensive methodology has been proposed yet. This paper aims at contributing to fill this gap by presenting a comprehensive literature review, and a general and unifying modeling framework for representing and planning semi-flexible systems. The latter takes the form of the Demand Adaptive Systems, which generalizes the semi-flexible systems described in the literature, and also offers a number of advanced features, the scheduling mechanism, in particular. The paper then provides a classification of planning decisions, which is used to structure a comprehensive and comparative literature review of the field of semi-flexible systems, including methodological contributions as well as a number of particularly significant practical experiences.