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) DNS Physical Models Engineering-level CFD Codes A KIVA-3V engine simulation Formation of edge flames in a turbulent counterflow

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

5. S3D: MPP DNS Code  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:  8 th order non-dissipative spatial finite difference, 10 th order dealiasing filter  4 th order explicit RK integrator with error monitoring  Additive 4 th 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 Y i  Radiative heat transfer (discrete ordinate / discrete transfer method)*  Soot formation*  Lagrangian spray model* * Recent Contributions from the SciDAC TSTC Project

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 inflowoutflow L i : characteristic wave with i (wave velocities, 1 = (u  c), 2 = 3 = 4 =u, 5 = (u+c) ) Computational domain flow

8. Locally One-Dimensional Inviscid (LODI) Relations  Neglecing transverse convection, viscous, and reactive terms  The incoming L i ’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 L i ’s Conventional LODIImproved BC Outflow boundary conditions (at x = l x ) 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 Improved BC ( a = 0.05 ) BC2 ( a = 0.0 ) P 

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

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

15. Temperature and HO 2 Case A (LODI) Case B (Sutherland & Kennedy) Case C (Improved BC) Y HO2 T

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 Temporal variation of pressure  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

17. Test 4: Turbulent Reacting Counterflow  Transverse terms cannot be ignored  a = 0.01  Use the steady laminar H 2  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)  S n approx.  number of equations = n(n+2)/2 (2-D)  S 2 : 4 eqs., and S 4 : 12 eqs.  Discrete transfer method (DTM) RTE solved for n rays (ray-tracing)

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

21. 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 NucleationCoagulation Surface growth Oxidation Nucleation Parameters

22. Computational Configuration  Calculation procedure 1.Generate 1-D diffusion flame profile (Oppdif) 2.Establish steady diffusion flame in counterflow 3.Superimpose initial vortex pairs  Velocity profile for a vortex L x =2.48cm L y =2.48cm Ethylene Air u0u0 uLuL

23. Parameters ParameterCase ACase BCase C u ,max [cm/s]100300500 u 0 [cm/s]78 u L [cm/s]78  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 TemperatureN soot fvfv Case A Case C Vorticity Case B

25. Integrated N soot and f v (Case B) Volume-integrated f v in different temperature regions Volume-integrated N soot and flame volume  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. Comparison of integrated f v for Cases A-C Comparison of integrated N soot for Cases A-C Effects of the Vortex Strength  As vortex strength increases, more soot particles are convected into fuel rich zone  Case A: f v is more directly affected by the soot nucleation.  Case C: f v does not change much even the the soot nucleation (N soot ) is turned off.

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

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  Enabling Technologies  Data-mining and visualization  Object-oriented code architecture for efficient management DOE INCITE Project: 3D DNS of turbulent nonpremixed jet flame, J. H. Chen et al. Sandia National Labs

29. Acknowledgments  SciDAC TSTC Program  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