DEM and CFD–DEM meso-particle modelling of mixing processes

Host Institutions

University of Twente [ 12 months ]
DCS Computing [ 24 months ]

Closing Date:

Thursday 15, April 2021

Develop a meso-particle model to predict segregation and mixing behaviour of large industrial mixing systems.

Specific objectives are:
  1. Develop spatial and temporal filters to derive sub-parcel models and/or correlations to correct for the impact of the non-resolved part of the physics in meso-particle simulations; address the fundamental challenge of modelling the micromechanics to predict mixing and segregation;
  2. Develop DEM and CFD–DEM based simulation methodology using meso-particle scale-up and compare to fully resolved DEM models;
  3. Apply to selected large industrial mixers at BASF/Procter & Gamble and validate predictive capabilities.
Expected Results:
  1. Literature study and existing model evaluation; choice of methods;
  2. Report simulation data and proposed correlations laws for use in sub-parcel models for meso-particle modelling;
  3. Sub-parcel models for meso-particle modelling of segregation and mixing established, calibrated and validated;
  4. Industrial application (mixing system) established and validated.

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