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1
UQ for Turbulent Fluid Mixing
James Glimm1,3
Stony Brook University
With thanks to:
Wurigen Bo1, Baolian Cheng2, Xiangmin Jiao1, T. Kaman1, Hyun-KyungLim1, Xaolin Li1, Roman Samulyak1,3, David H. Sharp2, Justin Iwerks1,Yan Yu1
1. SUNY at Stony Brook2. Los Alamos National Laboratory3. Brookhaven National Laboratory
2
Some DefinitionsTurbulence
Active vortices on many length scales
MixingTwo or more fluids in (turbulent) flow
Hot-cold water; salt-fresh water; oil-water
Instabilities generated by acceleration or shearSteady acceleration: Rayleigh-TaylorImpulsive acceleration: Richtmyer-MeshkovShear: Kelvin-Helmholtz
3
Multiscale, so a challenge for computation. This lecture: LES
Direct Numerical Simulation (DNS)Resolve all important scales
Large Eddy Simulation (LES)Resolve the large but not the small turbulent scalesModel scales not resolved
Reynolds Averaged Navier-Stokes (RANS)Model all turbulent scales
4
LES regimeThe (laminar) viscosity and mass diffusion are small
Equations are Euler like
But the effects of the unresolved terms are diffusive, generating turbulent viscosity and turbulent mass diffusion, which are not small
Solutions need to be Navier-Stokes like
5
Convergence in the LES regimeLES regime is inherently stochastic
Convergence of probability distribution functions (pdfs) Pdf indexed by space time = Young measureLimit = Pdf solution (Young measure) of Euler equation
Verification: fine grid agrees approximately with course grid?
Fine grid pdf should be sampled, not averaged, to agree (approximately) with coarse grid pdfSimpler: convergence of mean, variance, higher moments
Mean, variance etc. generated by variation of fine grid solution over the coarse solution resolution scale
6
A mathematical theorem (G-Q Chen, JG; also others?)
Incompressible Euler equationsAssume Kolmogorov 1941 turbulence bounds
Fluctuations in velocity satisfy an integrable power law decayThus velocity belongs to a Sobolev spaceBounds and convergence (through a subsequence) to a classical weak solution follows
Couple to passive scalar (mixing)Volume fractions are bounded, thus w* convergence (subsequences), as a pdf to a pdf limit, i.e. a Young measure solution of the concentration equation coupled incompressible Euler solution
7
Conceptual Picture conjectured(compressible or active scalars for incompressible)
Euler equation andLES simulation of Navier Stokes equation
Is inherently stochasticSolution is a pdf (Young measure)Convergence is convergence of pdfsConsistent with view of DNS and Navier-Stokes as having smooth solutions
8
Numerical algorithm for LES turbulent mixing: Front Tracking + turbulence models
Capturing: Computation with steep gradients, rapid time scales
Tracking is an extreme version of this idea
Turbulence models: Good subgrid modelsBest of two ideas combined
9
Central Features of Combined Algorithm
Tracking allows very steep gradient at a numerical level
Subgrid scale (SGS) models ensure proper choice of turbulent transport
Dynamic SGS models have no free parametersnumerical Schmidt number = physical Schmidt number?A good idea in general, or a lucky accident?
10
Geometry preservation, accuracy and high (subgrid) resolution
Geometry preservation Subgrid resolution
Accuracy
64x64x64
128x128x128
2D
3D
11
Robust geometry and topology functions
Robust topological bifurcation
Efficient mesh deformation
Robust mesh merging
12
Subgrid models for turbulence, etc.
Typical equations have the formAveraged equations:
( )tU F U Uε+∇ = Δ
( )
( ) ( )
( ) ( ) ( )
t
SGS
U F U U
F U F U
F U F U F U
ε+∇ = Δ
≠
≈ +
is the subgrid scale model and corrects for grid errorsSGSF
13
Subgrid models for turbulent flow
( ) ( ) ( )
( ) ( )( )
( ) ( )turbulent
turbulent
(key modeling step)
SGS
t SGS
SGS
t
F U F U F U
U F U U F U
F U U
U F U U
ε
ε
ε ε
≡ −
+∇ = Δ +∇
∇
+∇ = + Δ
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Dynamic Sub Grid Scale (SGS) ModelsNo Free Parameters!
xΔ2
Missing coefficient determined at xΔ2
xΔ
Transfer coefficient to xΔ
Coarsening
SGS by model formula at xΔ2 Close SGS
model
xΔ2
15
Tests of numerical algorithmsVerification
Does the numerics solve the mathematical equation? Requires proof of convergence
ValidationIs the physical problem solved?
Requires comparison to experiment or observational data
Uncertainty QuantificationWhat kind of bounds (error bars) can be established for the combined effect of errors of all types?
16
Tests, continued: What to measure?
Macro variablesOuter boundary of mixing region
Meso variablesCoherent structures in flow
Micro variablesMeasures of molecular mixing
Pdf of species concentrationFirst, second moment of species concentration
17
Tests in context of applications(we will know if we are wrong!)
Hydro instabilitiesRayleigh-Taylor and Richtmyer-Meshkov
ICF applications
Turbulent mixing and combustionScram jet applications
Mixing in Couette flowSpent nuclear fuel separation
Crystal growthNuclear fuel; porous media applications
Diesel sprayDroplet size in primary jet beakup
18
Rayleigh-Taylor Instable MixingLight fluid accelerates heavy
Across a density contrast interface
Overall growth of mixing regionMolecular mixing: second moment of concentration
2
2 1
2 1
acceleration force
(1 )1
h Agt
A
g
f ff f
αρ ρρ ρ
θ
=−
=+
=
⟨ − ⟩=⟨ ⟩⟨ − ⟩
19
Simulation study of RT alpha forSmeeton-Youngs experiment #112
Agreement with experiment (validation)Agreement under mesh refinement (verification)Agreement under statistical refinement (verification)Agreement for Andrews-Mueschke-Schilling alpha (code comparison; different experiment)Agreement within error bounds established for uncertain initial conditions (uncertainty quantification)
20
Experiment : V. S. Smeeton and D. L. Youngs, Experimental investigation of turbulent mixing byRayleigh‐Taylor instability (part 3). AWE Report Number 0 35/87, 1987Simulation : H. Lim, J. Iwerks, J. Glimm, and D. H. Sharp, Nonideal Rayleigh‐Taylor Mixing
The simulations reported here were performed on New York Blue, the BG/L computer operated jointly by Stony Brook University and BNL.
Simulation-ExperimentComparison Movie
21
Uncertainty quantification regarding possible long wave length perturbationsReconstruction oflong wave lengthinitial perturbationssimulated at +/- 100% to allowfor uncertaintyin reconstruction.Net effect: 10%for alpha.
22
Molecular level mixing: second moment of concentration 2 experiments, 3 simulations (one DNS) compared
23
3D Simulation for Primary Jet Breakup
Work done by W.Bo, Stony Brook UniversitySimulation is performed at NewYorkBlue (A 126Tf BGL/P at Stony Brook/BNL)
24
Scram jet: H2 injection into M = 2.4 cross flow: Mixing Only
Black dots are the flame frontextracted from the experimentalOH-PLIF image.
25
Scram jet: Mixing Only
H2 mass fraction contour plotted at the midline plane
26
Crystal growth unstable regime Da = 285
27
Two phase Couette flow in a fluid contactor.
Simulation of a smallangular sector
Used in chemical processingfor separation of spentfuel from nuclear powerreactors
28
ConclusionsReacting, turbulent, mixing flows require
LES solutionsControl over numerical mass diffusion (front tracking)Subgrid scale turbulence modelsPdf convergenceV&V+UQTesting in realistic examples where “truth” is known
Partial results on all of the above was presented