Modelling the degradation of particles in fluidised beds

Abstract

This thesis focuses on modelling the degradation of particles in gas-solid fluidised beds. Modelling is performed by using a coupled approach where the gas phase is treated as a continuum and the solid phase is represented by individual discrete particles, using the discrete element method (DEM). This approach makes it possible to access individual particle properties. By implementing new modelling techniques into the DEM framework, the individual particle degradation behaviour can be numerically described with high accuracy. The main interest is to understand more complex gas-solid systems as encountered e.g. in fluidised beds which might contain numerous degrading particles. This work focuses on verifying and validating these sub-models to be able to obtain accurate information for further suggestions in operation and optimisation of dense particulate systems.

Particle degradation is studied by means of thermophysical, thermochemical and mechanical aspects. Drying (thermophysical) is an energy intensive process which makes further research inevitable for further optimisation. Large particles during drying develop temperature and species gradients along their radius, affecting the product quality. The DEM has been used to monitor flow, particle and subparticle properties which have been found useful to control, operate and optimise such large particle drying processes. Pyrolytic (thermochemical) conversion of biomass in fluidised beds represents a promising route for the production of biooil. This process has been modelled and studied under consideration of drying, shrinkage, segregation and entrainment. Breakage or mechanical degradation is often encountered in engineering applications and requires a much better process understanding. Therefore, a new discrete fragmentation method (DFM) has been developed to study breakage in dense particle systems such as fluidised beds but also mills or crushers. Much reliable breakage information can be obtained to further optimise such systems.

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