Presented by

Ramanan SankaranEvatt R. Hawkes

Chunsang YooDavid O. Lignell

Jacqueline H. Chen (PI)Combustion Research Facility

Sandia National Laboratories, Livermore, CA

High Fidelity Numerical Simulationsof Turbulent Combustion

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Combustor size~1m

Molecularreactions ~ 1nm

Direct numerical simulation (DNS) of turbulent combustion

DNS Approach and Role

Fully resolve all continuum scales without using sub-grid models

Only a limited range of scales is computationally feasible

Terascale computing = DNS with O(103) scales for cold flow.

DNS is limited to small domains. Device-scale simulations are out of reach

Turbulent Combustion involves coupled phenomena at a wide range of scales

O(104) continuum scales

Turbulent Combustionis a Grand Challenge

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S3D – Sandia’s DNS solver

DNS provides unique fundamental insight into the chemistry-turbulence interaction

Solves compressible reacting Navier-Stokes equations

High fidelity numerical methods

8th order finite-difference

4th order explicit RK integrator

Detailed chemistry andtransport models

Multi-physics (sprays, radiation and soot) from SciDAC-TSTC

Ported to all major platforms

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S3D - Parallel Performance

90% parallel efficiency on 5000 XT3 processors

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XT37200 cores

XT34800 CPUs

X1E512 MSPs

Performed on

1.2M500K200kCPU-hours

200M88M52MMesh

1063u Õ/S L

XT37200 cores

XT34800 CPUs

X1E512 MSPs

Performed on

1.2M500K200kCPU-hours

200M88M52MMesh

1063u Õ/S L

DNS of lean premixed combustion Goals

Better understanding of lean premixed combustionin natural-gas-based stationary gas turbines

Model validation and development

Simulation details Detailed CH4/air chemistry; 18 degrees of freedom Slot burner configuration with mean shear Laboratory configuration and statistically stationary

-Better suited for model development A unique and first-of-its-kind DNS Three different simulations at increasing turbulence

intensities to clarify the effect of turbulent stirringon flame structure and burning speed

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1/4

1/2

3/4

FreshBurned

u’/SL=3 u’/SL=6

Effect on flame structure

Progress variable defined based on O2 mass fraction

Instantaneous slices shown on the left for Case 1

Progress variable from 0 (blue) to 1 (red) in color

Heat release rate as line contours

Considerable influence on preheat zone

Reaction zone relatively intact

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Hawkes, Sankaran, Sutherland, Chen - 2006

DNS of extinction/reignition in a jet flame Understanding extinction/reignition

in non-premixed combustion is key to flame stability and emission control in aircraft and power producing gas-turbines

The largest ever simulations of combustion have been performedto advance this goal:

500 million grid points

11 species and 21 reactions

16 DOF per grid point

512 Cray X1E processors

30 TB raw data

2.5M hours on IBM SP NERSC (INCITE); 400K hours on Cray X1E (ORNL)

Scalar dissipationrate in DNSof a jet flame

Burning

Extinguished

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Wall heat fluxes in turbulent flame wall Wall heat fluxes in turbulent flame wall interaction at low Reynolds numberinteraction at low Reynolds number

A. Gruber, R. Sankaran, E. R. Hawkes, and J. H. Chen - 2006

DNS of turbulent flame-wall interaction

DNS of a premixed flame interacting with turbulencein a wall-bounded channel flow

Detailed H2/Air chemistry (14 D.O.F.)

Inflow turbulence obtainedfrom a separate simulationof inert channel flow

Cost: 100k hours on X1E

Goals Material failure from fluctuating

thermal stress in micro-gas turbines

Study spatial and temporal patterns of wall heat flux

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FuelFuel

AirAir

AirAir

fuelfuel

airair

D. O. Lignell, P. J. Smith, and J. H. Chen

DNS of non-premixed sooting ethylene flames (planned)

Motivation Soot is a pollutant and lowers

combustion efficiencies in dieselengines

Soot radiation is the major heat transfer mode

Goals Quantify soot formation

and transport mechanismsin turbulent flames

Approach DNS of turbulent sooting

flames with detailedchemistry, transport,radiation

2–3 moment soot particlemodel with semi-empiricalsoot chemistry

3M cpu-hours on Cray XT3at ORNL to observe slowsoot processes

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Heat release (gold) and vorticityin a lifted autoigniting H2/airjet flame

Goal: Determine stabilization mechanisms in lifted, auto-igniting flames relevant to efficient, clean burning low-temperature compression ignition engines and flashback in aircraft gas turbine engines

DNS of stabilization in lifted auto-igniting flames (planned)

Hydrogen lifted flame 300K hydrogen turbulent jet; 1100K air

coflow jet Important submechanism for n-heptane Comparison with experiment (Chung, Cabra) Auto-ignition may occur below the base of the

lifted flame due to high co-flow temperature

Approximately 1.2 million CPU hoursper simulation on Jaguar at NCCS 9 species; 21 elementary reaction steps

(Li et al. 2006) 24x20x3.6 mm3 domain size; 1600x1000 x240

grid resolution= ~400M grids 4–6 flow-though times; Umean = 350 m/s Total 3~4 simulations (~3.0 million cpu-hours

on CrayXT4 at ORNL 2006–2007)

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Contacts

Jacqueline H. ChenCombustion Research FacilitySandia National LaboratoriesLivermore, CA 94550jhchen@sandia.gov

Ramanan SankaranNational Center for Computational SciencesOak Ridge National Laboratorysankaranr@ornl.gov

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