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。     

冰载荷下的船舶运动建模

随着极地航道的开辟以及极地海洋能源开发的需要,海冰与船体的相互作用以及极地船舶航行与作业安全越来越受到关注。本文主要针对破冰过程的几个典型阶段,对冰载荷对船舶的作用力进行了分析与计算,并考察了破冰船在不同的海冰密集度、冰厚以及船舶不同航速情况下的不同影响。     

基于粗糙-模糊软计算的船板线加热成形加工参数预报方法

提出一种基于粗糙-模糊软计算的建模方法,构造一种基于贴近方向修正的高精度模糊推理算法,通过有限元分析(FEA)建立板材线加热成形工艺信息系统,根据粗糙集软计算获取线加热成形的工艺规律,运用模糊推理实现加工参数的快速准确预报。粗糙-模糊建模适用于线加热成形过程的静态或动态模型的构建,为实现该工艺的智能建模与控制提供一种新的技术手段。     

Daily activity and travel sequences of students,faculty and staff at a large Canadian university

This paper examines the activity engagement, sequencing and timing of activities for student, faculty and staff commuter groups at the largest university in the Maritime Provinces of Canada. The daily activity patterns of all university community groups are modeled using the classification and regression tree classifier algorithm. The data used for this study are derived from the Environmentally Aware Travel Diary Survey (EnACT) conducted in spring 2016 at Dalhousie University, Nova Scotia. Results show that there are significant differences in activity and travel behavior between university population segments and the general population in the region, and between campus groups. For example, students participate in more recreation activities compared to faculty and staff. They also take more trips to and from campus, and are more flexible in their scheduling of trips. The insights gained from this study will provide helpful information for promoting sustainability across university campuses, and for development of campus-based travel demand management strategies.     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.