Spatial Interaction and Network Structure Evolvement of Cities in Terms of China's Rail Passenger Flows

Cities separated in space are connected together by spatial interaction (SI) between them. But the studies focusing on the SI are relatively few in China mainly because of the scarcity of data. This paper deals with the SI in terms of rail passenger flows, which is an important aspect of the network structure of urban agglomeration. By using a data set consisting of rail O-D (origin-destination) passenger flows among nearly 200 cities, intercity rail distance O-D matrixes, and some other indices, it is found that the attenuating tendency of rail passenger is obvious. And by the analysis on dominant flows and spatial structure of flows, we find that passenger flows have a trend of polarizing to hubs while the linkages between hubs upgrade. However, the gravity model reveals an overall picture of convergence process over time which is not in our expectation of integration process in the framework of globalization and economic integration. Some driven factors for the re-organization process of the structure of urban agglomeration, such as technique advance, globalization, etc. are discussed further based on the results we obtained.

Patient-Specific Echo-Based Fluid-Structure Interaction Modeling Study of Blood Flow in the Left Ventricle with Infarction and Hypertension

Understanding cardiac blood flow behaviors is of importance for cardiovascular research and clinical assessment of ventricle functions.Patient-specific Echo-based left ventricle(LV)fluid-structure interaction(FSI)models were introduced to perform ventricle mechanical analysis,investigate flow behaviors,and evaluate the impact of myocardial infarction(MI)and hypertension on blood flow in the LV.Echo image data were acquired from 3 patients with consent obtained:one healthy volunteer(P1),one hypertension patient(P2),and one patient who had an inferior and posterior myocardial infarction(P3).The nonlinear Mooney-Rivlin model was used for ventricle tissue with material parameter values chosen to match echo-measure LV volume data.Using the healthy case as baseline,LV with MI had lower peak flow velocity(30%lower at beginejection)and hypertension LV had higher peak flow velocity(16%higher at begin-filling).The vortex area(defined as the area with vorticity>0)for P3 was 19%smaller than that of P1.The vortex area for P2 was 12%smaller than that of P1.At peak of filling,the maximum flow shear stress(FSS)for P2 and P3 were 390%higher and 63%lower than that of P1,respectively.Meanwhile,LV stress and strain of P2 were 41%and 15%higher than those of P1,respectively.LV stress and strain of P3 were 36%and 42%lower than those of P1,respectively.In conclusion,FSI models could provide both flow and structural stress/strain information which would serve as the base for further cardiovascular investigations related to disease initiation,progression,and treatment strategy selections.Large-scale studies are needed to validate our findings.

CFD Analysis of Ship-to-Ship Hydrodynamic Interaction

A numerical study of ship-to-ship interaction forces is performed using a commercial CFD code,and the results are compared with experimental data and with the results of a panel method analysis.Two ship models have been used in the interaction forces analysis:a tug and a tanker,advancing parallel to each other with different lateral distances and two different values of the fluid depth.Computations are carried out with four different flow models:inviscid and viscous flow with the free surface modeled as a rigid wall and inviscid and viscous flow with the deformable free surface.A fair agreement was obtained with available experimental data and results obtained by panel method.The influence of viscosity in the computations is found to be comparatively weak,while the wavemaking effects may be important,at small magnitude of the horizontal clearance.

Numerical Investigation on Dynamic Response Characteristics of Fluid-Structure Interaction of Gas-Liquid Two-Phase Flow in Horizontal Pipe

Fluid-structure interaction(FSI)of gas-liquid two-phase fow in the horizontal pipe is investigated numerically in the present study.The volume of fluid model and standard k-e turbulence model are integrated to simulate the typical gas-liquid two-phase fow patterns.First,validation of the numerical model is conducted and the typical fow patterns are consistent with the Baker chart.Then,the FSI framework is established to investigate the dynamic responses of the interaction between the horizontal pipe and gas-liquid two-phase fow.The results show that the dynamic response under stratified fow condition is relatively flat and the maximum pipe deformation and equivalent stress are 1.8 mm and 7.5 MPa respectively.Meanwhile,the dynamic responses induced by slug fow,wave fow and annular fow show obvious periodic fuctuations.Furthermore,the dynamic response characteristics under slug flow condition are maximum;the maximum pipe deformation and equivalent stress can reach 4mm and 17.5 MPa,respectively.The principal direction of total deformation is different under various flow patterns.Therefore,the periodic equivalent stress will form the cyclic impact on the pipe wall and affect the fatigue life of the horizontal pipe.The present study may serve as a reference for FSI simulation under gas-liquid two-phase transport conditions.

基于动态图神经常微分方程的地铁短时客流预测方法

随着城市轨道交通的快速发展,客流量的准确预测对于改善运营服务至关重要。为了解决当前地铁客流预测存在的时空特性挖掘不充分等问题,进一步提高预测的精度与效率,研究了基于动态图神经常微分方程模型(multivariate time series with dynamic graph neural ordinary differential equations,MTGODE)的地铁短时客流预测方法。该方法通彭颢1贺玉过学习地铁站点间的动态关联强度构建动态拓扑图结构,基于学习得到的动态图进行连续图传播以传递时空信息、挖掘客流的依赖关系,并采用残差卷积提取多时间尺度下的周期性模式,实现了对站点间时空动态的连续表征,克服了传统图卷积网络模型难以刻画动态空间依赖的局限性。此外,为了充分挖掘不同站点间客流分布的时空规律,综合利用北京地铁自动售检票系统(auto fare collection,AFC)刷卡数据、天气数据、空气质量数据以及车站周边用地属性数据构建多源融合的客流预测模型。通过选取地铁北京站和积水潭站-东直门站的历史数据开展进站客流和OD客流预测实验,结果表明:与多个基准模型相比,该模型在平均绝对误差、均方根误差和平均百分比误差这3个指标中均取得了更优的预测效果,相较最优基准模型扩散卷积循环神经网络(diffusion convolutional recurrent neural network,DCRNN)分别降低了9.93%,12.30%,9.23%,对地铁客流时空分布的拟合程度更好,模型具有更好的预测精度、稳定性和拟合能力。

铁路客运站进站客流集散系统动力学模型与算法

掌握车站客流的集散分布特征是优化设施配置与科学规划客流组织策略不可或缺的前提。通过分析铁路客运站进站客流集散网络构成,将其视为融合人流、设施、环境、管理等多维度要素的复杂系统。在此基础上,提出双层客流集散系统动力学模型,该模型全面覆盖从宏观的交通方式分担率、设施通行能力与承载能力,到微观的旅客行进速度与路径选择等关键要素。选择某客运站进行实地调研,依据调研数据建立符合实际场景的出发客流集散系统动力学模型。通过对候车室客流时变特征进行分析,发现客流高峰期的规律性特征,并据此提出通过调整列车时刻表有效缓解高峰时段客流压力的策略,旨在进一步提升车站的运营效率与旅客的出行体验。

Observed Solar Cycle Variation of the Stratospheric QBO Generated in the Mesosphere and Amplified by Upward Propagating Waves

With an analysis of zonal wind observations over 40 years, Salby and Callaghan [1] showed that the Quasi-biennial Oscillation (QBO) at 20 km is modulated by 11-year solar cycle (SC) variations from about 12 to 20 m/s (Figure 2). The observations are reproduced qualitatively in a study with the 3D Numerical Spectral Model, which shows that the SC effect of the stratospheric QBO is produced by dynamical downward coupling originating in the mesosphere. In this modeling study, the SC period is taken to be 10 years, and a realistic heat source is applied varying exponentially with altitude: 0.2%, surface;2%, 50 km;20%, 100 km and above. The numerical results show that the variable solar radiation in the mesosphere around 65 km generates a hemispheric symmetric Equatorial Annual Oscillation (EAO), which is modulated by relatively large SC variations. Under the influence of wave mean flow interactions, the EAO propagates into the lower atmosphere and is the dynamical source or pacemaker for the large SC modulation of the QBO. The numerical results show that the upward propagating small-scale gravity waves from the troposphere amplify the SC modulations of the QBO and EAO in the stratosphere, part of the SC mechanism. The zonal winds of the equatorial QBO and EAO produce through the meridional circulation measurable SC variations in the temperature of the stratosphere and troposphere at high latitudes. Analysis of NCEP temperature and zonal wind data (1958 to 2006) provides observational evidence of the EAO with SC variations around 11 years.

基于无偏灰色组合动态模型的铁路客运量预测研究

针对目前铁路运输客运量预测在精度方面的不足,提出一种无偏灰色组合动态预测模型,应用于现有铁路客运量的预测。通过借鉴无偏GM(1,1)模型直接建模思想,对传统的灰色Verhulst模型作出改进,即对原始序列作倒数生成,运用新生成的倒数序列建立无偏灰色Verhulst模型,以消除传统的灰色Verhulst模型自身的一些偏差;为进一步提高模型的拟合精度及收敛速度,引入马尔科夫链方法对无偏灰色Verhulst模型的拟合结果进行修正,同时兼顾数据序列具有一定的时效性,构建出无偏灰色组合动态客运量预测模型。以我国兰青铁路某区段2010—2019年共10年的客运量数据作为原始数据,验证模型的可靠性与准确性,并与传统EDGM(1,1)模型、灰色Verhulst模型和无偏灰色Verhulst模型作对比,结果表明,本文模型在预测精度方面更凸显优势,能有效提高预测结果的准确性。

基于精细化建模的换热管涡激振动数值研究

为了研究换热管的涡激振动行为,本文基于大涡模拟方法建立了精细化流场计算模型。采用HHT-α方法求解结构动力学方程,结合局部动网格变形技术,得到了换热管涡激振动流固耦合计算模型。以雷诺数为3900的固定圆柱绕流算例和Jauvtis&Williamson的经典涡激振动实验分别对流场计算模型和结构场计算模型进行了验证分析,并研究了不同约化流速下换热管的振动响应、运动轨迹、尾迹模式等。结果表明:建立的涡激振动计算模型可以准确地预测单根换热管的涡激振动行为。本文研究对建立换热管管束结构的流致振动计算模型具有借鉴意义。

机场到港旅客乘坐出租车短时需求预测

对机场旅客陆侧交通需求进行准确预测是机场陆侧交通资源合理分配的重要依据.针对机场到港旅客乘坐出租车短时需求开展研究,从群体角度出发,考虑其他交通方式的影响,基于交通方式的交互直接预测机场乘坐出租车到港旅客流量.采集机场到港旅客出租车订单数据、机场到港飞机数据、机场天气报文数据和机场到港旅客地铁闸门数据,搭建LightGBM模型并根据具体情景采取网格法或贝叶斯优化进行参数标定,预测机场到港旅客乘坐出租车流量,结果优于6个传统经典模型,相比于以往研究,模型考虑乘坐地铁旅客数量对乘坐出租车旅客需求的影响,预测精度更高.研究结果可推广到机场其他陆侧交通方式,完善机场集疏运系统.

基于时段分布的市郊轨道交通车站滞留客流分布算法

市郊轨道交通车站滞留客流的分时段预测,关系到运营计划的调整、乘客出行方式的选择、出行时间的预估等,尤其对市郊线路快慢车模式下开行方案的优化具有重要意义.首先引入出行方式角度费用理论,分析了乘客公交出行与地铁线路形成的角度费用,构建了角度费用模型Anglecostm,nk,计算乘客的流失率VPn,进而确定因滞留客流达到阈值而导致的乘客流失量.其次,以AFC获取的客流数据为支撑,结合角度费用模型对乘客流失量的计算,提出了一种基于时段的滞留车站客流分布预测方法,接着分析了站台候车客流与通过列车实际载客情况两者之间的客流交互规律,提出了候车客流—列车载客量影响动态交换模型,并分析和研究该模型求解算法.最后,以某市郊线路进行实例演算,预测结果可为轨道交通开行方案优化提供理论和方法支持,对运营计划临时调整,客流预测及引导模型的补充等提供参考.

基于交通系统与城市空间结构互馈机制的城际轨道交通走廊客流预测

基于交通系统与城市空间结构之间的动态互馈机制和公交导向性开发策略,开展城际轨道交通走廊客流预测研究。对新建区,在土地使用形态控制的基础上,利用土地价值计算人口地理分布权,进而得到出行发生和出行吸引的权重,它刻画了交通系统对城市空间结构的作用机制;对建成区,主要根据土地使用形态计算出行发生和出行吸引的权重,它体现了城市空间结构对交通系统的影响。在此基础上,给出了城际轨道交通走廊的客流预测方法。该预测方法不仅反映了城际轨道交通系统对客流需求的满足,更重要的是,能真实体现城际轨道交通系统对城市群空间结构形态和交通需求的导向作用。以长株潭城际轨道交通建设项目为背景,运用该方法分析预测了相应区域的城际轨道交通走廊的客流需求量。

城市轨道交通列车运行图能力与客流需求匹配度的评价方法

为了衡量城市轨道交通列车运行图对于动态多维度客流的适应性,提出一种基于实际客流数据的列车运行图能力与客流需求匹配度的评价方法。在微观层面,考虑列车能力约束,构建客流与列车交互模型,得到载客量、满载率、留乘人数、平均候车时间等微观指标,设计色阶列车运行图从时空维度可视化展示客流与列车的作用结果。在宏观层面,提出能力匹配度的概念,并在采用梯形分布函数量化乘车舒适度、候车满意度和企业满意度的基础上,通过乘法合成模型计算得到能力匹配度。以上海轨道交通9号线为例的验证结果表明:由交互模型所得的微观指标与实际运营规律一致;能力匹配度是对乘客利益与企业利益的综合评价,晚高峰时段的能力匹配度最高,早高峰和平峰时段的次之;随着高峰时段发车频率的增加和平峰时段发车频率的减少,能力匹配度呈先增后减的趋势。该方法可为定量优化列车运行图质量提供理论支撑。

城市轨道交通网络客流分布仿真模型研究

城市轨道交通网络客流时空分布特征是网络化协同运输组织的基础与核心.本文在系统分析城市轨道交通乘客出行行为的基础上,基于Multi-Agent建模技术,构建了网络客流分布动态仿真模型,应用该模型模拟乘客的网络出行过程,统计分析得到路网的客流分布特征.该模型既能反映乘客网络出行行为全过程,又能满足大规模路网仿真需求.最后,开发了城市轨道交通网络客流仿真系统,通过北京市轨道交通网络的实际数据对模型和算法进行验证.

城市轨道交通车站客流关联预警研究

为解决车站客流多因素关联预警问题,通过分析闸机客流、通道客流等因素之间的关联关系,基于系统动力学(SD)原理建立车站客流流动模型,并确定SD方程中的变量及常量;利用Vensim软件分别对站台承载客流、进站客流等建立SD方程,形成基于SD方程的关联预警分析流程。最后,建立站台层仿真模型,预测未来一段时间内站内该区域的客流状况。结果表明,当模型内某变量(如站台承载客流量)出现变化时,可通过及时调整该变量所对应的动力学方程中的其他参量,使车站站台承载客流量保持在其能力和安全范围内。

基于元胞自动机的路面车流荷载

引入微观交通流模型中的元胞自动机模型来模拟路面上的车流荷载,用元胞的演变规则分析车流行驶过程中各个车辆的速度以及它们之间车距的变化;车辆振动模型采用1/4车身结构的2自由度模型,并根据国家标准GB7031-86规定生成路面轮廓的时域信号.分析了某盾构隧道在车流荷载作用下的动力响应,为研究车流荷载作用下隧道结构动力响应提供了数值参考.

灰色动态模型群在城市轨道交通客流预测中的应用研究

随着城市轨道交通的快速发展,客流预测作为一项基础工作,在城市轨道交通规划、设计、建设及运营等环节中起着至关重要的作用。鉴于城市轨道交通客流具有周期性变化的特点,依据灰色系统理论,本文提出了由多个灰色Verhulst模型组成的灰色动态模型群,以某城市轨道交通线路为例进行短期客流的预测分析。实例计算证明了采用动态模型群的预测平均值作为最终预测,具有较高的预测精度,可满足实际应用需求。

基于动态广义费用的轨道交通客流划分模型研究

根据轨道交通出行受运营时间影响较大的特点,基于旅客理想出行时间与实际出行时间之差所产生的动态广义费用,构建了不同收入水平旅客总广义费用最少与轨道交通运营部门票价收入最高的双目标优化模型。应用该模型分析了东莞—广州的客流,其结果符合东莞—广州的轨道交通发展趋势,证明了所构建模型的可行性及合理性。

考虑乘客选择行为的地铁车站承载能力瓶颈识别方法

乘客选择行为引起地铁车站客流量分布动态变化,并导致拥堵的传播,是承载能力瓶颈产生的关键因素之一.通过分析乘客在站服务事件链,构建地铁车站系统中设施设备关联网络.在分析乘客选择行为作用下的关联网络特性的基础上,建立了节点约束下的车站客流分配模型,并引入动态惩罚函数求解该模型,结合求解结果,提出通过节点受影响程度指标来识别能力瓶颈.以上海地铁陆家浜路站为例分析,与StaPass软件的仿真结果进行对比,验证了该方法的可行性和准确性,有助于快速分析不同客流条件下车站客流分布,并确定能力瓶颈.

大数据环境下道路场景高时空分辨率众包感知方法

道路场景作为人类发展演变中最重要、最复杂、最典型的载体之一,是道路基础设施与活动行为共同构成的综合体,链接和构建“人地关系”。道路场景感知从二维抽象简略到三维精细丰富、从静态过去式向动态现在时发展,成为智慧城市、智能交通、无人驾驶的关键技术支撑,是我国新型城镇化战略、交通强国战略的核心技术保障。本文立足于时空交通大数据,提出基于道路场景静态基础设施“形”和动态活动行为“流”的高时空分辨率道路场景感知方法。该方法从静态路网“形”角度,以“点-线-面-体”等要素为研究脉络,构建高精度道路地图众包感知的理论体系;在活动行为“流”感知上,突破传统的点模式分析局限,发展了道路网络空间活动流的时空建模与多尺度分析方法。本文揭示了静态基础设施“形”结构与动态活动行为“流”模式交互作用下的道路场景演化规律,形成以“形”控“流”、借“流”定“形”、“形”“流”叠置的高时空精度道路场景众包感知理论体系,为智慧城市、智能交通的发展提供核心技术与数据支撑。