CFD modelling of marine discharge mixing and dispersion

Abstract

Many municipal and industrial outfalls release effluent into water bodies. Temperatures and/or salinities of the effluent and receiving water may be different, and other dissolved/suspended constituents may be present. Away from the outfall, mixing processes usually reduce constituent concentrations to acceptable levels for local water quality. However, at the outlet, concentrations may be sufficient to cause environmental concern. Accurate dispersion prediction is therefore important. Two-stage modelling approaches are typically used: (1) a near-field dilution assessment, based on mixing zone or empirical models; and (2) a mid- /far-field dispersion assessment, using hydrodynamic models. As computational and numerical methods improve, computational fluid dynamics (CFD) can increasingly model dispersion across both regions. These methods require validation of the underlying discretisation and turbulence schemes. Preliminary validation is presented for near-field simulations of buoyant and dense jets. Buoyant jet predictions compare well with established results. Preliminary simulations under-predict entrainment into the dense jet, overly-predicting near-field concentrations.

Keywords:

• CFD
• desalination
• dilution
• dispersion
• jets
• mesh adaptivity

Acknowledgments

The authors gratefully acknowledge the support of HR Wallingford Ltd, who is providing funding for this ongoing Doctoral research. Also, Imperial College London's High Performance Computing Service for HPC resource and time, and ARCHER, the UK National Supercomputing Service. The authors are very grateful for the insightful comments of two anonymous reviewers whose input significantly improved the quality of this paper, and helped clarify some of the key technical issues discussed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

David Robinson is a PhD student within the AMCG Group developing CFD code ‘Fluidity’ at Imperial College London. His thesis title is ‘Multi-scale modelling of effluent dispersal within the marine environment’. He is funded by (and works part time for) HR Wallingford. Before starting his PhD, he spent six years as an Engineer at HR Wallingford, where his role included physical and computational modelling of hydraulic structures and coastal defence.

He has a Masters degree in Mechanical Engineering and is an associate member of the IMechE. His physical modelling experience includes testing breakwaters in India and Brazil, sea walls on the English South Coast and ports in Rotterdam, Dover and Tristan Da Cuna. He has computational modelling experience of jet dynamics, dispersion, tidal flow, wave–current–structure interaction and air flow over reservoirs.

Matthew Wood is a Principal Scientist at HR Wallingford Ltd., specialising in environmental hydraulics and pollutant dispersion modelling. Matthew has over 10 years' experience as a researcher and a consultant on water quality, thermal/saline impact, pollutant and sediment transport, and the effects of reclamations in marine waters. He has particular expertise in marine outfall optimisation, and the innovative application of computational models to support environmental and engineering decisions. He is a member of the International Water Association/International Association for Hydro-Environment Engineering and Research's Joint Committee on Marine Outfall Systems.

Matthew Piggott is Grantham Reader in Ocean Modelling at Imperial College London. He holds a PhD in Mathematics from the University of Bath and works in the general areas of computational physics and geophysical fluid dynamics. He has been at Imperial College London since 2011 and now holds the position of Reader in the Department of Earth Science and Engineering. Specific research interests include the development and application of multi-scale simulation methods using anisotropic adaptive mesh methods, unstructured meshes and finite element discretisation methods.

Gerard Gorman is a Senior Lecturer at Imperial College London. His research interests include high performance computing, parallel algorithms and multi-physics, and multi-scale model development.