HIGH PERFORMANCE COMPUTATION (HPC) FOR THE

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1 HIGH PERFORMANCE COMPUTATION (HPC) FOR THE DEVELOPMENT OF FLUIDIZED BED TECHNOLOGIES FOR BIOMASS GASIFICATION AND CO2 CAPTURE P. Fede, H. Neau, O. Simonin Université de Toulouse; INPT, UPS ; IMFT ; Toulouse, France CNRS; Institut de Mécanique des Fluides de Toulouse ; Toulouse, France

2 MOTIVATIONS Prediction of industrial dispersed two-phase turbulent flow injection primary fragmentation secondary break-up turbulent dispersion Industrial applications: Coal fired furnaces inter-droplets interactions droplets / walls interactions vaporization combustion CFB boilers Polymerization reactor FCC riser IC engine (liquid fuel injection) Solid rocket booster Separation... Turbulent two-phase flows: Fluid-particle interaction (mass, momentum and energy transfer) Particle-particle interaction (collision, agglomeration, attrition) Particle-wall interaction (inelastic bouncing with friction, deposition) 2

3 MOTIVATIONS CFD approaches dedicated to the numerical prediction of gas-particle reactive flows are becoming powerful tools to support: - the development of new concepts, - the scaling up (laboratory pilot industrial), - the optimization of existing processes. the physical modeling and numerical prediction of many phenomena remain an open challenge. 3

4 MOTIVATIONS/METHODOLOGY Microscopic scale (~1mm) DNS, immersed boundary method Mesoscopic scale (~10cm) DNS/LES + Discrete Particle Simulation (DPS) Macroscopic scale (~10m) RANS, Euler-Euler MeOx concentration field. NEPTUNE_CFD bi-solid prediction of the circulating fluidized bed coal combution reactor (chemical looping fuel reactor) 4

5 MATHEMATICAL MODEL EULER-EULER POLYDISPERSE APPROACH Closure of the kinetic transport equation on the single particle PDF based on a Lagrangian modeling of particle-fluid, particle-particle and particle-wall interactions. Derivation of the moment transport equations (concentration, velocity, temperature, fluctuating motion kinetic energy, kinetic stresses ) and the transport properties (viscosity, diffusivity). Validation from Euler-Lagrange numerical experiments Implementation in NEPTUNE_CFD and comparison of model predictions with experimental measurements (laboratory, pilot and industrial scales). 5

6 MATHEMATICAL MODEL EULER-EULER POLYDISPERSE APPROACH Mass balance equation Momentum balance equation Gas-particle momentum transfer particle relaxation time particle Reynolds number mean gas-particle relative velocity Particle-particle momentum transfer 6 6

7 MATHEMATICAL MODEL NUMERICAL SOLVER Neau, Laviéville, Simonin, ICMF 2010 Neau, Fede, Laviéville, Simonin, Fluidization XIV, 2013 NEPTUNE_CFD computation efficiency: 38,000,000 cells 3,150,716 cells 7

8 MATHEMATICAL MODEL NUMERICAL SOLVER Neau, Laviéville, Simonin, ICMF 2010 Neau, Fede, Laviéville, Simonin, Fluidization XIV, 2013 NEPTUNE_CFD computation efficiency: Full mesh cells 500 x x y z 1cm 3 8

9 MATHEMATICAL MODEL NUMERICAL SOLVER NEPTUNE_CFD computation efficiency: Neau, Laviéville, Simonin, ICMF 2010 Neau, Fede, Laviéville, Simonin, Fluidization XIV,

10 MATHEMATICAL MODEL NUMERICAL SOLVER NEPTUNE_CFD computation efficiency: Neau, Laviéville, Simonin, ICMF 2010 Neau, Fede, Laviéville, Simonin, Fluidization XIV, 2013 x5 x5 10

11 B-Type particle according to Geldart classification 11

12 SCALE-UP 12

13 DENSE LAB-SCALE FLUIDIZED BED OF B-TYPE PARTICLES Time-averaged mean solid velocity normalized by the fluidization velocity The no-slip wall boundary conditions on the mean solid velocity improves the numerical predictions. However such boundary conditions are not physical. 13

14 DENSE INDUSTRIAL-SCALE FLUIDIZED BED OF B-TYPE PARTICLES 14

15 DENSE INDUSTRIAL-SCALE FLUIDIZED BED OF B-TYPE PARTICLES 15

16 A- or A/B- Type particle according to Geldart classification 16

17 CHEMICAL LOOPING Given conditions: Gas fluidization and fresh carbon injection, MeOx solid inventory, Carbon reaction rate, Cyclone «cut-off» diameter. Results: Pressure drop, MeOx circulating mass flow rate. 17

18 CHEMICAL LOOPING Peculiar fluidized bed operating conditions: Mixture of particle species with a large contrast in diameter and density: MeOx particles: d p ~ 200 µm, p ~ kg/m 3 Coal (+ ash) particles: d p < 50 µm, p ~ kg/m 3 Particle relaxation time ratio > 50 Particle settling velocity ratio > 40 Local effective production of gas in the fuel reactor due to the coal gazeification. 18

19 EFFECT OF UNRESOLVED SOLID STRUCTURES CIRCULATING FLUIDIZED BED OF A-TYPE PARTICLES Influence of the mesh refinement: Mesh refinement Δx = 14cm Δx = 10cm Δx = 3cm 19

20 EFFECT OF UNRESOLVED SOLID STRUCTURES CIRCULATING FLUIDIZED BED OF A-TYPE PARTICLES Influence of the mesh refinement: Computation time 1 month 10 minutes 20

21 EFFECT OF UNRESOLVED SOLID STRUCTURES HOW TO ANALYZE/MODEL THE EFFECT OF SUBGRID SOLID STRUCTURE Numerical simulation of large-scale industrial CFB α p Limitation of computational resources leads to use relatively too coarse mesh for detailed prediction of the meso-scale structure Bad prediction of the meso-scale structures Fine grid Δ=1 cm Coarse grid Δ=10 cm Dramatic influence on bed hydrodynamics (solid flux, bed height, ) Mesh independent results useful for: Development understanding/modeling of an of the approach effect of meso-scale allowing solid to structures perform model numerical validation simulation with a reasonable mesh 21

22 EFFECT OF UNRESOLVED SOLID STRUCTURES MESH INDEPENDENT RESULTS Mesh independent simulation: Periodic ~10m 22

23 EFFECT OF UNRESOLVED SOLID STRUCTURES MESH INDEPENDENT RESULTS Mesh independent simulation: Mesh refinement 23

24 EFFECT OF UNRESOLVED SOLID STRUCTURES BUDGET ANALYSIS Filtered solid momentum balance equation Ozel, Fede & Simonin, IJMF

25 SUBGRID MODEL DERIVATION Subgrid fluid-particle momentum exchange model By definition we have If we assume that the computed drag is composed of a filtered gas-solid relative velocity and a drift velocity then Then we get 25

26 MODEL VALIDATION 2D DENSE FLUIDIZED BED Mesh ind. results Without sgs model With sgs model 26

27 MODEL VALIDATION PERIODICAL CIRCULATING FLUIDIZED BED With Subgrid model Fr 1 = ( ) Fr 1 = ( ) Fr 1 = ( ) 27

28 MODEL VALIDATION PERIODICAL CIRCULATING FLUIDIZED BED Solid mass flow rate Coarse mesh Without model Coarse mesh With model 28

29 CONCLUSIONS, PROSPECTS & CHALLENGES Conclusions: Mesh-converged Euler-Euler numerical simulations are crucial for understanding the role of sugbrid solid structures The subgrid drag term is the first order in magnitude, and subgrid Reynolds stresses can be important Models for subgrid drag have been proposed: functional functional with dynamic computation of constant tensorial model (not presented here) Models for subgrid Reynolds stresses have been proposed (Smagorinsky, and Yoshizawa like) 29

30 CONCLUSIONS, PROSPECTS & CHALLENGES Prospects & challenges: Effect of sugbrid solid structures in polydisperse Euler-Euler simulation (FP 7 EU Project NANOSIM) Effect of coarse mesh in reactive Euler-Euler simulation (FP 7 EU Project NANOSIM) Effect of attrition/fragmentation in numerical simulation (FP 7 EU Project SUCCESS) Taking into account combustion in numerical simulation (FP 7 EU Project SUCCESS) 30