Sediment transport and deposition
The research began with Dr Stovin's PhD, which - in 1996 - pioneered the use of CFD as a practical engineering tool, specifically considering the prediction of sediment deposition in combined sewerage storage chambers [Papers 1, 2, 5, 7, 10]. Lagrangian discrete phase modelling (particle tracking) was utilised for sediment transport modelling. This approach has also been applied to the design of CSO chambers [Papers 3 and 4] and sewer invert sediment traps [Buxton PhD; Papers 6, 9 and 13]. User-defined subroutines have been exploited to refine the deposition criteria [Paper 10]. Some experience of multiphase modelling for sewer sediment deposition and accumulation has also been gained [EPSRC project report].
Solute transport and dispersion
Recent work has focused on the modelling of dispersion effects, collaboratively with Professor Ian Guymer (University of Warwick).
Fred Sonnenwald and Mahshid Golzar are working on an EPSRC-funded project to develop practical simulation tools aimed at understanding how vegetation affects solute transport in stormwater ponds.
John Grimm undertook rigorous evaluations of both an unsteady species transport model and a discrete phase model (using tiny, neutrally-buoyant particles) in terms of their ability to reproduce measured solute transport behaviours within a straight pipe flowing full [Grimm PhD].
This approach was subsequently applied to a broader range of urban drainage ancillary structures [Paper 23].
Douglas Lau developed this work in the context of dispersion due to surcharged manholes, with particular reference to scale effects [Lau PhD, Papers 18, 19, 21, 22 and 25]. The most significant finding from his work was the observation that the solute transport characteristics of a surcharged manhole could be described using just two dimensionless Cumulative Residence Time Distribution (CRTD) curves [Papers 25 and 28.
As part of this work, and in collaboration with systems engineering colleagues Mike Chappell and John Hattersley, we have developed novel deconvolution techniques that enable CRTDs to be identified from (noisy) laboratory data [Paper 24 and 26]. Fred Sonnenwald's PhD focused on the further development of deconvolution tools [Paper 29].
The validity of a range of (high Reynolds number) turbulence models has been examined with respect to a range of different hydrodynamic contexts:
Opportunities for future work
Key areas for future work have been identified as follows: