三维复杂弹性耦合冲击隔离系统建模研究

针对带弹性筏体和弹性基础的三维复杂弹性耦合冲击隔离系统,综合运用多体动力学理论、结构动力学理论、子结构方法、有限元方法,考虑系统刚体运动与弹性振动的耦合,建立了三维复杂弹性耦合冲击隔离系统的动力学模型;编写计算程序计算系统的固有频率,并与用ANSYS软件建模计算的固有频率和实验值进行比较,结果吻合得较好,通过试验工况下计算的机组加速度响应与实测结果的比较,验证了模型的正确性;最后计算分析系统在三向冲击激励下的动力学响应,为分析浮筏系统的冲击响应控制和参数优化奠定理论基础。     

基于理性推理的观点演化模型

针对现实生活中个体观点形成中的理性推理过程,提出了一种基于DS（Dempster-Shafer）证据理论的观点更新规则,并在连续观点离散决策的框架下,对个体如何利用其他个体的意见和相关知识来形成自身意见的过程进行建模.实验仿真结果表明,群体中能够出现观点一致、分散等常见的舆论现象,观点演化过程中伴随着知识由确定性个体向不确定性个体的扩散,同时发现在规则网络中,意见领袖的观点的影响力在扩散过程中是逐渐减弱的,其影响范围与个体对知识不确定性的接受程度密切相关.     

动车组运营速度由350km/h提升至400km/h可行性研究

为了进一步提升人们乘坐高铁的出行体验和服务质量,提高运输组织效率,降低运营成本,中车长春轨道客车股份有限司拟研发400 km/h高速动车组。文章结合我国科技部"先进轨道交通"重点专项"时速400公里及以上高速客运装备关键技术"项目研究成果,主要从运行能力、安全性、舒适性、经济性等角度着重探讨动车组运营速度由350 km/h提升至400 km/h的可行性。     

基于系统动力学的铁路固体污染量仿真分析

基于对铁路固体污染的分析,本文运用系统动力学的原理,建立固体污染系统模型,在流图分析的基础上,采用DYNAMO语言进行仿真.通过反复实验,使固体污染量与历史数据一致来确定调控参数,进行了动态仿真并预测了铁路固体污染量.依据研究结果,对铁路固体污染的治理提出了建议.     

某型舰炮弹炮耦合问题初探

针对某型舰炮运用ADAMS软件建立了该型舰炮的弹炮耦合动力学模型。在此模型基础上,分析了该型舰炮发射时,弹炮耦合对弹丸初速的影响和计及弹丸作用时对身管后坐的影响。     

短肢剪力墙结构力学性能分析

在分析整体小开口剪力墙结构、壁式框架结构和联肢剪力墙结构受力特点的基础上,提出了一种合理的短肢剪力墙结构形式,既克服了整体小开口剪力墙结构和传统联肢剪力墙墙肢净距受限的缺点,又克服了壁式框架结构连梁刚度过高的不足,同时短肢剪力墙还具有较佳的弹性力学性能．     

散装水泥运输罐车刹车过程物料流动特性研究

为探索散装水泥运输半挂车在刹车过程罐内物料的流动特性,基于FLUENT计算流体力学软件,采用欧拉-欧拉方法建立双流体模型,通过Syamlal-O＇Brien模型描述气-固曳力,对散装水泥运输半挂车在刹车过程罐内水泥的流动特性进行了数值模拟。结果表明,散装水泥运输半挂车在刹车过程中,罐内水泥向前运动,牵引车载荷高于设计载荷,对此提出通过在罐内顶部增设阻流板,可有效避免散装水泥运输半挂车在刹车过程由于载荷分布不合理而引起的一系列问题的改进措施。     

土石堆积体精细化模型构建及力学特性数值试验

土石堆积体具有较强的非均质性,其力学破坏特性受内部块石的细部特征影响较大.依托罗打拉堆积体隧道,借助数字图像处理与块石随机投放技术实现了对土石堆积体精细化数值模型的构建,采用大型三轴试验验证模型的正确性,并深入探讨土石堆积体力学破坏的特征及规律.研究结果表明:该方法获得的力学参数及应力应变曲线与三轴试验结果差异不大;在...     

A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities

This paper presents a hybrid simulation-assignment modeling framework for studying crowd dynamics in large-scale pedestrian facilities. The proposed modeling framework judiciously manages the trade-off between ability to accurately capture congestion phenomena resulting from the pedestrians’ collective behavior and scalability to model large facilities. We present a novel modeling framework that integrates a dynamic simulation-assignment logic with a hybrid (two-layer or bi-resolution) representation of the facility. The top layer consists of a network representation of the facility, which enables modeling the pedestrians’ route planning decisions while performing their activities. The bottom layer consists of a high resolution Cellular Automata (CA) system for all open spaces, which enables modeling the pedestrians’ local maneuvers and movement decisions at a high level of detail. The model is applied to simulate the crowd dynamics in the ground floor of Al-Haram Al-Sharif Mosque in the City of Mecca, Saudi Arabia during the pilgrimage season. The analysis illustrates the model’s capability in accurately representing the observed congestion phenomena in the facility.     

Assessing energy consumption impacts of traffic shifts based on real-world driving data

Information and communication technologies used for on-board vehicle monitoring have been adopted as an additional tool to characterize mobility flows. Furthermore, traffic volumes are traditionally measured to understand cities traffic dynamics. This paper presents an innovative methodology that uses an extensive and complementary real-world dataset to make a scenario-based analysis allowing assessing energy consumption impacts of shifting traffic from peak to off-peak hours. In the specific case of the city of Lisbon, a sample of 40 drivers was monitored for a period of six months. The obtained data allowed testing the impacts of increasing the percentage of traffic shifting from peak to off-peak hours in energy consumption. Both average speed and energy consumption variations were quantified for each of the tested percentages, allowing concluding that for traffic shifts of up to 30% a positive impact in consumption can be observed. In terms of potential gains associated to shifting traffic from peak hours, reductions in energy consumption from 0.1% to 0.4% can be obtained for traffic volumes shifts from 5 to 30%. Overall, the maximum reduction in energy consumption is achieved for a 20% traffic shift. Average speed variation follows the same trend as energy consumption, but in the opposite direction, i.e. instead of decreasing, average speed increases. For the best case scenario, considering only the sections of roads with traffic sensors, a 1.4% reduction in trip time may be achieved, as well as savings of up to 6 l of fuel and 14.5 kg of avoided CO₂ emissions per day.