Experimental study of hydrodynamic correlations in 2D fluidized bed reactors for iron oxides reduction modelling

Metallic iron is a promising solid energy carrier for low-carbon energy systems, since renewable energy can be stored by reducing iron oxides and later released as heat through iron oxidation. The reduction step is typically carried out at high temperature in fluidized bed reactors, where good gas-solid contact and efficient heat and mass transfer can be achieved. In order to design and control the process, reliable models are required: iron oxides reduction models strongly depend on the correct description of bed hydrodynamics, including minimum fluidization velocity, bubble size, bubble rise velocity and gas distribution. However, most hydrodynamic correlations available in the literature were developed and validated under ambient or near-ambient conditions. Since temperature can significantly affect gas properties and bed behaviour, the applicability of these correlations under high-temperature conditions must be assessed experimentally. This thesis project aims to study hydrodynamic correlations in order to support the modelling of iron oxide reduction in fluidized bed systems. The presented work combines the formulation of a simplified two-phase reduction model, based on the Kunii-Levenspiel approach, with experimental measurements performed on non-reactive particles, namely zirconium silicate particles and glass beads. These materials are used to investigate the hydrodynamic behaviour of the bed without the additional complexity introduced by chemical reaction. Firstly, the particles are characterized in terms of particle size distribution, solid density and minimum fluidization velocity at different temperatures, in order to provide the required input data for the hydrodynamic analysis. Then, high-temperature endoscopic PIV/DIA is used as a non-invasive optical technique to investigate particle motion and flow behaviour inside a two-dimensional fluidized bed reactor placed in a furnace. The employed innovative method for optical diagnostics provides useful information to evaluate the hydrodynamic assumptions used in the reduction model and, where necessary, to improve them.