Multiscale Simulations and Modeling of Particulate Flows in Oxycoal Reactors

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Multiscale Simulations and Modeling of
Particulate Flows in Oxycoal Reactors

• Sourabh Apte
• Department of Mechanical Engineering
• Funding DoE
• National Energy Technology Laboratory
• A Cihonski, M. Martin, E. Shams, J. Finn

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National Energy Technology Lab.
US Bureau of Mines---gt Albany Metallurgy Research
Center ---gt Albany Research Center---gt Now,
NETL-Albany.
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Oxy-Coal Reactors

• Pulverized coal combustion in recirculated
  mixture of flue gas and oxygen (oxygen rich
  environment)
• Nitrogen depleted environment eliminates NOx
• Completion of combustion leading to products
  rich in water vapor and CO2
• Reduced CO and flue gases means efficient
  control of emissions

• Need for carbon capture and sequestration
• O2 enriched environments lead to increased
  reactor temperatures and thermal effects
• Cost of production of pure O2 could be high

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Combustion/Gasification Hybrid
http//fossil.energy.gov/programs/powersystems/com
bustion/combustion_hybridschematic.html

• Flue gases from coal gasifier linked with a
  combustor
• Char from gasification burned in a Fluidized Bed
  for steam

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Modeling Needs

• Multiphase, multiple species, multicomponent
  heat transfer and turbulent flow problem
• Multiple spatio-temporal scales
• Particle-turbulence interactions
• Coal volatization
• Turbulent combustion
• Modeling of ash, soot particles
• Complex geometry
• Radiative heat transfer through participating
  media
• Burnout gt Metals

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Modeling Needs Particulate Flows

• Dilute and dense clusters of coal particles
• Arbitrary shapes
• Particle dispersion and interactions with
  turbulence
• Particle-particle interactions, preferential
  concentrations and structure formation
• Spatio-temporal variations in solid volume
  fractions
• Detailed experimental data for validation

Grace et al.
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Modeling Challenges Particulate Flows

• Grid Based Classification
• Fully Resolved particles larger than the grid
• Sub-grid particles smaller than the grid
  resolution
• Partially resolved particles resolved in one or
  more directions and under-resolved in others
• Temporally evolving regions

• Physics-Based Classification
• Particle size smaller than smallest resolved
  scale (Kolmogorov scale for DNS or filter size
  for LES)
• Particle size comparable to energetic eddies

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Simulation Techniques Particulate Flows
Van der Hoeff et al. Annual Review of Fluid
Mechanics, 2008
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Particulate Flow Modeling

• Fully Resolved Direct Numerical Simulation
• Develop an efficient approach for fully resolved
  simulation (FRS) of particle-laden turbulent
  flows (heavier-than fluid particles)
• Apply FRS to study interactions of sedimenting
  particles with turbulent flow and quantify drag
  and lift correlations in inhomogeneous clusters
• Large-eddy Simulation (LES) with under-resolved
  particle dynamics
• Develop an efficient approach for LES of
  turbulent flows with dense particle-laden flows
  with Discrete Element Modeling (DEM)
• Apply LES-DEM to investigate particle-turbulent
  interactions in realistic oxycoal reactors.
• Further advance LES-DEM for turbulent reacting
  flows

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Background

• Resolved Simulations of Particle-Laden Flows
• Arbitrary Lagrangian Eulerian Schemes (ALE)
  (Hirt, Hu et al.)
• Fictitious Domain Method (Glowinski, Hu,
  Patankar, Minev)
• Overset Grids (Burton)
• Lattice-Boltzmann (Ladd, ten Cate etal.)
• Immersed Boundary Methods (Peskin,Ulhmann,
  Mittal)
• Immersed Boundary with Spectral Model (PHYSALIS
  Prosperetti)
• Immersed Boundary Lattice Boltzmann (Proteus
  Michaelides)
• .

None show simulations with large density ratios
(particle-air 2000)
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Fictitious-Domain Based Approach

• Fixed background grid (structured or
  unstructured)
• Particle sizes are assumed larger than grid
  resolutions
• Assume the entire domain (even the particle
  regions) filled with a fluid
• Solve Navier-Stokes over the entire domain
  (finite volume)
• Impose additional constraints obtained from
  restricting the particle domain to undergo rigid
  body motion (translation and rotation)

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Algorithm

• Define material points/volumes within the
  particle domain
• Use color functions to identify particle domain
  (volume fraction)
• Use conservative kernels (second order) for
  interpolation of all quantities between material
  volumes and grid CVs (Roma et al.)
• Compute density using the color function

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Fractional Time-Stepping for Rigidity Constraint
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Fractional Time-Stepping for Rigidity Constraint
Patankar (2001) Apte et al. (JCP, 2008 under
review)
Advance particle positions and repeat
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Verification Studies for Fully Resolved
Simulation (FRS)
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Taylor Problem
Error in pressure
Error in velocity

• Stationary, decaying vortices
• A rotating rigid body (cube)
• Initial condition (velocity pressure) and
  velocity at material points specified

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Flow Over a Fixed Sphere
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Flow Over a Fixed Sphere
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Flow Over an Oscillating Sphere
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Freely Falling Sphere
Experiments by Ten Cate et al. (PoF 2005)
Grid 100x100x160 Time Step0.75 ms
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Freely Falling Sphere
Experiments by Ten Cate et al. (PoF 2005)
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Wake Interactions (Drafting-Kissing-Tumbling)
Same density particles
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Wake Interactions
Heavy particle
Density ratio 1.5
Rep100
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Decaying Isotropic Turbulence
cubes
spheres

• 96x96x96, 10 cvs per particle
• 125 particles, ?p/?f 9, ? 0.05
• Re? 30 St 5, 64 proc.
• Approx. 6 sec per time-step

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Isotropic Turbulence
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Can We Simulate Large Number of Particles?

• Overhead 20
• Simulations of 10,000 particles may require
  around 10 million grid points

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Subgrid Particles
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Subgrid Particles (LES-DEM)
Mixture theory based formulation Joseph and
Lundgren, 1990
Continuum phase Eulerian Dispersed Phase
Lagrangian
Continuity
Locally non-zero divergence field
Momentum
Interphase interaction force
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Subgrid Particles (LES-DEM)
Mixture theory based formulation Joseph and
Lundgren, 1990
Continuum phase Eulerian Dispersed Phase
Lagrangian
Based on a drag model Flow around particle not
resolved
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Searching and Locating Particles
n

• Criterion for Locating
• Compare face-normal vectors
• Brute Force
• Compute Minimum Distance of Droplet from CV
  Centroids
• Search CV and Neighbors to Locate Droplet
• Known Vicinity Algorithm Neighbor to Neighbor
  Search
• Lohner, R. (JCP, Vol. 118, 1995)
• Requires Good Guess of Initial Location of
  Droplet
• Search in the Direction of Particle Motion
• Most Efficient if Particle Located in lt 10-15
  attempts
• Scalar in Nature

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Performance of Search Algorithm
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Particle-laden Swirling Flow

• Experiments by Sommerfeld et al. (1991)

Dilute Loading (particle-particle interactions
negligible)
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Particle-laden Swirling Flow

• 1.6 million total hexahedral cells nearly 1.2
  million cells in region of interest

Convective Boundary condition
Convective Boundary Condition
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Particle-laden Swirling Flow
Coaxial combustor Re26,200

Apte et al, IJMF 2003
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Particle-laden Swirling Flow

• Gas Phase Statistics

Apte et al, IJMF 2003
Mean Axial Velocity
RMS of Axial Velocity
RMS of Radial Velocity
Mean Radial Velocity
Mean Swirl Velocity
RMS of Swirl Velocity
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Particle-laden Swirling Flow

• Particle Statistics

Apte et al, IJMF 2003
Mean Axial Velocity
RMS of Axial Velocity

RMS of Radial Velocity
Mean Radial Velocity
RMS of Swirl Velocity
Mean Swirl Velocity
RMS of Particle Diameter
Mean Particle Diameter
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Densely Loaded Regions Ongoing Developments

• Issues
• Need to model inter-particle interactions
• Models for collision
• Load imbalance (only few processors have
  particles) leading to loss of computing
  efficiency
• Sparse block grid
• Partition particles on a simple Cartesian mesh
  (boxes)
• Redistribute boxes among processors to balance
  load
• Solve particle equations and advance particle
  locations (searching and locating simple as
  Cartesian boxes)
• Transfer particles to appropriate processors
  partitioned based on the unstructured grid
  (Octree searches)
• Compute particle-fluid interactions forces
• Solve fluid equations.

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Gravitational Settling
Particle Evolution
Apte et al, IJMF 2008
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Rayleigh-Taylor Instability (preliminary study)
Particle Evolution
Particle void fraction