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 : fluid Gas-solid drag Solid stressesSolid-solid drag 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 Kinetic theory of granular flow soil mechanics principles

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

8. polydispersed mixture

9. 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. 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/m 3 ) and wood (500 µm, 585 kg/m 3 ) with the mixing ratio of 83 wt% to 17 wt%. polydispersed mixture 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: O 2, N 2, CO, H 2, CH 4, CO 2, tar, and H 2 O  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.  Drying  Is modelled as mass transfer mechanism:  Devolatilization and tar cracking  Partial combustion and gasification reactions  Combustion reactions  Heterogeneous reactions  Homogenous reactions Latest trends- modelling of reactive system

12.  Combustion reactions C+ 0.5O 2 → CO 2CO + O 2 → 2CO 2  Heterogeneous gasification reactions C + 2H 2 → CH 4 C + CO 2 → 2CO C + H 2 O → CO + H 2  Homogenous reactions CO + H 2 O → H 2 + CO 2 CH 4 + H 2 O → 3H 2 + CO Building the reaction model- continue

13. Results: hot flow hydrodynamics  Gasifier operating at: Inlet sand temperature of 900 o C; 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  Contours of gas concentration in the reactor. Solid inlet temp 1200 o C, ER=0.1, steam-to- biomass ratio =0.6, biomass feed=18 kg/h.  Steady exit gas composition at 900 o C solid inlet temperature; ER=0.1; steam- to-biomass ratio = 0.6  Tar content in the exit gas is 3.7 g/Nm 3.

15. Results of parametric analysis- Effect of temperature  Consistent increase in the product gas heating value (HHV) with increasing the temperature  H 2 content independent of operating temperature  CO 2 decreases and CO increases with increasing temperature  The improved product gas quality (high H 2 and HHV) here is due to the increase in the gasifer throughput, 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 o C 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. Acknowledgment Mr Mohamed Hassan (PhD student)