This paper presents the methodology and results of the parallel multiobjective optimisations of draft gear designs. The methodology used white-box draft gear models, whose parameters were used as the optimisation variables. Two optimisation algorithms were used: genetic algorithm and particle swarm optimisation. All the optimised draft gear designs were constrained by impact tests to ensure that the optimised designs also comply with the current acceptance standards for draft gears. The performance of draft gears was assessed using whole-trip longitudinal train dynamics simulations and coupler fatigue damage calculations. Each simulation covered a round trip (loaded one way, empty on return) over a total of 640 km of track, which involved about 10 h of operational time. Three optimisation objectives were considered: minimal fatigue damage for wagon connection systems of loaded trains, minimal in-train forces for loaded trains, and minimal longitudinal wagon accelerations for empty trains. Two case studies were presented, which optimised two types of draft gears (single-stage and double-stage draft gears) using genetic algorithm and particle swarm optimisation, respectively.


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    Title :

    Parallel multiobjective optimisations of draft gear designs


    Contributors:
    Wu, Qing (author) / Cole, Colin (author) / Spiryagin, Maksym (author) / McSweeney, Tim (author)


    Publication date :

    2018-03-01


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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