Research on deformation failure mode of slope diseases caused by earthquakeEI北大核心

Research purposes: The slope diseases caused by earthquake are different from other types of slope diseases in general. They have various mechanism and deformation failure modes and can cause large damages. In order to prevent and control these diseases pointedly, based on investigations of 3 slope diseases along the Wenchuan-Yingxiu Road influenced by the "5·12"Wenchuan Earthquake, the analyses and researches were made and done on the slope diseases types, slope structures and mechanism to summarize the deformation failure modes of slope diseases caused by earthquake. Research conclusions: (1) The main types of slope diseases include the collapse, landslide, slumping, fault and rockfall. Collapse is the major disease, up to 71% of the total slope diseases. About 80% diseases happens to rock slope. (2) The deformation failure modes of collapse have 8 types like pull cracking and falling.Landslide has 5types like pull cracking, shearing off and sliding. Slumping has 2 types of shaking loose and slumping. Rock falling has 2 types of throwing and dropping. Disorder falling has 1 type of shaking to crimping. (3) This research result can provide the reference to prevention and control of the slope diseases caused by earthquakes along railways and roads.     

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为了提高城市交通流预测神经网络方法的快速动态学习能力,提出了一种生长自组织神经网络群,将复杂的神经网络个体分解为多个训练简单的神经网络群组,并利用设计的动态生长自组织算法来避免神经网络在学习新知识的时候对已有知识造成破坏,同时保持整个群工作的高效稳定,规模不过度扩张.该神经网络群尝试解决神经网络的一次性学习问题,具有动态知识增殖学习能力和更强的错误自修复能力及系统适应灵活性.仿真结果表明,这一方法能够更精确地实现函数逼近和城市交通流自适应动态预测,适用于需要不断快速动态学习的复杂系统.     

Mesh generation and hysteretic loss prediction of 3-D periodic patterned tire

This paper is concerned with the numerical prediction of the hysteretic loss-induced rolling resistance of 3-D periodic patterned tire. Elastomeric rubber compounds of rolling tire exhibit the hysteretic loss owing to the phase difference between stress- and strain-time responses. By virtue of this physical characteristic, the rolling resistance is considered as a pseudo-force resisting the tire rolling. The 3-D periodic patterned tire model is constructed by copying an 1-sector mesh in the circumferential direction, and strain cycles of each strain component are approximated by 3-D static tire contact analysis. According to the principal value of half strain amplitudes, the hysteretic loss is calculated in terms of the amplitude of the maximum principal strain and the loss modulus of rubber compound. The numerical results of 3-D periodic patterned tire are justified with the experimental data and compared with those of 3-D smooth tire.     

Objective evaluation of human perception of automotive sound based on physiological signal of human brain

This paper presents a novel approach to apply the physiological signal of the human brain to the sound quality evaluation of automotive sound. In the previous work, psychoacoustic metrics were applied to the sound quality evaluation of automotive sound. Loudness among psychoacoustic metrics is used for one of major sound metrics for the objective evaluation of the sound quality of the acceleration sound inside a car. Subjective evaluation of the sound quality of the acceleration sound shows different results depending on the two different groups of participants. One group liked powerful sound when a car is accelerated: the other group liked the refine sound. Loudness of the acceleration sound is not correlated with the subjective rating of the former group whilst it is correlated with that of the latter group. This evaluation suggests that for the people who like the powerful acceleration sound, it needs to find the sound metric for the objective evaluation of the sound quality of the acceleration sound. In this paper, a driver’s brain signal is measured using electroencephalography (EEG) when a driver hears the acceleration sound of passenger cars. The signal is analyzed to obtain the relationship between brain signals and human perception. According to these results, the alpha wave correlates to the human perception of powerful sound quality of passenger cars. This interesting relationship can be used for objective evaluation of passenger car sounds.     

Demand for taxi services: new elasticity evidence

This paper investigates the factors that influence the choice of, and hence demand for taxis services, a relatively neglected mode in the urban travel task. Given the importance of positioning preferences for taxi services within the broader set of modal options, we develop a modal choice model for all available modes of transport for trips undertaken by individuals or groups of individuals in a number of market segments. A sample of recent trips in Melbourne in 2012 was used to develop segment-specific mode choice models to obtain direct (and cross) elasticities of interest for cost and service level attributes. Given the nonlinear functional form of the way attributes of interest are included in the modal choice models, a simple set of mean elasticity estimates are not behaviourally meaningful; hence a decision support system is developed to enable the calculation of mean elasticity estimates under specific future service and pricing levels. Some specific direct elasticity estimates are provided as the basis of illustrating the magnitudes of elasticity estimates under likely policy settings.     

Examining the relationship between active travel,weather, and the built environment: a multilevel approach using a GPS-enhanced dataset

This study examines how the built environment and weather conditions influence the use of walking as a mode of transport. The Halifax Regional Municipality in Nova Scotia, Canada is the study area for this work. Data are derived from three sources: a socio-demographic questionnaire and a GPS-enhanced prompted recall time-use diary collected between April 2007 and May 2008 as part of the Halifax Space-Time Activity Research project, a daily meteorological summary from Environment Canada, and a comprehensive GIS dataset from the regional municipality. Two binary logit multilevel models are estimated to examine how the propensity to use walking is influenced by the built environment and weather while controlling for socio-demographic characteristics. The built environment is measured via five attributes in one model and a walkability index (derived from the five attributes) in the other. Weather conditions are shown to affect walking use in both models. Although the walkability index is significant, the results demonstrate that this significance is driven by specific attributes of the built environment—in the case of this study, population density and to a lesser extent, pedestrian infrastructure.     

What’s your type: a multidimensional cyclist typology

Increasing bicycle use for utilitarian trips is a common city objective for health and environmental improvement and congestion reduction, but cyclists react heterogeneously to interventions and infrastructure. Understanding cyclist types helps in comprehending and planning for this diverse population. This study uses data from 2004 surveyed Montreal cyclists to generate a multidimensional cyclist typology based on seven factors derived from 35 variables, mostly proven determinants of the intensity of bicycle usage. The analysis revealed four distinct cyclist types: dedicated cyclists, path-using cyclists, fairweather utilitarians, and leisure cyclists. The cycling frequencies of each group respond differently to potential interventions and vary within commuting rate ranges with apparent minima and maxima. Building a network adapted to different cyclist types and emphasizing its convenience, flexibility and speed, could be an effective strategy to increase cycling mode share and frequency among the various groups. Findings from this study can be of benefit to transportation engineers, planners and policy makers as they help in better understanding the impacts of various interventions on the different groups of cyclists.     

Application of El Farol model for managing marine terminal gate congestion

Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of the problem. An approach being experimented by some terminals to reduce truck queuing at the terminal is to provide live views of their gates via webcams. An assumption made by the terminals in this method is that truck dispatchers and drivers will make rational decisions regarding their departure times such that there will be less fluctuations in truck arrivals at the terminal based on the live information. However, it is clear that if dispatchers send trucks to the terminal whenever the truck queues are short and not send trucks when the truck queues are long, it could lead to a perpetual whip lash effect. This study explores the predictive strategies that need to be made by the various dispatchers to achieve the desired effects (i.e. steady arrival of trucks and hence less queuing at the seaport terminal gates). This problem is studied with the use of an agent-based simulation model and the solution to the well known El Farol Bar problem. Results demonstrate that truck depots can manage (without any collaboration with one another) to minimize congestion at seaport terminal gates by using the provided real-time gate congestion information and some simple logics for estimating the expected truck wait time.     

Modelling commuting mode choice with explicit consideration of carpool in the choice set formation

This article investigates the carpool mode choice option in the context of overall commuting mode choice preferences. The article uses a hybrid discrete choice modelling technique to jointly model the consideration of carpooling in the choice set formation as well as commuting mode choice together with the response bias corrections through the accommodation of measurement equations. A cross-nested error structure for the econometric formulation is used to capture correlations among various commuting modes and carpool consideration in the choice set. Empirical models are estimated using a data set collected through a week-long commuter survey in Edmonton, Alberta. The empirical model reveals many behavioural details of commuting mode choice and carpooling. Interestingly, it reveals that interactions between various Travel Demand Management (TDM) tools with the carpooling option can be different at different level of decision making (choice set formation level and final choice making level).     

Behavioural responses to vehicle emissions charging

Road pricing as an economic construct is not a new phenomenon in transportation research. Whilst fuel taxation and tolling of roads are common ways of raising revenue in many countries, these initiatives are primarily aimed at road infrastructure financing. Worldwide there has been growing interest in pricing structures designed to also manage the growing levels of traffic congestion and, in recent times, an increasing focus on generating reductions in carbon emissions from vehicle ownership and use. This paper presents a stated choice experiment undertaken in response to the increasing interest in the environmental externalities of travel behaviour. The aim of this choice experiment is to identify the potential to switch to more fuel efficient cars that emit lower emissions, under differing pricing and technology scenarios. Results indicate that annual and variable emissions surcharges targeted very specifically to vehicle emission rates have a noticeable role in modifying vehicle purchasing decisions.