Two-fluid models for fluidized bed reactors: Latest trends and challenges Yassir Makkawi

1. Two-fluid models for fluidized bed reactors: Latest trends and challenges Yassir Makkawi Chemical Engineering

2. Contents • Two-fluid model for multiphase flow simulation • Limitations and challenges • Example of results • Conclusion and recommendations

3. Two-fluid model • Mathematical formulation to describe the interaction of two fluids by treating the phases as interpenetrating continua • e.g. solid momentum • Kinetic energy • PDE : • Algebraic : Gas-solid drag fluid Solid-solid drag Solid stresses Solid-solid energy exchange

4. Limitations • Slightly wet or cohesive particles • Intermediate flow • Poly-dispersed particles • Various constitutive relations • Adjustable parameters • Size change during processing

5. Constitutive relations- example

6. Schematic of flow regimes and modelling soil mechanics principles Kinetic theory of granular flow

7. ? R h Slightly wet or cohesive particles Cohesive particles dry wet Slightly wet particles Kinetic+ collision contacts Enduring contact

8. polydispersed mixture

9. polydispersed mixture Solution of the Energy equation Comparison of predicted and measured cross-sectional average solid velocity for the case of a polydispersed binary mixture of glass beads (755 µm,2500 kg/m3) and wood (500 µm, 585 kg/m3) with the mixing ratio of 83 wt% to 17 wt%. Granular temperature predicted by two different solution methods of the energy equation. Data produced with particle size of 755 µm fluidized by air at 4.7 m/s at the solid circulation rate of 36.g/s. Positron Emission Particle Tracking (PEPT)

10. Building a biomass gasifier model • 3D model is considered to simulate the gasification of Biomass using Fluent. • two solid phases are modelled as mixture: • Gas phases: O2, N2, CO, H2, CH4, CO2, tar, and H2O • Solid phases: Biomass mixture of C(s), volatiles and ash. • Sand is introduced as an inert solid phase • The gasification model is based on three main steps: (i) Drying (ii) Devolatilization and tar cracking (iii) Partial combustion and gasification reactions

11. Latest trends- modelling of reactive system • Drying • Is modelled as mass transfer mechanism: • Devolatilization and tar cracking • Partial combustion and gasification reactions • Combustion reactions • Heterogeneous reactions • Homogenous reactions

12. Building the reaction model- continue • Combustion reactions C+0.5O2→CO 2CO+O2→2CO2 • Heterogeneous gasification reactions C + 2H2→ CH4 C + CO2→ 2CO C + H2O → CO + H2 • Homogenous reactions CO + H2O → H2 + CO2 CH4 + H2O → 3H2 + CO

13. Results: hot flow hydrodynamics • Gasifier operating at: Inlet sand temperature of 900 oC; ER=0.1; biomass-to-steam ratio of 0.6; biomass feed rate of 20 g/s (7.2 kg/h)

14. Results: product gas composition • Steady exit gas composition at 900 oC solid inlet temperature; ER=0.1; steam-to-biomass ratio = 0.6 • Tar content in the exit gas is 3.7 g/Nm3. • Contours of gas concentration in the reactor. Solid inlet temp 1200 oC, ER=0.1, steam-to-biomass ratio =0.6, biomass feed=18 kg/h.

15. Results of parametric analysis- Effect of temperature • H2 content independent of operating temperature • CO2 decreases and CO increases with increasing temperature • Consistent increase in the product gas heating value (HHV) with increasing the temperature • The improved product gas quality (high H2 and HHV) here is due to the increase in the gasiferthroughput, which in this case: 50 g/s (18 kg/h) for biomass and 30 g/s (108 kg/h) for sand. • The operating temperature of ~900 oC appear to be reasonable for high quality fuel.

16. Conclusion and recommendations • Two-fluid modelling is so far the most reliable for the simulation of solid-gas fluidized bed reactors. • The development and improvement of predictive capabilities of the two-fluid model is moving at a faster pace than the alternative Discrete Element Modelling. • Great success in simulating complex reactive system. • More effort is required: • To reduce computational time • Inter-particle forces • Particle size distribution and physical change

17. AcknowledgmentMr Mohamed Hassan (PhD student)