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Interaction of Turbulence, Chemistry, and Radiation in Strained Nonpremixed Flames

Interaction of Turbulence, Chemistry, and Radiation in Strained Nonpremixed Flames. Chun Sang Yoo, Hong G. Im Department of Mechanical Engineering University of Michigan Yi Wang, Arnaud Trouvé Department of Fire Protection Engineering University of Maryland

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Interaction of Turbulence, Chemistry, and Radiation in Strained Nonpremixed Flames

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  1. Interaction of Turbulence, Chemistry, and Radiation in Strained Nonpremixed Flames Chun Sang Yoo, Hong G. Im Department of Mechanical Engineering University of Michigan Yi Wang, Arnaud Trouvé Department of Fire Protection Engineering University of Maryland Sponsored by the DOE SciDAC Program http://purl.org/net/tstc

  2. Outline of Presentation • Introduction • Role of DNS in Combustion Science (a brief version) • Overview: Terascale High-Fidelity Simulations of Turbulent Combustion with Detailed Chemistry (TSTC) • Research Highlights* (work led by U. Michigan) • Computational: Improved Navier-Stokes Characteristic Boundary Conditions (NSCBC) • Science: Counterflow Diffusion Flames with Soot and Radiation Models • Ongoing/Future Work *More TSTC Research Highlights: Poster Session WED21: Trouvé and Wang (Maryland) WED22: Rutland and Wang (Wisconsin)

  3. DNS: A Computational Microscope • A diagnostic tool to study the fundamental physics of turbulent reacting flows • Full access to temporally/spatially resolved information. • Allows identification of key paths for relevant phenomena, such as turbulence-chemistry interaction • A benchmark tool to develop and validate physical submodels used in macro-scale simulations of engineering-level systems (LES with embedded DNS) Formation of edge flames in a turbulent counterflow Physical Models Engineering-level CFD Codes DNS A KIVA-3V engine simulation

  4. Terascale High-Fidelity Simulations of Turbulent Combustion with Detailed Chemistry (TSTC) http://purl.org/net/tstc Software architecture Numerical algorithms SciDAC CFRFS . S3D0: F90 MPP 3D . S3D1: GrACE-based . S3D2: CCA-compliant . IMEX ARK . IBM . AMR Physical models SciDAC CCA . Thermal radiation . Soot formation . Spray dynamics MPP S3D SciDAC CMCS SDM Hong G. Im, University of Michigan Arnaud Trouvé, University of Maryland Chris Rutland, University of Wisconsin Jackie Chen, Sandia National Labs Post-processors: In-situ visualization Feature tracking

  5. S3D code characteristics: Compressible reacting Navier-Stokes, total energy, species equations Fortran 90, MPI domain decomposition Highly scalable and portable on all modern architectures Numerical algorithms: 8th order non-dissipative spatial finite difference, 10th order dealiasing filter 4th order explicit RK integrator with error monitoring Additive 4th order RK integrator for stiff chemistry Improved boundary conditions to allow transverse velocity, flame passage through boundary, or solid walls* Physical models: Lewis number, mixture averaged, or multi-component transport Detailed gas-phase chemical kinetics (Chemkin-compatible) All thermodynamic properties are functions of T, p, and Yi Radiative heat transfer (discrete ordinate / discrete transfer method)* Soot formation* Lagrangian spray model* *Recent Contributions from the SciDAC TSTC Project S3D: MPP DNS Code

  6. Characteristic Boundary Conditions • A “pre-requisite” issue for high-quality turbulent combustion DNS • Historical Development • General nonreflecting outflow boundary conditions (Engquist and Majda 1977, Hedstrom 1979) • Pressure damping for Navier-Stokes equations (Rudy & Strikwerda 1980, 1981) • Inviscid characteristic theory for Euler equations (Thompson 1987,1990) • Navier-Stokes characteristic boundary conditions (NSCBC) - Viscous conditions (Poinsot & Lele 1992) • Multi-component reacting flows (Baum et al. 1994) • Applications to turbulent and reacting flows have revealed problems of spurious pressure waves, numerical instabilities. • Reaction source terms (Sutherland & Kennedy 2003)

  7. Characteristic Waves • Li : characteristic wave with i (wave velocities, 1= (uc), 2=3=4=u, 5= (u+c)) Computational domain inflow outflow flow

  8. Locally One-Dimensional Inviscid (LODI) Relations • Neglecing transverse convection, viscous, and reactive terms • The incoming Li’s can be determined at both inflow and outflow boundaries using LODI relations • Hard inflow boundary conditions yield large spurious wave reflections : nonreflecting conditions are needed • Inflow boundary • Outflow boundary

  9. Generalized NSCBC for Transverse, Viscous, Reacting Flows • LODI relations are no longer valid: transverse, viscous, reaction terms must be considered in Li’s Outflow boundary conditions (at x = lx) Conventional LODI Improved BC Spatial : Temporal : Low-Ma asymptotic expansion yields:

  10. Test 1: Vortex-Convection • Incompressible inviscid vortex • Conditions • Three different boundary conditions • BC1 : conventional LODI with • BC2 : keep all the transverse terms(a = 0.0) • BC3 : improved BC with pressure and transverse damping (a = M= 0.05)

  11. Vorticity and Pressure  LODI BC2 (a = 0.0) Improved BC (a = 0.05) P

  12. Velocities u LODI BC2 (a = 0.0) Improved BC (a = 0.05) v

  13. Temporal Pressure Variation • Examine how the solution approaches the steady state • The L2-norm : Temporal variations of the L2-norms of pressure difference

  14. Test 2: Ignition H2-O2 Mixture • Stoichiometric H2-O2 mixture diluted with 50% N2 by volume • 2mm  2mm (200  200 grid points) • Initial temperature and pressure, 300K and 1atm • Initial Gaussian temperature peak • Three test cases • Case A: conventional LODI • Case B: include source terms in incoming Li’s (Sutherland & Kennedy 2003) • Case C: improved BC with a = 0.125 (scaling analysis)

  15. Temperature and HO2 T Case A (LODI) Case B (Sutherland& Kennedy) Case C (Improved BC) YHO2

  16. Test 3: Poiseuille Flow (Isothermal Wall) • Viscous terms must be considered • Test cases • Case A: conventional LODI B.C. with 1,exact • Case B: including only pressure damping term (a = 0.0) • Case C: improved B.C. with a = 0.1 • The pressure level of Case A is increased because 1,exact does not cancel out all the viscous and heat flux effect • The velocity at the outflow boundary in Case B is not accurate: transverse damping term is needed Temporal variation of pressure

  17. Test 4: Turbulent Reacting Counterflow • Transverse terms cannot be ignored • a = 0.01 • Use the steady laminar H2air nonpremixed counterflow flame as the initial condition • Turbulence inflow condition • Velocity fluctuations are superimposed on the mean inlet velocities. • Homogenous turbulence (a) temperature (b) vorticity

  18. Strained Nonpremixed Flames with Soot and Radiation • Motivation • Predictive tools for pollutant formation (soot, NOx) • Thermal radiation plays an important role, but has not been incorporated in high-fidelity simulations • Need better understanding of interaction between flow, chemistry, and heat transfer • Objectives • To develop high-fidelity DNS capabilities with advanced physical submodels for soot and radiation • Validate and assess the impact of the advanced physical models in a canonical configuration (flame-vortex) • Perform laboratory-scale simulations to answer science questions on turbulence-chemistry-radiation interaction (future work)

  19. Radiation Models in S3D Based on gray gas assumption Radiative heat flux: • Optically thin model (OTM) • Discrete ordinate method (DOM) RTE solved in n discrete directions (ordinates) • Sn approx.  number of equations = n(n+2)/2 (2-D) • S2: 4 eqs., and S4: 12 eqs. • Discrete transfer method (DTM) RTE solved for n rays (ray-tracing)

  20. Performance of DOM/DTM • MPI Scalability Total radiative power DOM is found to be overall superior for the desired accuracy. Relative error

  21. Nucleation Coagulation Surface growth Nucleation Oxidation Soot Model (Two Equation Model) • A semi-empirical two-equation model based on a flamelet approach (Young and Moss, 1995) • Soot number density • Soot volume fraction • Parameters

  22. Ly=2.48cm u0 uL Ethylene Air Lx=2.48cm Computational Configuration • Calculation procedure • Generate 1-D diffusion flame profile (Oppdif) • Establish steady diffusion flame in counterflow • Superimpose initial vortex pairs • Velocity profile for a vortex

  23. Parameters • Three different vortex strength cases • Weak vortex : flame and soot are not extinguished • Medium vortex : extinguishes soot only • Strong vortex : extinguishes both flame and soot

  24. Weak vs. Strong Vortex Cases Vorticity Temperature Nsoot fv Case A Case B Case C

  25. Integrated Nsoot andfv (Case B) Volume-integrated Nsoot and flame volume Volume-integrated fv in different temperature regions • Soot number density depends strongly on the high-temperature flame volume • Soot volume fraction increases by surface growth at low temperature, fuel-rich regions

  26. Effects of the Vortex Strength Comparison of integrated fv for Cases A-C Comparison of integrated Nsoot for Cases A-C • As vortex strength increases, more soot particles are convected into fuel rich zone • Case A: fv is more directly affected by the soot nucleation. • Case C: fv does not change much even the the soot nucleation (Nsoot) is turned off.

  27. Comparison of Radiation Models • Radiative heat loss • During transient period, OTM overpredictsthe radiative heat loss by up to a factor of two compared to DOM • Fidelity of radiation model is important in DNS Total radiative heat loss with OTM and DOM for Case B

  28. Ongoing/Future Work Terascale Computing: 3D Turbulent Nonpremixed Counterflow Flames with Radiation, Soot, and Water Spray • Integration of all the developed physical submodels • Test bench for numerical algorithms: boundary conditions, acoustic speed reduction (ASR) • Science issue: partial/total extinction and pollutant formation due to water spray interaction Further To-Do List • Computational Development • Immersed boundary method • Adaptive mesh refinement • Chemistry reduction strategies • Physical Models • Detailed soot model • Radiation model (spectral) • Catalytic surface reaction DOE INCITE Project: 3D DNS of turbulent nonpremixed jet flame, J. H. Chen et al. Sandia National Labs • Enabling Technologies • Data-mining and visualization • Object-oriented code architecture for efficient management

  29. Acknowledgments • SciDAC TSTCProgram • Hong G. Im (Michigan) • Chunsang Yoo, Ramanan Sankaran (SNL) • Christopher J. Rutland (Wisconsin) • Yunliang Wang • Arnaud Trouvé (Maryland) • Yi Wang • Jacqueline H. Chen (Sandia National Laboratories) • Scott Mason, Chris Kennedy, James Sutherland, Evatt Hawkes • Pittsburgh Supercomputing Center • Ravishankar Subramanya, Raghurama Reddy • DOE Computing Resources • National Energy Research Scientific Computing Center • Oak Ridge National Laboratory • Pacific Northwest National Laboratory • University of Oregon (the Tau Project) • Sameer Shende, Allen Malony

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