Introduction: This paper introduces a fast method to evaluate the effect of payload distribution on in-train forces. Methods: The method is based on Strong Orthogonal Arrays (SOA) and the excellent space-filling properties of Latin Hypercube Design (LHD): SOA-based-LHD is proved to be very efficient in spanning the range of in-train forces for different types of trains (also considering distributed power/braking) and trains operations. Results: The distribution of the percentage of braked mass is used to consider the effect of payload distribution on in-train forces. Because of its computational efficiency, the method proposed here can be satisfactorily employed to perform an optimization analysis of train composition.
Fast Method to Evaluate Payload Effect on In-Train Forces of Freight Trains
Arcidiacono G;
2018-01-01
Abstract
Introduction: This paper introduces a fast method to evaluate the effect of payload distribution on in-train forces. Methods: The method is based on Strong Orthogonal Arrays (SOA) and the excellent space-filling properties of Latin Hypercube Design (LHD): SOA-based-LHD is proved to be very efficient in spanning the range of in-train forces for different types of trains (also considering distributed power/braking) and trains operations. Results: The distribution of the percentage of braked mass is used to consider the effect of payload distribution on in-train forces. Because of its computational efficiency, the method proposed here can be satisfactorily employed to perform an optimization analysis of train composition.| File | Dimensione | Formato | |
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2018_TOTJ_Fast Method to Evaluate Payload Effect on In-Train Forces of Freight.pdf
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