基于BIM设计的道岔设备建模方法研究

为了解决站场BIM设计中道岔与岔线建模繁琐、定位捕捉困难等问题,基于最新的OpenRail软件环境,对MicroStation直接建模和道岔设备抽象化线性建模两种思路进行比较分析。经研究,线性建模方法更适合站场BIM设计。针对线性建模手段,将道岔的主要设备及尺寸信息转化为标准化道岔库元素和标记,然后按抽象化的道岔元素及标记信息进行xml文件编程,得到了较好的应用体验。     

船用蓄电池保养装置旋盖机构的建模和运动仿真

介绍使用Pro／E与ADAMS建立船用蓄电池保养装置中旋盖机构的虚拟样机方法,建立三维模型样机并进行了运动仿真分析。分析过程中使用参数化设计方法得到适合机构运动要求的零件参数,为旋盖机构和安装平台的整体设计提供了理论依据。     

雷达侦察信号环境描述与建模

信号环境仿真是检验雷达侦察设备性能的重要手段。针对雷达侦察信号环境时域、空域、频域、能域分布特点,对雷达侦察信号环境进行了数学描述,建立了雷达辐射源信号环境数学模型,为雷达侦察信号环境仿真奠定基础。     

形式化可测性约束在软件模型实现过程中的研究

在软件测试中,软件使用模型反映实际运行场景的能力是直接决定测试的成功与否的关键因素之一。一般可以通过对在需求分析阶段已生成的UML建模进行研究得到使用模型,但原始的UML模型,由于缺乏严格的定义及必要的约束,如果要生成高精度的软件模型,必须对其添加必要的形式化可测性约束。这正是文章研究的重点。     

舰船工程风险演变机理和建模分析

为增强舰船工程风险管理的针对性与有效性,研究了舰船工程风险的演变机理,讨论了舰船工程中的各种风险成分及其相互关系.通过定性分析表明,随着舰船工程阶段的推移,不仅总的风险度是逐渐降低的,而且各种风险成分占总风险的比例也是不断变化的.在此基础上又通过建立数学模型的方法给出了舰船工程风险的演变模型与函数关系,并通过举例给出了风险演变和转化的趋势,进一步验证了定性分析的正确性.本文的研究成果为舰船工程风险的管理提供了理论依据.     

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。     

基于ANSYS的350 km/h高速动车组用鼓形齿式联轴器的参数化建模

对350 km/h高速动车组用鼓形齿式联轴器的结构进行了分析,并采用ANSYS软件的APDL语言对其实现了参数化建模,大大方便了以后对该联轴器进行的相关分析,并且为复杂结构的建模提供了一个新的思路和方法.     

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.     

(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.     

Privacy protection method for fine-grained urban traffic modeling using mobile sensors

With the ubiquitous nature of mobile sensing technologies, privacy issues are becoming increasingly important, and need to be carefully addressed. Data needs for transportation modeling and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms that would simultaneously satisfy privacy protection and data needs for fine-grained urban traffic modeling applications using mobile sensors. To accomplish this, a virtual trip lines (VTLs) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed and tested to evaluate the effectiveness of such a privacy protection system by making privacy attacks. The results show that in addition to ensuring an acceptable level of privacy, the released datasets from the privacy-enhancing system can also be applied to urban traffic modeling with satisfactory results. Albeit application-specific, such a “Privacy-by-Design” approach would hopefully shed some light on other transportation applications using mobile sensors.