1,720,982 research outputs found
Cooperative control and stability analysis for virtual coupling of rail vehicles
Get PDFCooperative control for rail vehicles is a new idea which builds on existing models and methods developed in the context of flight formation and autonomous ground vehicles. The underlying idea is to assimilate virtually coupled rail vehicles to arrays of mass–spring–dashpot systems. The contribution of this paper is three-fold. First, a novel scheme is proposed which involves a supervisory control for the higher-level planning and a local motion coordination for the lower-level implementation. For the supervisory control, a review of the existing scheduling models and methods based on alternate graphs and a mixed-integer (non)linear program is conducted. For the local coordination, a nonlinear and uncertain model is developed and a constructive method is provided to design a feedback control that stabilizes the vehicle around a desired equilibrium point, in terms of position and velocity. Second, the control design method is extended to the case of multiple virtually coupled vehicles. It is proven that the transient dynamics follows a typical synchronization dynamics. It is also proven that under such control, the whole system of rail vehicles converges to a pre-defined equilibrium point, characterized by a specific velocity and relative distance between vehicles. Conditions for the stability of such equilibrium points are investigated. Third, under the hypothesis of homogeneity, bounds on the damping coefficient for the synchronization equilibrium (in terms of velocity and relative distance between vehicles) to be overdamped or underdamped are provided
A mathematical programming model to select maintenance strategies in railway networks
Get PDFThis paper presents a nonlinear integer programming model to support the selection of maintenance strategies to implement on different segments of a railway network. Strategies are selected which collectively minimise the impact of sections’ conditions on service, given network availability and budget constraints. Different metrics related to the network topology, sections’ availability, service frequency, performance requirements and maintenance costs, are combined into a quantitative approach with a holistic view. The main contribution is to provide a simple yet effective modelling approach and solution method which are suitable for large networks and make use of standard solvers. Both an ad hoc heuristic solution and relaxation methods are developed, the latter enabling the quality of the heuristic solution to be estimated. The availability of railway lines is computed by exploiting the analogy with series–parallel networks. By varying the model parameters, a scenario analysis is performed to give insight into the influence of the system parameters on the selection of strategies, thus enabling more informed decisions. For its simple structure, the model is versatile to address similar problems arising in the maintenance of other types of networks, such as road and bridges networks, when deciding on the strategic allocation of maintenance efforts
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Modelling resilient railway systems
Get PDFThe complexity of the railway asset management process motivates the need for bespoke tools to enable optimal asset management decisions. To address such a need, a Railway Asset Management Modelling Framework is presented to support a structured and systematic decision making process on asset interventions. The framework describes the structure and requirements of the railway asset management system for delivering a safe and reliable railway, whilst minimising the life-cycle costs. It specifies the models and data needed to predict assets’ and network performance indicators on a whole-life, whole-system basis. Depending on the level of abstraction, the models support decisions at asset/route/network level to ultimately meet service and safety targets for the minimum cost. Two main types of models are described: (i) predictive models to forecast the performance of the system of interest under a variety of circumstances, and (ii) optimisation models that use real and predicted data to achieve optimal decisions on the asset interventions. To the first group belong the asset state models aimed at assessing the assets’ response to a range of maintenance strategies.
To demonstrate the capabilities of such models, a track asset management model is presented. It combines the description of the degradation and intervention processes involved in the maintenance of the overall track geometry. The model is built for a line section to account for dependencies due to opportunistic maintenance and renewals. The technique adopted to develop the model is based on Coloured Petri nets with the Monte Carlo simulation method used for its analysis. The asset state models provide statistics on the asset's behaviour which inform a network-level optimisation model for the selection of the optimal combination of intervention strategies for all assets along a given route. A nonlinear integer model is presented along with the ad hoc solution approaches developed to address the nonlinearities. Relaxation tools offered by the mathematical programming formulation enable the percentage error to be estimated thus giving a measure of the quality of the approximate solutions.
Effective asset management strategies result in higher reliability and availability of the assets. However failures and possessions of the infrastructure cannot be completely avoided, and a capability is needed to tolerate disruptions. Crossovers enable trains to switch track, and thus are essential to provide a flexible and connected network. If their number and distribution on the network is optimised, then they unlock the potential for a fault tolerant network. A nonlinear bi-objective mixed-integer optimisation model is developed to this purpose along with a solution approach. The aim is to find the number and distribution of crossovers for the minimum costs, which also minimises the loss of train flow and enables availability targets to be achieved for each line.
Both optimisation models are applied to analyse a variety of scenarios for different values of the system parameters. The analysis of the results enables an evaluation of the robustness of the solutions towards the system parameters
Modelling resilient railway systems
Get PDFThe complexity of the railway asset management process motivates the need for bespoke tools to enable optimal asset management decisions. To address such a need, a Railway Asset Management Modelling Framework is presented to support a structured and systematic decision making process on asset interventions. The framework describes the structure and requirements of the railway asset management system for delivering a safe and reliable railway, whilst minimising the life-cycle costs. It specifies the models and data needed to predict assets’ and network performance indicators on a whole-life, whole-system basis. Depending on the level of abstraction, the models support decisions at asset/route/network level to ultimately meet service and safety targets for the minimum cost. Two main types of models are described: (i) predictive models to forecast the performance of the system of interest under a variety of circumstances, and (ii) optimisation models that use real and predicted data to achieve optimal decisions on the asset interventions. To the first group belong the asset state models aimed at assessing the assets’ response to a range of maintenance strategies.
To demonstrate the capabilities of such models, a track asset management model is presented. It combines the description of the degradation and intervention processes involved in the maintenance of the overall track geometry. The model is built for a line section to account for dependencies due to opportunistic maintenance and renewals. The technique adopted to develop the model is based on Coloured Petri nets with the Monte Carlo simulation method used for its analysis. The asset state models provide statistics on the asset's behaviour which inform a network-level optimisation model for the selection of the optimal combination of intervention strategies for all assets along a given route. A nonlinear integer model is presented along with the ad hoc solution approaches developed to address the nonlinearities. Relaxation tools offered by the mathematical programming formulation enable the percentage error to be estimated thus giving a measure of the quality of the approximate solutions.
Effective asset management strategies result in higher reliability and availability of the assets. However failures and possessions of the infrastructure cannot be completely avoided, and a capability is needed to tolerate disruptions. Crossovers enable trains to switch track, and thus are essential to provide a flexible and connected network. If their number and distribution on the network is optimised, then they unlock the potential for a fault tolerant network. A nonlinear bi-objective mixed-integer optimisation model is developed to this purpose along with a solution approach. The aim is to find the number and distribution of crossovers for the minimum costs, which also minimises the loss of train flow and enables availability targets to be achieved for each line.
Both optimisation models are applied to analyse a variety of scenarios for different values of the system parameters. The analysis of the results enables an evaluation of the robustness of the solutions towards the system parameters
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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