Software simulation is vitally important in a number of industries. It allows engineers to test new products before they leave the drawing board and enables tests that would otherwise be difficult or impossible to perform. Traditional engineering simulations use sophisticated numerical methods to produce models that are highly accurate, but computationally expensive and time-consuming to use. This accuracy is essential in the latter stages of the design process, but can make the early stages - which often involve frequent, iterative design changes - a lengthy and frustrating process. Additionally, the scope of such simulations is often limited by their complexity. An attempt has been made to produce an alternative, real-time simulation tool, developed using software and development practices from the video games industry, which are designed to simulate and render virtual environments efficiently in real-time. In particular, this tool makes use of real-time physics engines; iterative, constraint-based solver systems that use rigid body dynamics to approximate the movements and interactions of physical entities. This has enabled the near-real-time simulation of multi-vehicle trains, and is capable of producing reasonably realistic results, within an acceptably small error bound, for situations in which a real-time simulation would be used as an alternative to existing methods. This thesis presents the design, development and evaluation of this simulation tool, which is based on NVidia's PhysX Engine. The aim was to determine the suitability of a physics engine-based tool for simulating various aspects of rail dynamics. This thesis intends to demonstrate that such a tool, if configured and augmented appropriately, can produce results that approach those produced by traditional methods and is capable of simulating aspects of rail dynamics that are otherwise prohibitively expensive or beyond the capabilities of existing solutions, and may therefore be a useful supplement to the existing tolls used in the rail industry.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:724691 |
| Date | January 2017 |
| Creators | Simpson, Michael David |
| Publisher | University of Newcastle upon Tyne |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10443/3584 |
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