基于不规则三角网的视相关细节层次网格化方法研究

多分辨率三角形网格表示对于实时渲染复杂的几何场景来说是一个重要的工具。本文对交互可视复杂的三角形网格提出了有效的视相关网格化的框架,介绍了涉及视锥、表面方向和屏幕投影误差的视相关网格化准则,给出了基于边的数据结构和构建元操作层次结构的方法,同时根据这些准则发展了渐进细化和简化网格的实时算法。提出的视相关网格化方法具有较高的时间效率。     

基于山区复杂路段下的车辆主动限速控制系统研究

山区复杂路段交通事故频发,行车安全问题亟待解决,因此研究该路段下的主动限速控制技术具有重要意义。本文阐述了主动限速控制系统的原理与构成,并且对车辆的运行安全车速进行了分析与建模,提出了主动限速的控制策略。最后通过对该系统软硬件进行了调试,初步验证了其可行性比较合理,能够指导驾驶人的行车安全。     

基于模型系统工程在全舰计算环境集成框架的应用概览

“全舰计算环境”（TSCE）作为当今软件密集型复杂武器系统的典型代表,需要从研制模式上转变传统的系统工程实践,采用基于模型的系统工程（MBSE）解决方案,从以文档为中心转变为以模型为中心,实现系统的快速开发以应对需求和环境的变化。首先,介绍MBSE的发展概况及国内外相关研究情况,然后,结合TSCE集成框架并参考经典的V模型,梳理系统工程过程,初步建立各个阶段与美国国防部体系结构框架（DoDAF）视点或模型的对应关系。重点讨论为了得到合适的TSCE系统模型应该采用的建模规范和标准,主要包括：系统建模语言（SysML）、可扩展标记语言（XML）模式、面向服务架构（SOA）、业务流程模型与标注（BPMN）、军事想定定义语言（MSDL）、联合作战管理语言（C-BML）等。形式化建模方法的应用预期将在构建TSCE集成框架的过程中发挥重要作用。     

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。     

(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.