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Optimisations of draft gear designs for heavy haul trains

thesis
posted on 08.12.2017, 00:00 by Qing WuQing Wu
This thesis developed a parallel multiobjective optimisation methodology to enable fast optimisations of draft gear designs for heavy haul trains. Improvements were achieved in the development of deterministic white-box draft gear models to enable direct use of the results in product design. Draft gear model parameters such as spring stiffness, wedge angles, and preloads were used as optimisation variables. Two optimisation algorithms were used: Genetic Algorithm and Particle Swarm Optimisation. All draft gear designs in the optimisations were constrained by impact tests to ensure the optimised designs also comply with current draft gear acceptance standards. Draft gear performance was assessed using whole-trip Longitudinal Train Dynamics (LTD) simulations and coupler fatigue damage calculations. Each simulation covered about 640 km of track and had about 10 hours of operational time. Three optimisation objectives were considered: minimal fatigue damage for wagon connection systems of loaded trains, minimal in-train (coupler) forces for loaded trains, and minimal longitudinal wagon accelerations for empty trains.

History

Location

Central Queensland University

Additional Rights

I hereby grant to Central Queensland University or its agents the right to archive and to make available my thesis or dissertation in whole or in part through Central Queensland University’s Institutional Repository, ACQUIRE, in all forms of media, now or hereafter known. I retain all copyright, including the right to use future works (such as articles or books), all or part of this thesis or dissertation.

Open Access

Yes

Era Eligible

No

Supervisor

Professor Colin Cole ; Associate Professor Maksym Spiryagin ; Mr Tim McSweeney

Thesis Type

Doctoral Thesis