Modelling of wheels and rail discontinuities in dynamic wheel-rail contact analysis

A classification of wheel-rail contact is given. Difference is made between modelling of a running wheel with continuous single-point-contact, as is common practice in wheel-rail contact analysis, and a wheel with transient double- or multi-point-contact, which may occur for rail irregularities with curvatures larger than that of the wheel circumference. It is shown that application of the first model for these irregularities will strongly underestimate the contact forces as it does not describe occurring mechanisms correctly. Further, it is shown that in principle it is not possible to describe the second type of contact fully correct with a lumped wheel model. Both wheel models are formulated mathematically for some basic contact cases. Afterwards, results are applied to a linear track model. Analytical closed-form solutions are found in the frequency domain for arbitrary type of contact and numerically transformed to the time domain. Finally, the necessity is shown to avoid situations where transient multiple-point-contact may occur (like rail joints) in practice.     

Gas transfer velocities of CO2 and CH4 in a tropical reservoir and its river downstream

We have measured simultaneously the methane (CH₄) and carbon dioxide (CO₂) surface concentrations and water–air fluxes by floating chambers (FC) in the Petit-Saut Reservoir (French Guiana) and its tidal river (Sinnamary River) downstream of the dam, during the two field experiments in wet (May 2003) and dry season (December 2003). The eddy covariance (EC) technique was also used for CO₂ fluxes on the lake. The comparison of fluxes obtained by FC and EC showed little discrepancies mainly due to differences in measurements durations which resulted in different average wind speeds. When comparing the gas transfer velocity (k₆₀₀) for a given wind speed, both methods gave similar results. On the lake and excluding rainy events, we obtained an exponential relationship between k₆₀₀ and U₁₀, with a significant intercept at 1.7 cm h^− 1, probably due to thermal effects. Gas transfer velocity was also positively related to rainfall rates reaching 26.5 cm h⁻¹ for a rainfall rate of 36 mm h^− 1. During a 24-h experiment in dry season, rainfall accounted for as much as 25% of the k₆₀₀. In the river downstream of the dam, k₆₀₀ values were 3 to 4 times higher than on the lake, and followed a linear relationship with U₁₀.     

Implementing green supply chain practices: an empirical investigation in the shipbuilding industry

ABSTRACT

Environmental concerns have become important in the shipbuilding industry. Governmental expectations about environmental and social performance are much higher than in the past. Public authorities penalize companies that do not comply with the rules. Shipbuilding companies face these challenges by introducing new technologies into their business processes. They do not only start initiatives to green their own business processes but also those of their supply chain partners. This form of environmental management is called Green Supply Chain Management (GrSCM) and its importance is increasingly recognized. Although GrSCM is growing, companies are experiencing difficulties engaging suppliers in environmental activities.

This empirical study analyses drivers for supply chain participation of suppliers in the shipbuilding industry. We explain the participations of suppliers in GrSCM practice by investigating influencing factors including governmental involvement in greening the supply chain, customer requirements towards green issues, feeling of social responsibility, competitive advantage by going green, and GrSCM readiness. Hypotheses are tested with partial least squares, using survey data of 93 suppliers of two leading shipbuilding companies. We found GrSCM readiness, competitive advantage, and social responsibility to be significant drivers in supplier participation. No significant support was found for governmental involvement and customer requirements.     

Modeling the interaction between buses,passengers and cars on a bus route using a multi-agent system

This paper models part of a public transport network (PTN), specifically, a bus route, as a small-size multi-agent system (MAS). The proposed approach is applied to a case study considering a ‘real world’ bus line within the PTN in Auckland, New Zealand. The MAS-based analysis uses modeling and simulation to examine the characteristics of the observed system – autonomous agents interacting with one another – under different scenarios, considering bus capacity and frequency of service for existing and projected public transport (PT) demand. A simulation model of a bus route is developed, calibrated and validated. Several results are attained, such as when the PT passenger load is not close to bus capacity, this load has no effect on average passenger waiting time at bus stops. The model proposed can be useful to practitioners as a tool to model the interaction between buses and other agents.     

重庆轨道交通一号线一期工程站点影响范围研究

轨道交通的开通运营将对沿线经济发展起到极大的带动作用,确定轨道交通各站点的影响范围是定量研究轨道交通对沿线经济影响的基础。本研究从实证的角度,运用可达性相等理论研究重庆轨道交通一号线一期工程沿线14个站点的影响范围。认为轨道交通站点的影响范围随距城市中心轨道交通站点距离的增加呈递增趋势。     

Investigating scalability in population synthesis: a comparative approach

In this paper, we investigate the influence of scalability on the accuracy of different synthetic populations using both fitting and generation-based approaches. Most activity-based models need a base-year synthetic population of agents with various attributes. However, when several attributes need to be synthesized, the accuracy of the synthetic population may decrease due to the mixed effects of scalability and dimensionality. We analyze two population synthesis methods for different levels of scalability, i.e. two to five attributes and different sample sizes – 10%, 25% and 50%. Results reveal that the simulation-based approach is more stable than Iterative Proportional Fitting (IPF) when the number of attributes increases. However, IPF is less sensitive to changes in sample size when compared to the simulation-based approach. We also demonstrate the importance of choosing the appropriate metric to validate the synthetic populations as the trends in terms of RMSE/MAE are different from those of SRMSE.     

Real Time Detection and Classification of Arrow Markings in Urban Streets

For highly automated driving in urban regions it is essential to know the precise position of the car. Furthermore it is important to understand the surrounding context in complex situations, e.g. multilane crossings and turn lanes. To understand those situations there is not only the task to detect the lane border, but to detect the painted information inside the lane. The paper is facing and evaluating two methods to classify this additional lane information. Therefore the images from five cameras mounted around the car are used. Four of them with fisheye lenses. The methods have in common, that the input images are transformed into a bird view projection. First introduced method is to extract contours from the transformed images and collect geometrical features and Fourier coefficients. The second introduced way, is to calculate histograms of oriented gradients and use it as input for the classification step. Both classification approaches are implemented and evaluated as multiclass and single class detectors for each arrow type. Furthermore, the classification results from a support vector machine and random forest were faced for this classification problem. The results from the multiclass detectors are evaluated and presented in form of confusion matrices. With the introduced approaches a high detection confidence could be achieved, proofed with validation datasets and in practical use.     

Market Orientation in Public Transport Research—A Review

It is commonly argued that, in order to meet increasing competition, public transport organizations and systems need to be market oriented. Even though the notion of market orientationhas not been explicitly addressed in public transport research, studies relevant to market orientation have been conducted. The aim of this paper is to introduce the concept of market orientation into the field of public transport, to review previous research into market orientation in public transport research, and to suggest directions for future research. Market orientation is defined as the generation and dissemination of market intelligence by organizations, as well as responses to it. The review suggests that previous academic research has focused on intelligence generation by developing and using models for measuring travel behaviour, stated preferences, perceived customer quality, and satisfaction. Studies of responsiveness have mainly addressed the physical improvements made in public transport organizations, which is also the primary concern of the industry research accounted for. There has been less research into the dissemination of market intelligence, the drivers of market orientation, the relations between the elements, and the overall concept of market orientation in public transport. It is thus concluded that future public transport research needs to address these issues.     

Latent temporal preferences: An application to airline travel

An essential element of demand modeling in the airline industry is the representation of time of day demand—the demand for a given itinerary as a function of its departure or arrival times. It is an important datum that drives successful scheduling and fleet decisions. There are two key components to this problem: the distribution of the time of day demand and how preferred travel time influences itinerary choice. This paper focuses on estimating the time of day distribution. Our objective is to estimate it in a manner that is not confounded with air travel supply; is a function of the characteristics of the traveler, the trip, and the market; and accounts for potential measurement errors in self-reported travel time preferences. We employ a stated preference dataset collected by intercepting people who were booking continental US trips via an internet booking service. Respondents reported preferred travel times as well as choices from a hypothetical set of itineraries. We parameterize the time of day distribution as a mixture of normal distributions (due to the strong peaking nature of travel time preferences) and allow the mixing function to vary by individual characteristics and trip attributes. We estimate the time of day distribution and the itinerary choice model jointly in a manner that accounts for measurement error in the self-reported travel time preferences. We find that the mixture of normal distributions fits the time of day distribution well and is behaviorally intuitive. The strongest covariates of travel time preferences are party size and time zone change. The methodology employed to treat self-reported travel time preferences as potentially having error contributes to the broader transportation time of day demand literature, which either assumes that the desired travel times are known with certainty or that they are unknown. We find that the error in self-reported travel time preferences is statistically significant and impacts the inferred time of day demand distribution.