DEVELOPMENT OF SLURRY MIXING MODELS USING RESISTANCE TOMOGRAPHY

The design, modelling and simulation of solid-liquid mixers remains on e of the least advanced aspects of particulate processing due to diffi culties in quantifying complex slurry hydrodynamics from first princip les and in acquiring reliable experimental data for model verification and development. This contribution describes the application of elect rical resistance tomography (ERT) for three-dimensional imaging of the concentration of solids in a slurry mixer as a function of key proces s variables (particle size, impeller type, agitation speed). It is dem onstrated how ERT can provide a wealth of detailed data to allow model development, which ultimately will lead to much improved design capab ilities and the generation of mixing models which could reside within particle process simulators. This principle is illustrated using descr iptions of mixer behaviour based on an empirical approach, although th e measurement methodology described is equally suited to development o f computational fluid dynamics models, cellular models or design appro aches based on artificial intelligence. It is demonstrated that ERT ca n be used for routine acquisition of experimental information thereby accelerating the development of empirical correlations for design and scale-up. The experimental data can be built into a visualization data bank, which acts as a 'process toolkit' by allowing a library of proce ss responses to be catalogued. Hence these data can be accessed for th e purposes of model development, equipment selection, optimization of operating conditions or testing on-line control strategies.