Creating robust empirical and computational models of the process of deposition of salts, dust, sand and volcanic ash has gained increased importance over the last two decades as civil aircraft flights in regions with particulate laden atmospheres have increased. This is associated with increased costs of maintenance to engine suppliers in a market where there is pressure from carriers to continue to fly. Thus, knowledge of the build-up of particulates within the engine over long or multiple deposition events is required in addition to predicting its onset. In this paper deposition in idealised geometries typical of internal cooling passages is examined. The fluid phase is modelled using the commercial flow solver FLUENT and a simple RANS approach. The discrete phase was then solved using Lagrangian particle tracking and a continuous random walk model using one-way coupling. Following identification of deposition fluxes, the local surface of the solid domain was modified using a bespoke cell transformation process. Particular care was taken to distribute deposited mass appropriately to surface cells to avoid large discontinuities at the boundaries. The model was implemented using user-defined functions. The functionality of the technique, is demonstrated through application two impingement cooling geometries for which experimental validation data are available. Here the solution was highly sensitive to the changing target surface geometry as deposition advanced temporally. Fair agreement was found with the experimental data of Burwash et al.[1] though the level of accretion found was an order of magnitude too high, highlighting the need to combine this approach with accurate stick-bounce and shedding models. Significant changes in deposition locations were observed as the deposition site grew in size. Comparison to a second validation case, by Clum et al [2], was used to test further the effect of deposition on the local flow field. Again, good qualitative agreement was obtained. The procedure is shown to create believable deposits of volcanic ash for all cases tested, without many of the typical problems encountered with mesh morphing — overlapping volumes and indeterminate boundary layer resolution. For the commercial computational fluid dynamic (CFD) code used, the process of identifying cells which are to be modified and their neighbours is, disappointingly, an order of magnitude slower than using a mesh morphing strategy. The procedure does, however maintain high, known, resolution throughout the thermal boundary layer, will allow the redistribution of particles to take into account features such as the fusing of neighbouring accretions and the breakaway of deposits from the surface as they grow.

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