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

Yassir Makkawi

Chemical Engineering

Contents Two-fluid model for multiphase flow simulation

Limitations and challenges

Example of results

Conclusion and recommendations

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 stresses Solid-solid drag

Solid-solid energy exchange

LimitationsSlightly wet or cohesive particlesIntermediate flowPoly-dispersed particlesVarious constitutive relationsAdjustable parametersSize change during processing

Constitutive relations- example

Schematic of flow regimes and modelling

24 sopsssk geP

Kinetic theory of granular flowcollisionkinetick

soil mechanics principles

Sp ff 1sin2

criticalssqs

pcriticals

criticalss

f AP

if

if 0

max

Slightly wet or cohesive particlesCohesive particles

Slightly wet particles

Rh

Skwetfs 2

?Enduring contact

Kinetic+ collision contacts

dry wet

polydispersed mixture

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/m3) and wood (500 µm, 585 kg/m3) with the mixing ratio of 83 wt% to 17 wt%.

polydispersed mixture

Positron Emission Particle Tracking (PEPT)

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

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

�̇�=𝝐 𝒍𝝆 𝒍𝑻 −𝑻 𝒔𝒂𝒕

𝑻 𝒔𝒂𝒕

�̂�𝒗𝒐𝒍=−𝒌𝒗𝒐𝒍∗𝑪𝒗𝒐𝒍

�̂�𝒕𝒂𝒓=−𝒌𝒕𝒂𝒓 ∗𝑪 𝒕𝒂𝒓

Combustion reactionsC+ 0.5O2 → CO

2CO + O2 → 2CO2

Heterogeneous gasification reactions C + 2H2 → CH4

C + CO2 → 2CO

C + H2O → CO + H2

Homogenous reactionsCO + H2O → H2 + CO2

CH4 + H2O → 3H2 + CO

Building the reaction model- continue

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)

300 600 900 12000

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8 BiomassGas

Temperature (oC)

Hei

ght (

m)

8E-04 4E-020

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8 Biomass

Volume fraction (-)

Hei

ght (

m)

-1 0 1 2 3 4 5 6 70

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8 BiomassGas

Vertical velocity (m/s)

Hei

ght (

m)

Results: product gas composition

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.

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.

Results of parametric analysis- Effect of temperature

Consistent increase in the product gas heating value (HHV) with increasing the temperature

H2 content independent of operating temperature

CO2 decreases and CO increases with increasing temperature

The improved product gas quality (high H2 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 oC appear to be reasonable for high quality fuel.

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

Acknowledgment

Mr Mohamed Hassan (PhD student)