压力管道局部损伤检测的多输出模态实验研究

基于振动的实验模态分析方法可对结构参数进行识别,并在此基础上实现结构损伤识别.该方法目前已用于压力管道的损伤检测中.通常采用单输出模态实验法,即各个节点进行逐点激励,这样就带来了检测效率较低的问题.对此,采用多输出模态实验,同时在管道模型上布置多个传感器进行数据采集,使检测效率得到了显著提高.压力管道损伤诊断的模态实验...     

隧道爆破振动下砌体结构局部动力反应研究

文章依托成渝客专新红岩隧道爆破工程,选取典型实测爆破地震波和典型二层砌体结构,分析了砌体结构的低阶整体模态和高阶局部模态,采用振型位移叠加法理论分析了隧道爆破振动下结构的位移和应力反应特征,研究了不同峰值振速下砌体砖墙的主拉应力分布及变化规律。结果表明:典型二层砌体结构1~5阶为低阶整体模态,固有频率为8.80~24.86 Hz,振型为整体均匀变形;6~20阶为高阶局部密集模态,固有频率为25.96~36.14 Hz,局部变形显著大于整体变形;高频的隧道爆破振动引起的结构位移很小,而局部构件上的内力要比位移大得多,这是因为结构内力计算中的振型幅值向量乘以了振型频率的平方;隧道爆破振动下结构的动力损伤主要由瞬时产生的高应力控制,而不是位移;砖墙的门、窗洞角处及砖墙与混凝土构件接触的应力集中部位和女儿墙、侧墙、中隔墙、阳台等局部构件振动较大的部位受拉应力较大,在隧道爆破振动下容易产生损伤。     

基于小波变换和模态声发射的管道中导波传播特性的试验研究

基于小波变换和模态声发射理论,通过模态声发射试验的方法确定了管道中导波传播的频散特性。通过分析声发射信号的Gabor小波变换幅度在时频空间分布特点,确定某一频率下某一模态导波到达传感器的时间,从而确定该频率下该模态导波的群速度,进而确定其频散曲线。试验确定管道中频散曲线与理论计算曲线较好吻合,证明小波变换是分析频散波时频特性的有效工具。     

磁致伸缩导波技术在管道检测中的应用

介绍了磁致伸缩T模态导波技术检测管道缺陷的原理.实验研究了磁致伸缩导波技术检测管道缺陷的灵敏度和精度,实验结果证明该检测技术具有很高的灵敏度和精度.在此基础上应用该检测技术对在役管道进行在线检测,给出了数据分析结果和不同环境下磁致伸缩导波技术对管道缺陷检测的可靠灵敏度.实验和现场检测表明:磁致伸缩T模态导波技术在管道检测上具有较高的可靠性和快捷性.     

汽车前梁设计中有限元方法的应用

使用有限元分析软件,模拟汽车前梁台架试验条件,对设计的前梁进行静力学分析,模态分析以及疲劳分析,并根据分析结果对前梁优化设计改进,提高了前梁强度和疲劳寿命。从而缩短了产品设计周期,提高了产品质量和可靠性。     

管道超声导波腐蚀检测技术应用研究

介绍了导波的频散特性及相关的理论成果.从导波的结构出发,分析了导波在介质中能量与位移的分布.阐述了导波检测技术领域中数值分析方法和信号处理方面的一些新技术,根据超声导波现场检测存在缺陷及不能精确定量问题,推荐使用C扫描为缺陷定量.完成检测后,对管道强度进行了分析,指出存在的主要问题,对开展超声导波检测有重要指导作用.     

多圆盾构土体位移特征及其应用

文章以日本某深埋地铁车站工程为例,基于修正的Loganathan公式,运用叠加原理,建立了多圆盾构施工扰动引起土体位移的计算公式,分析了多圆盾构施工扰动引起的地表沉降、土体深层沉降、侧向位移特征.结果表明,计算值与实测值吻合较好,其修正的Loganathan公式适用于计算多圆盾构施工扰动引起的土体位移,多圆盾构横向地表沉降特征基本符合正态分布.所得结论对于多圆盾构工法在我国的进一步运用具有一定的借鉴作用.     

某车型座椅骨架动态安全性与模态分析

为判断汽车座椅骨架的结构合理性,文章利用ANSA建立了某乘用车座椅骨架总成及假头型有限元模型,对该座椅骨架进行了模态分析与基于显式动力学有限元的头枕吸能性仿真试验,得到前四阶固有频率和振型、头枕前碰仿真分析加速度时间历程图。结果表明,该座椅骨架自由模态频率避开了人体最敏感的共振频率范围,整个碰撞过程假头型减速度超过80 g的连续作用时间未超过3 ms。     

对冲式消能器的消能效率及模态分析

文中利用ANSYS中的Fluent流体分析软件、静力学软件和模态分析软件进行了单向流固耦合仿真,分析了流体为压裂返排液时,该消能装置在一定高压范围和管径范围内的消能效率以及固有频率变化情况.流体分析表明,随着进口总压不断增高,对冲式消能器的消能效率基本稳定在70％;由于对冲产生涡流自耗,消能器进出口的速度未发生突增.模...     

金属磁记忆检测缺陷量化及管道寿命预测研究

为了更好了解金属磁记忆检测在管道缺陷识别、尺寸量化和剩余寿命方面的研究现状,展望将来的研究方向,综合分析了基于金属磁记忆的管道缺陷识别的研究方法和存在的问题。根据缺陷尺寸量化的现有文献,归纳出管道缺陷尺寸量化进一步研究的方向。阐述了管道剩余寿命预测的研究和数据收集存在的问题。数学方法、数学模型和计算机技术将成为金属磁记忆研究的有力工具,根据真实环境下的管道相关实验数据建立管道缺陷识别、尺寸量化和管道剩余寿命的自动化分析系统是研究的重要方向。     

Effects of incorporating latent and attitudinal information in mode choice models

Abstract

Hybrid choice modelling approaches allow latent variables in mode choice utility functions to be addressed. However, defining attitude and behavior as latent variables is influenced by the researcher's assumptions. Therefore, it is better to capture the effects of latent behavioral and attitudinal factors as latent variables than defining behaviors and attitudes per se. This article uses a hybrid choice model for capturing such latent effects, which will herein be referred to as modal captivity effects in commuting mode choice. Latent modal captivity refers to the unobserved and apparently unexplained attraction towards a specific mode of transportation that is resulting from latent attitude and behavior of passengers in addition to the urban transportation system. In empirical models, the latent modal captivity variables are explained as functions of different observed variables. Empirical models show significant improvement in fitting observed data as well as improved understanding of travel behavior.     

Evolution of latent modal captivity and mode choice patterns for commuting trips: A longitudinal analysis using repeated cross-sectional datasets

This paper presents an investigation of the temporal evolution of commuting mode choice preference structures. It contributes to two specific modelling issues: latent modal captivity and working with multiple repeated crossectional datasets. In this paper latent modal captivity refers to captive reliance on a specific mode rather than all feasible modes. Three household travel survey datasets collected in the Greater Toronto and Hamilton Area (GTHA) over a ten-year time period are used for empirical modelling. Datasets collected in different years are pooled and separate year-specific scale parameters and coefficients of key variables are estimated for different years. The empirical model clearly explains that there have been significant changes in latent modal captivity and the mode choice preference structures for commuting in the GTHA. Changes have occurred in the unexplained component of latent captivities, in transportation cost perceptions, and in the scales of commuting mode choice preferences. The empirical model also demonstrates that pooling multiple repeated cross-sectional datasets is an efficient way of capturing behavioural changes over time. Application of the proposed mode choice model for practical policy analysis and forecasting will ensure accurate forecasting and an enhanced understanding of policy impacts.     

Modeling traveler mode choice behavior of a new high-speed rail corridor in China

This study examines mode choice behavior for intercity business and personal/recreational trips. It uses multinomial logit and nested logit methods to analyze revealed preference data provided by travelers along the Yong-Tai-Wen multimodal corridor in Zhejiang, China. Income levels are found to be positively correlated with mode share increases for high-speed rail (HSR), expressway-based bus, and auto modes, while travel time and trip costs are negatively correlated with modal shift. Longer distance trips trigger modal shifts to HSR services but prevent modal shift to expressway-based auto use due to escalation of fuel cost and toll charges. Travelers are less elastic in their travel time and cost for trips by nonexpressway-based auto use modes. The magnitude of elasticity for travel time is higher than trip costs for business trips and lower for personal/recreational trips. The study provides some policy suggestions for transportation planners and decision-makers.     

A reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

Tradable credits scheme and transit investment optimization for a two‐mode traffic network

This paper proposes an optimization model to minimize the “system costs” and guide travelers' behavior by exploring the optimal bus investment and tradable credits scheme design in a bimodal transportation system. Travelers' transport mode choice behavior (car or bus) and the modal equilibrium conditions between these two forms of transport are studied in the tradable credits scheme. Public transport priority is highlighted by charging car travelers credits only. The economies of scale presented by the transit system under the tradable credit scheme are analyzed by comparing the marginal cost and average cost. Numerical examples are presented to demonstrate the model. Furthermore, the effects of tradable credits schemes on bus investment and travelers' modal choice behavior are explored based on scenario discussions. Copyright © 2016 John Wiley & Sons, Ltd.     

多轴车桥耦合振动模型的Fourier级数求解方法分析

文章以某高速公路40m简支T梁为研究对象,基于结构动力学原理推导了多轴车桥耦合振动系统的系统振动微分方程,并求解出微分方程时变激振力的Fourier级数表达式,同时基于模态叠加法得出结构动力响应的解析表达式,对该简支T梁在不同过桥车速、不同车辆车轴布置以及不同车辆车轴超重情况下的结构动力响应进行参数分析。     

Investigating travel utility elements in association with travel time and mode choice: the case of Seoul,South Korea

In this paper, travel utility is conceptualized into the elements of disutility, or derived utility, and positive utility, which includes synergistic and intrinsic utility, and then analyzed in terms of the effects of these elements on weekly travel time according to three travel modes – the automobile, public transit, and nonmotorized modes – and on the choice of the annually most used mode. Linear regressions on mode-specific travel time and a multinomial logistic regression on mode choice show that, compared to life situation and land-use characteristics, utility elements are among the strongest travel determinants. Specifically, while some utility elements contribute exclusively to shifting the mode of travel and others to increasing nonmotorized travel, modal shift is most strongly affected by a disutility element, trip timeliness, and the increase in nonmotorized travel by a positive utility element, amenities.     

A behavioral analysis of freight mode choice decisions

This paper develops a behavioral analysis of freight mode choice decisions that could provide a basis for an acceptable analytical tool for policy assessment. The paper specifically examines the way that truck and rail compete for commodity movement in the US. Two binary mode choice models are introduced in which some shipment-specific variables (e.g. distance, weight and value) and mode-specific variables (e.g. haul time and cost) are found to be determinants. The specifications of the non-selected choice are imputed in a machine learning module. Shipping cost is found to be a central factor for rail shipments, while road shipments are found to be more sensitive to haul time. Sensitivity of mode choice decisions is further analyzed under different fuel price fluctuation scenarios. A low level of mode choice sensitivity is found with respect to fuel price, such that even a 50% increase in fuel cost does not cause a significant modal shift between truck and rail.     

Investigating the effects of psychological factors on commuting mode choice behaviour

This paper utilizes socio-psychometric survey data to investigate the influence of attitudes, affective appraisal and habit formation on commuting mode choice. The data-set was collected in 2009–2010 in Edmonton, Alberta. In addition to conventional socio-economic, demographic and modal attributes, the survey gathered psychological information regarding habitual behaviour, affective appraisal and personal attitudes. Different psychometric tools were used to capture psychological factors affecting mode choice. Habitual behaviour was measured using Verplanken's response-frequency questionnaire. Affective appraisal was indirectly estimated using the Osgood's semantic differential. Five-point Likert scales were used to measure attitude. The structural equation modelling (SEM) approach was used to investigate the effects of psychological factors on mode choice behaviour. SEM captures the latent nature of psychological factors and uses path diagrams to identify the directionality as well as intensity of the relationships. The investigation reveals that passengers have positive emotions towards their chosen mode. Further, evidence of the superiority of the car as a travel alternative was established in terms of strong habit towards it, such that passengers would use the car for almost every single trip.     

Travel demand (modal split) estimation by hierarchical measurement

This paper develops a procedure for travel demand estimation via the Saaty method of Analytic Hierarchy. A stratification of the travel demand by trip-making and trip attributes has been represented more inclusively in a hierarchy system. Various elements and dimensions of the hierarchy have been hypothesized as different levels of decisions made by trip-makers. The elements contained in a set of specified matrices of travel attributes have been weighed utilizing a ratio scale, in a process of mapping transportation systems (modal) attributes with the characteristic trip-making behavior in a hierarchical demand structure. The principal output of this procedure is an estimate of the trip distribution by mode, or modal split. The estimate closely approximates the observed modal split pattern for the inter city travel problem simulated. This procedure is proposed for travel demand forecasting and planning.