The Granular Mechanics and Industrial Infrastructure research group, at the School of Engineering of the University of Edinburgh, conducts fundamental research on the mechanics of granular materials and their interaction with industrial infrastructure, with broad applications in silo design, bulk solids handling, paste rheology, fluidisation and natural hazard mitigation. We are currently looking for candidates for the following funded PhD positions:
Simulation of arbitrary, non-spherical particle shapes in DEM
In a large majority of discrete element modelling (DEM) simulations, real particles are represented by idealised geometries: typically spheres in 3D. This is computationally efficient but means that the quantitative predictions made by DEM are poor in situations where particle shape is known to be influential, e.g., angle of repose formed upon silo discharge or angle of shearing resistance in simulations of sands. In this project, a range of methods will be used to simulate non-spherical particles including rolling/twisting resistance models, rigid, multi-sphere clumps, and potential particles. These methods differ greatly in terms of computational expense. The aim of this project is to discover whether the simpler methods are often sufficient to permit a significant improvement to be achieved in simulated macro-scale behaviour with a modest increase in computational effort. Those limiting cases will be explored for which it is necessary to adopt the more accurate, computationally-expensive methods to simulate irregular particles.
Contact: Dr Kevin Hanley ([email protected]
Applicants must be of outstanding academic merit and hold (or be expected to gain) either a first class honours degree (or the international equivalent) or an MSc with distinction (or the international equivalent). Enthusiastic and self-motivated candidates are sought with a solid background in civil, mechanical, chemical engineering, or in physics and mechanics. A good grasp of mechanics and experience in programming and computational modelling would be advantageous.