The NRC is a joint venture between The University of Bristol and The University of Oxford, a collaboration that intends to provide leading edge and innovative research to support the safe operation of current and future generation nuclear systems.

The conference on the 8th of October invites scientists and engineers to present their own R&D findings, while discussing all aspects of managing the UK radioactive waste legacy, including:- decommissioning technologies, waste characterisation, treatment, packaging and disposal, site remediation and radiation effects.

MMI has been heavily involved with the conference’s subject matter, joining a Technology Strategy Board (TSB) funded industry-academic collaboration alongside Sellafield Ltd and The University of Leeds with the intention of overcoming major processing issues surrounding legacy wastes. The project aims to reduce the costs associated with sludge transfer and to enhance process efficiency. With regards to the latter, MMI is to develop a ‘drift-flux’ model of particle separation within a Computational Fluid Dynamics (CFD) environment, enabling the prediction of sludge settling efficiency in different systems. David Burt of MMI will discuss this framework at the NRC Conference, expanding upon key features and findings:-

“The critical feature of this model will be the incorporation of particle breakup and agglomeration characteristics in the model framework, which is necessary due to the break-up of particles during pumping transfer and the likely re-agglomeration within the sludge settlers themselves. Simulations of particle flows under various turbulent flow regimes will enable us to track particle settling behaviour, agglomeration and break-up – providing significant input and validation data that will be utilised in the drift-flux model and CFD as a whole. The result will be a fully validated drift-flux model of particle settling in large-scale corrals for prediction of sludge transfer behaviour.”

For more information surrounding the conference, please visit