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Mitchell McClanachan
Researcher at Central Queensland University
Publications - 25
Citations - 294
Mitchell McClanachan is an academic researcher from Central Queensland University. The author has contributed to research in topics: Track (rail transport) & Bogie. The author has an hindex of 8, co-authored 25 publications receiving 262 citations.
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Design and Simulation of Rail Vehicles
Maksym Spiryagin,Colin Cole,Yan Quan Sun,Mitchell McClanachan,Valentyn Spiryagin,Tim McSweeney +5 more
TL;DR: In this paper, the authors introduce the problems involved in designing and modeling all types of rail vehicles, including freight and passenger rolling stock, locomotives, and self-powered vehicles used for public transport.
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Wagon instability in long trains
TL;DR: In this article, a model of coupler angles has been added to normal longitudinal train simulation to allow comprehensive study of lateral components of couplers forces, and centripetal inertia calculations to determine quasi-static lateral forces and vertical forces.
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The Calculation of Wheel Impact Force Due to the Interaction between Vehicle and a Turnout
TL;DR: In this article, a method using VAMPIRE® modeling to determine the wheel impact forces due to passing turnout has been developed and is presented in this article; the simulation shows that both turnout curve and crossing have significant effect on the wheel impacts.
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An investigation of the effect of bogie and wagon pitch associated with longitudinal train dynamics
TL;DR: In this paper, the coupler impacts combined with pitching motions in the wagon body and bogies of a 70 tonne hopper coal wagon were located in experimental data and attempts were made to simulate these interactions using NUCARS, ADAMS/Rail and a train-wagon interaction model developed as source code.
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Current train control optimization methods with a view for application in heavy haul railways
Mitchell McClanachan,Colin Cole +1 more
TL;DR: In this paper, train control optimization methods used in passenger, freight, and long heavy haul trains with a view of determining which methods would be best applied to the optimization of heavy haul train control are reviewed.