High Fidelity Numerical Simulations of Turbulent Combustion Ramanan Sankaran Evatt R. Hawkes Chunsang Yoo David O. Lignell Jacqueline H. Chen (PI) Combustion Research Facility Sandia National Laboratories, Livermore, CA

Direct numerical simulation (DNS) of turbulent combustion Turbulent Combustion is a Grand Challenge 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 Combustor size~1m Molecular reactions ~ 1nm

S3D – Sandia’s DNS solver Solves compressible reacting Navier-Stokes equations High fidelity numerical methods 8th order finite-difference 4th order explicit RK integrator Detailed chemistry and transport models Multi-physics (sprays, radiation and soot) from SciDAC-TSTC Ported to all major platforms DNS provides unique fundamental insight into the chemistry-turbulence interaction

S3D - Parallel Performance 90% parallel efficiency on 5000 XT3 processors Ramanan: “This figure will be replaced by a new scaling figure. With dual core xt3 scaling on it.”

DNS of lean premixed combustion Goals Better understanding of lean premixed combustion in 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 stirring on flame structure and burning speed Better images from more recent simulations can go here. When they are ready. May be an animation too.

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 Fresh 1/4 Burned u’/SL=3 u’/SL=6 1/2 3/4

DNS of extinction/reignition in a jet flame Hawkes, Sankaran, Sutherland, Chen - 2006 Scalar dissipation rate in DNS of 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 performed to 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) Burning Extinguished

DNS of turbulent flame-wall interaction A. Gruber, R. Sankaran, E. R. Hawkes, and J. H. Chen - 2006 DNS of a premixed flame interacting with turbulence in a wall-bounded channel flow Detailed H2/Air chemistry (14 D.O.F.) Inflow turbulence obtained from a separate simulation of 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 Wall heat fluxes in turbulent flame wall interaction at low Reynolds number

DNS of non-premixed sooting ethylene flames (planned) D. O. Lignell, P. J. Smith, and J. H. Chen Motivation Soot is a pollutant and lowers combustion efficiencies in diesel engines Soot radiation is the major heat transfer mode Goals Quantify soot formation and transport mechanisms in turbulent flames Approach DNS of turbulent sooting flames with detailed chemistry, transport, radiation 2–3 moment soot particle model with semi-empirical soot chemistry 3M cpu-hours on Cray XT3 at ORNL to observe slow soot processes fuel air Fuel Air Picture shows DNS as a small region of a larger, more physically relevant flow. Smoke breakthrough/shielding near the top. Ethylene flame with extinction. Colored by temperature with soot contours Plot is mean soot mass fraction versus mixture fraction and time for the blue Kelvin Helmolz plot. Soot breakthrough is important in fires since smoke can shield the environment from radiation. How soot gets from fuel rich regions to a queched state outside the fire is a mystery.

DNS of stabilization in lifted auto-igniting flames (planned) 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 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 hours per 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) Heat release (gold) and vorticity in a lifted autoigniting H2/air jet flame

Contacts Jacqueline H. Chen Ramanan Sankaran Combustion Research Facility Sandia National Laboratories Livermore, CA 94550 jhchen@sandia.gov Ramanan Sankaran National Center for Computational Sciences Oak Ridge National Laboratory sankaranr@ornl.gov 11 Sankaran_Combustion_0611