“互联网+智能交通”市场进入发展黄金期

正1城市智能交通下一个创新风口统计结果显示,我国一线城市私家车保有量年平均增速达到20%。有限的城市土地供应和快速增长的城市交通需求之间的矛盾日益凸显。根据高德地图的研究,相比2015年,2016年调研的45座主要城市中有80%的城市延时拥堵指数加重。其中,北上广深的出行高峰时期平均每小时拥堵时间长达29 min,对于出行居民的个人年拥堵成本达到9 500元,相当于个人年均收入的     

Physical processes in wheel–rail contact and its implications on vehicle–track interaction

Friction within the wheel–rail contact highly influences all aspects of vehicle–track interaction. Models describing this frictional behaviour are of high relevance, for example, for reliable predictions on drive train dynamics. It has been shown by experiments, that the friction at a certain position on rail is not describable by only one number for the coefficient of friction. Beside the contact conditions (existence of liquids, solid third bodies, etc.) the vehicle speed, normal loading and contact geometry are further influencing factors. State-of-the-art models are not able to account for this sufficiently. Thus, an Extended-Creep-Force-Model was developed taking into account effects from third body layers. This model is able to describe all considered effects. In this way, a significant improvement of the prediction quality with respect to all aspects of vehicle–track interaction is expected.     

Multi-response optimization of diesel engine performance parameters using thumba biodiesel-diesel blends by applying the Taguchi method and grey relational analysis

This paper presents an experimental study that involves an application of the Taguchi method and grey relational analysis to determine the optimum factor level to obtain optimum multiple-performance characteristics of a diesel engine run with different low-percentage thumba biodiesel-diesel blends. Four factors, namely, low-percentage thumba biodiesel-diesel blend, compression ratio, nozzle opening pressure and injection timing were each considered at three levels. An L₉ orthogonal array was used to collect data for various engine performance- and emission-related responses under different engine loads. The signal-to-noise (S/N) ratio and grey relational analysis were used for data analysis. The results of the study revealed that the combination of a blend consisting of 30% thumba biodiesel (B30), a compression ratio of 14, a nozzle opening pressure of 250 bar and an injection timing of 20° produces maximum multiple performance of a diesel engine with minimum multiple emissions from the engine.     

Development of an idle speed engine model using in-cylinder pressure data and an idle speed controller for a small capacity port fuel injected SI engine

An idle speed engine model has been proposed and applied for the development of an idle speed controller for a 125 cc two wheeler spark ignition engine. The procedure uses the measured Indicated Mean Effective Pressure (IMEP) at different speeds at a constant fuel rate and throttle position obtained by varying the spark timing. At idling conditions, IMEP corresponds to the friction mean effective pressure. A retardation test was conducted to determine the moment of inertia of the engine. Using these data, a model for simulating the idle speed fluctuations, when there are unknown torque disturbances, was developed. This model was successfully applied to the development of a closed loop idle speed controller based on spark timing. The controller was then implemented on a dSPACE Micro Autobox on the actual engine. The Proportional Derivative Integral (PID) controller parameters obtained from the model were found to match fairly well with the experimental values, indicating the usefulness of the developed idle speed model. Finally, the optimized idle speed control algorithm was embedded in and successfully demonstrated with an in-house built, low cost engine management system (EMS) specifically designed for two-wheeler applications.     

U.S. import/export container flow modeling and disruption analysis

International containerized freight movement is a vital part of the supply chain for many companies, and a critical element of moving consumer goods to points of retail sale within the U.S. Containerized imports also present a clear security concern (e.g., terrorists attempting to ship “dirty bombs,” chemical, biological or even nuclear weapons, into the U.S. in a shipping container). The goal of the research presented here is to create a modeling tool for analyzing flows of U.S. imports and exports of containerized freight, and the potential changes in those flows under a variety of conditions (e.g., port disruptions, extensive security-related delays, etc.). Our focus is on movements through maritime container ports, and not overland movements between the U.S. and Canada or Mexico.The network model, referred to as the System for Import/Export Routing and Recovery Analysis (SIERRA), represents container movements between the U.S. and 46 other countries that account for the vast majority of U.S. imports and exports. The SIERRA model is a network equilibrium model that predicts flows between foreign countries and North American ports, the total volumes handled (import and export) by each port, the modal volumes (truck and rail) moving domestically into and out of each port, and volumes between each port and a set of transportation analysis zones within the U.S.     

A finite element model for flexible pipe armor wire instability

The constructive disposition of metallic and plastic layers confers flexible pipes with high and low axial stiffness respectively when tensile and compressive loads are applied. Under certain conditions typically found during deepwater installation or operation, flexible pipes may be subjected to high axial compression, sometimes accompanied by bending. If not properly designed, the structure may not be able to withstand this loading and fails. From practical experience observed offshore and in laboratory tests two principal mechanisms, which will be discussed in this paper, have been identified regarding the configuration of the armor wires. When the pipe fails by compression the armor wires may exhibit localized lateral or radial deflections, consequently permanent damage is observed in the armor wires with a sudden reduction of the structure’s axial stiffness. The pressure armor may also unlock, thus causing potential fluid leakage.In this work a finite element model is developed to estimate the critical instability load and failure modes. An axi-symmetric model is constructed employing a complex combination of beam and spring elements. For each armor layer only one wire needs to be modeled, hence the computational cost is minimized without compromising the phenomenon characterization. A parametric case study is performed for a typical flexible pipe structure, where the friction coefficient between the wire armors and the external pressure are varied, and the critical instability loads and failure modes are obtained and results are discussed.     

通过形状差异修正模式方法进行的损伤识别试验(英文)

An experimental program was undertaken to test the feasibility to detect the occurrence of structural damage using a modified mode shape difference technique. The vibration response of a steel beam fixed at one end and hinged at the other was obtained for the intact and damage conditions. Modal analysis was performed to extract the frequencies and mode shapes. The method shows a good potential in detection of occurrence and location of damage.     

Estimating a model of dynamic activity generation based on one-day observations: Method and results

In this paper we develop and explore an approach to estimate dynamic models of activity generation on one-day travel-diary data. Dynamic models predict multi-day activity patterns of individuals taking into account dynamic needs as well as day-varying preferences and time-budgets. We formulate an ordered-logit model of dynamic activity-agenda-formation decisions and show how one-day observation probabilities can be derived from the model as a function of the model’s parameters and, with that, how parameters can be estimated using standard loglikelihood estimation. A scale parameter cannot be identified because information on within-person variability is lacking in one-day data. An application of the method to data from a national travel survey illustrates the method. A test on simulated data indicates that, given a pre-set scale, the parameters can be identified and that estimates are robust for a source of heterogeneity not captured in the model. This result indicates that dynamic activity-based models of the kind considered here can be estimated from data that are less costly to collect and that support the large sample sizes typically required for travel-demand modeling. We conclude therefore that the proposed approach opens up a way to develop large-scale dynamic activity-based models of travel demand.     

Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings

In recent years we have seen important extensions of logit models in behavioural research such as incorporation of preference and scale heterogeneity, attribute processing heuristics, and estimation of willingness to pay (WTP) in WTP space. With rare exception, however, a non-linear treatment of the parameter set to allow for behavioural reality, such as embedded risk attitude and perceptual conditioning of occurrence probabilities attached to specific attributes, is absent. This is especially relevant to the recent focus in travel behaviour research on identifying the willingness to pay for reduced travel time variability, which is the source of estimates of the value of trip reliability that has been shown to take on an increasingly important role in project appraisal. This paper incorporates, in a generalised non-linear (in parameters) logit model, alternative functional forms for perceptual conditioning (known as probability weighting) and risk attitude in the utility function to account for travel time variability, and then derives an empirical estimate of the willingness to pay for trip time variability-embedded travel time savings as an alternative to separate estimates of time savings and trip time reliability. We illustrate the richness of the approach using a stated choice data set for commuter choice between unlabelled attribute packages. Statistically significant risk attitude parameters and parameters underlying decision weights are estimated for multinomial logit and mixed multinomial logit models, along with values of expected travel time savings.