Vehicle System Dynamics · 2018 · 33 citations · 19 references
BusinessComputational EngineeringSystems EngineeringChassis EngineeringStochastic ModelingUncertainty QuantificationMonte Carlo MethodsMonte Carlo SimulationSimulation MethodsStochastic Systems ModelingUncertainty AnalysisCurrent CollectionDynamic Performance AnalysisMonte Carlo Error AnalysisMonte Carlo Uncertainty PropagationProbability Density FunctionsStochastic DynamicsStochastic Simulation
The simulation of the pantograph–catenary dynamic interaction is at present mainly based on deterministic approaches. However, any errors made during the catenary stringing process are sources of variability that can affect the dynamic performance of the system. In this paper, we analyse the influence of dropper length, dropper spacing and support height errors on the current collection quality by applying a classic Monte Carlo method to obtain the probability density functions of several output quantities. The effects of installation errors are also studied for a range of train speeds. Finally, the pre-sag that, on average, produces the best behaviour of the system is identified, allowing for the uncertainty in the catenary installation. The results obtained show the convenience to consider variability in pantograph–catenary dynamic simulations.
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Bootstrap Methods: Another Look at the Jackknife
B. Efron · The Annals of Statistics · 1979 · 17.4K citations · Full text
N. Metropolis, Stanislaw M. Ulam · Journal of the American Statistical Association · 1949 · 6.1K citations
Central Limit Theorems for Empirical Measures
R. M. Dudley · The Annals of Probability · 1978 · 584 citations · Full text
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