基于多代理机制的列车运行调整模型及算法动态集成研究

分析列车运行调整问题研究的现状与进展,主要集中在模型研究和算法研究两个方面。分析传统求解模型及算法研究的局限性,提出对现有模型及算法进行动态集成的研究思路。采用基于多代理机制的动态集成方法,将模型对象和算法对象转化成多个代理,定义多代理之间的交互策略,实现调整方法的动态集成。提出基于多代理机制的列车运行调整问题模型及算法的动态集成系统。     

大跨度钢箱梁斜拉桥索梁锚固区传力机理

结合南京长江二桥、安庆长江大桥、苏通长江大桥索梁锚固区足尺模型疲劳试验及有限元分析,研究索梁锚固区的传力机理及应力分布。研究表明,由斜拉索传来的巨大压力,通过锚箱底板、承压板与腹板的连接焊缝,以剪力的形式传递到钢箱梁腹板上;锚箱与主梁腹板焊缝处的应力从上到下逐渐增大,在下端达到最大值,承压板上的应力稍小,均满足强度要求;经200万次和400万次(苏通大桥)疲劳加载,均未发现有裂纹发生,应力均无大的变化。验证了设计的正确性和制造工艺的可行性。     

西部某高速公路土石混合路堤离心模型试验研究

离心模型试验由于可直观的模拟自重应力场,在工程建设中起到越来越重要的作用。文章结合西部交通建设科技项目和某高速公路工程建设,利用离心模型试验研究了土石混合路堤在不同设计干密度和含水量条件下的沉降变形特征。     

管幕内顶进箱涵时顶部管幕力学作用的试验研究

上海市中环线虹许路北虹路下立交工程是目前世界上在饱和含水软土地层中施工的横截面最大的管幕法工程。为了充分研究箱涵顶进过程中管幕的力学作用,根据相似理论,按照实际工程状况进行了室内模型试验,得到了箱涵推进过程中地面和顶部管幕的竖向位移,以及管幕下土压力的变化特征,发现箱涵前端一定范围内的地层主要表现为竖向沉降变形,顶部管幕在箱涵推进过程中起到一定的承载作用,这对于稳定箱涵前端开挖面是有利的。试验结果对实际工程的设计与施工提供了一定的参考。     

列车运行调整模型的研究

铁路分局调度辅助决策系统是一个基干网络运行的管理信息系统,由若干个子系统构成,其中最重要的是行车调度台子系统.该子系统可以分成三个部分,分别是数据管理、列车调整指挥和调度信息处理.而列车运行调整是行车调度台子系统最重要的功能,论文着重分析了已有调整算法的特点和现场实际需求,阐述了新的列车运行调整模型的工作原理及其特点.     

E-R模型特殊超类/子类结构转换方法研究

分析了该系统的概念结构中出现的特殊超类/子类结构,即:超类实体对不同的子类实体具有不同的主码,其主属性仅仅是所有子类实体共同的主属性,各子类实体拥有各自特定的主属性.     

DCOM及其在分布式系统中的应用

Microsoft的分布式组件对象模型技术(DCOM)扩展了组件对象模型技术(COM),使其能够支持在局域网、广域网甚至Internet上不同计算机对象之间的通讯.使用DCOM的应用程序就可以在位置上达到分布性,从而满足客户和应用的需求.     

Road traffic conditions in Kenya: Exploring the policies and traffic cultures from unstructured user-generated data using NLP

Road traffic accidents (RTA) are a prevalent cause of fatality with African countries having the highest fatality index (25–34 per quota). The World Health Organization estimates Kenya's fatality rate due to RTA at 28 per quota. From literature, the country's fatality and injuries have increased by 26% and 46.5%, respectively, since the year 2015. The country is faced with incomplete RTA data capturing, hindering effective planning and policy adjustments to curb the menace. In this paper, we scrapped user-generated data (Twitter) and national transport and safety authority's (NTSA) reports to shed light on traffic safety, practices, and cultures in the country. To this end, we gathered 1,000,000 tweets and 8000 speeding entries between 2015 and 2021 and performed natural language processing (NLP) and quantitative study of the data. We applied NLP and n-gram search of keywords to categorize data into 8 topics: traffic, public service vehicle (PSVs), policing, accident, infrastructure, recklessness, robbery, and corruption. From the data, policing, which touches on all police and law-enforcement-related activity was found to be highly correlated with PSVs, recklessness, accidents, traffic congestion, robbery, infrastructure, and corruption with indices of r(76) = 0.92, 0. 91, 0.87, 0.82, 0.81, 0.76, and 0.70, respectively with p < 0.001. The topic modeling confirmed the identified topics to be the latent discussion issues affecting the public. From the study, PSVs, policing and traffic flow were isolated as key issues that ought to be addressed immediately. The research recommended the integration of driver monitoring systems to strengthen policing. The research, which utilized unstructured data, points to the utility of data mining which would greatly benefit traffic research, particularly African-based studies, that suffer from data inadequacy.     

汽车驱动桥半轴室内试验强化系数模型研究

依据材料疲劳损伤累积理论对汽车驱动桥半轴的疲劳寿命进行预估,结合随机载荷谱处理技术给出了室内试验强化系数的理论模型,研制了汽车驱动桥室内强化试验系统,并对某公司5 t ZL50DWB装载机车桥等多个产品进行了试验。分析表明理论模型和试验数据吻合较好。     

Multi-level condition-based maintenance planning for railway infrastructures – A scenario-based chance-constrained approach

This paper develops a multi-level decision making approach for the optimal planning of maintenance operations of railway infrastructures, which are composed of multiple components divided into basic units for maintenance. Scenario-based chance-constrained Model Predictive Control (MPC) is used at the high level to determine an optimal long-term component-wise intervention plan for a railway infrastructure, and the Time Instant Optimization (TIO) approach is applied to transform the MPC optimization problem with both continuous and integer decision variables into a nonlinear continuous optimization problem. The middle-level problem determines the allocation of time slots for the maintenance interventions suggested at the high level to optimize the trade-off between traffic disruption and the setup cost of maintenance slots. Based on the high-level intervention plan, the low-level problem determines the optimal clustering of the basic units to be treated by a maintenance agent, subject to the time limit imposed by the maintenance slots. The proposed approach is applied to the optimal treatment of squats, with real data from the Eindhoven-Weert line in the Dutch railway network.