DISTINCTIVE is a multi-disciplinary collaboration of 10 universities and 3 key industry partners from across the UK’s civil nuclear sector.
PhD/PDRA – PDRA
Academic Leads – Mike Fairweather, Tim Hunter, David Harbottle
Researchers – Hugh Rice and Derrick Njobuenwu
University – University of Leeds
Experimental: Current understanding of the flow and settling dynamics of nuclear waste suspensions and sludges is poor due both to the complex nature of the particle phase, its interaction with the fluid phase, the influence of flocculation and other time-dependent properties, as well as a scarcity of useful data for such materials and flows and the physical, chemical and radiological difficulties in gathering such data from real waste repositories. The first PDRA position concerns experimental work using realistic sludge simulants (based on recipes supplied by the National Nuclear Laboratory and Sellafield Ltd.) with a range of particle sizes, densities and shapes, both aggregating and non-aggregating, and their flow behaviour in horizontal and vertical pipes of circular cross-section, and in continuous- and batch-settling vertical columns. Novel, on-line, in-situ ultrasonic methods recently developed will be used to characterise the suspension, settling and segregation of these flows. In particular, the following properties will be investigated: mean velocity and turbulent stress fields, using ultrasonic Doppler velocimetry; particle concentration profiles, using a dual-frequency inversion method and acoustic backscatter strength; limit deposition velocity at which all solids remain suspended, using bed depth measurements (pipe flow only); and pressure drop and rheological properties, using a series of pressure transducers (pipe flow only).
Simulation: Predictions of similar flows will be obtained using a coupled large eddy simulation/Lagrangian particle tracking technique, with the influence of levels of turbulence, and the direction of gravity, on particle agglomeration and settling behaviour, and the shear break-up of particle aggregates explored. Model predictions will be compared with the data to be gathered to provide a validated predictive technique for complex particle-laden flows in closed pipes with geometries relevant to nuclear waste processing operations. The techniques developed will also be useful in the formulation and validation of the more pragmatic modelling approaches used within the industry in the design and operation of waste management processes.
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