- Access by Xinjiang University
Transported filtered density function in self-adaptive turbulence eddy simulation
Phys. Rev. Fluids 9, 033201 – Published 4 March, 2024
DOI: https://doi.org/10.1103/PhysRevFluids.9.033201
Abstract
The filtered density function (FDF) in the context of large eddy simulation (LES) has demonstrated its unique strength in predicting complex turbulent reacting flows. However, the high computational cost of FDF-LES may hinder its application in industrial configurations. The combination of FDF with the hybrid Reynolds-averaged Navier–Stokes (RANS)-LES method can potentially provide an effective means to significantly reduce computational cost while maintaining accuracy. In this work, the FDF method within the framework of self-adaptive turbulence eddy simulation (SATES), a hybrid RANS-LES approach, is formulated. The focus is on ensuring consistency in both definition and scalar-mixing modeling. The filtered density function in SATES-FDF can be interpreted as the spatial filtering density function under either RANS or LES filtering scale, depending on the local turbulence integral scale and grid resolution. The inconsistency of scalar-mixing rate modeling between RANS mode and LES mode in SATES-FDF is revealed. The general modeling criteria for modeling consistency of scalar-mixing rate are formulated in the context of SATES. A scalar-mixing rate model is then proposed through dimensional analysis, which utilizes a hybrid length scale to meet the criteria and achieve the consistency. The SATES-FDF approach is demonstrated in the simulations of standard turbulent premixed swirling burner TECFLAM, in which the shear stress transport model is adopted for the base model of SATES. With the consistency issue being resolved, it is shown that this mixing-frequency model achieves better overall agreement with experimental data than the classic models in standalone RANS or LES context in terms of reproducing the swirling flow and related flame characteristics, demonstrating its potential for practical combustor configurations. Finally, H equivalence is employed to extend SATES-FDF to more several hybrid RANS-LES frameworks, such that a unified framework for FDF in conjunction with hybrid RANS-LES method is established.
Physics Subject Headings (PhySH)
Article Text
References (73)
- H. Pitsch, Large-eddy simulation of turbulent combustion, Annu. Rev. Fluid Mech. 38, 453 (2006).
- M. Ihme and H. Pitsch, Prediction of extinction and reignition in nonpremixed turbulent flames using a flamelet/progress variable model: 2. Application in LES of Sandia flames D and E, Combust. Flame 155, 90 (2008).
- Y. Ge, M. Cleary, and A. Klimenko, A comparative study of Sandia flame series (D–F) using sparse-Lagrangian MMC modelling, Proc. Combust. Inst. 34, 1325 (2013).
- M. Nik, S. Yilmaz, P. Givi, M. Sheikhi, and S. B. Pope, Simulation of Sandia flame D using velocity-scalar filtered density function, AIAA J. 48, 1513 (2010).
- M. Sheikhi, T. Drozda, P. Givi, F. Jaberi, and S. B. Pope, Large eddy simulation of a turbulent nonpremixed piloted methane jet flame (Sandia Flame D), Proc. Combust. Inst. 30, 549 (2005).
- H. Turkeri, X. Zhao, S. B. Pope, and M. Muradoglu, Large eddy simulation/probability density function simulations of the Cambridge turbulent stratified flame series, Combust. Flame 199, 24 (2019).
- H. Koo, P. Donde, and V. Raman, LES-based Eulerian PDF approach for the simulation of scramjet combustors, Proc. Combust. Inst. 34, 2093 (2013).
- W. Jones, A. Marquis, and V. Prasad, LES of a turbulent premixed swirl burner using the Eulerian stochastic field method, Combust. Flame 159, 3079 (2012).
- H. Wang and S. B. Pope, Large eddy simulation/probability density function modeling of a turbulent jet flame, Proc. Combust. Inst. 33, 1319 (2011).
- A. Kempf, R. Lindstedt, and J. Janicka, Large-eddy simulation of a bluff-body stabilized nonpremixed flame, Combust. Flame 144, 170 (2006).
- H. Zhou, Z. Ren, D. H. Rowinski, and S. B. Pope, Filtered density function simulations of a near-limit turbulent lean premixed flame, J. Propuls. Power 36, 381 (2020).
- P. Wolf, G. Staffelbach, A. Roux, L. Gicquel, T. Poinsot, and V. Moureau, Massively parallel LES of azimuthal thermo-acoustic instabilities in annular gas turbines, C. R. Mecanique 337, 385 (2009).
- N. Ansari, P. Pisciuneri, P. Strakey, and P. Givi, Scalar-filtered mass-density-function simulation of swirling reacting flows on unstructured grids, AIAA J. 50, 2476 (2012).
- X. Zhao, D. Haworth, T. Ren, and M. Modest, A transported probability density function/photon Monte Carlo method for high-temperature oxy–natural gas combustion with spectral gas and wall radiation, Combust. Theory Model. 17, 354 (2013).
- S. Undapalli, S. Srinivasan, and S. Menon, LES of premixed and non-premixed combustion in a stagnation point reverse flow combustor, Proc. Combust. Inst. 32, 1537 (2009).
- S. T. Bose and G. I. Park, Wall-modeled large-eddy simulation for complex turbulent flows, Annu. Rev. Fluid Mech. 50, 535 (2018).
- P. R. Spalart, Strategies for turbulence modelling and simulations, Int. J. Heat Fluid Flow 21, 252 (2000).
- P. R. Spalart, Detached-eddy simulation, Annu. Rev. Fluid Mech. 41, 181 (2009).
- H. Foroutan and S. Yavuzkurt, A partially-averaged Navier–Stokes model for the simulation of turbulent swirling flow with vortex breakdown, Int. J. Heat Fluid Flow 50, 402 (2014).
- B. Basara, S. Krajnovic, S. Girimaji, and Z. Pavlovic, Near-wall formulation of the partially averaged Navier Stokes turbulence model, AIAA J. 49, 2627 (2011).
- S. Lakshmipathy and S. S. Girimaji, Partially averaged Navier–Stokes (PANS) method for turbulence simulations: Flow past a circular cylinder, J. Fluids Eng. 132, 121202 (2010).
- R. Schiestel and A. Dejoan, Towards a new partially integrated transport model for coarse grid and unsteady turbulent flow simulations, Theor. Comput. Fluid Dyn. 18, 443 (2005).
- X. Han and S. Krajnović, An efficient very large eddy simulation model for simulation of turbulent flow, Int. J. Numer. Methods Fluids 71, 1341 (2013).
- X. Han and S. Krajnović, Very-large-eddy simulation based on k-ω model, AIAA J. 53, 1103 (2015).
- C. G. Speziale, Turbulence modeling for time-dependent RANS and VLES: A review, AIAA J. 36, 173 (1998).
- X. Han and S. Krajnović, Validation of a novel very large eddy simulation method for simulation of turbulent separated flow, Int. J. Numer. Methods Fluids 73, 436 (2013).
- Z. Xia, X. Han, and J. Mao, Assessment and validation of very-large-eddy simulation turbulence modeling for strongly swirling turbulent flow, AIAA J. 58, 148 (2020).
- Z. Xia, H. Zhang, X. Han, and Z. Ren, Self-adaptive turbulence eddy simulation of a premixed jet combustor, Phys. Fluids 35, 085137 (2023).
- S. B. Pope, Small scales, many species and the manifold challenges of turbulent combustion, Proc. Combust. Inst. 34, 1 (2013).
- S. Sammak, Z. Ren, and P. Givi, Modern developments in filtered density function, in, Modeling and Simulation of Turbulent Mixing and Reaction: For Power, Energy and Flight (Springer, Singapore, 2020), p. 181.
- D. C. Haworth, Progress in probability density function methods for turbulent reacting flows, Prog. Energy Combust. Sci. 36, 168 (2010).
- S. B. Pope, PDF methods for turbulent reactive flows, Prog. Energy Combust. Sci. 11, 119 (1985).
- P. Givi, Filtered density function for subgrid scale modeling of turbulent combustion, AIAA J. 44, 16 (2006).
- J. Villermaux and J.-C. Devillon, Représentation de la redistribution des domaines de ségrégation dans un fluide par un modéle d'interaction phénoménologique, in Proceedings of the Second International Symposium on Chemical Reaction Engineering (Elsevier, Amsterdam, 1972), pp. 1–13.
- R. L. Curl, Dispersed phase mixing: I. Theory and effects in simple reactors, AICHE J. 9, 175 (1963).
- S. Subramaniam and S. B. Pope, A mixing model for turbulent reactive flows based on Euclidean minimum spanning trees, Combust. Flame 115, 487 (1998).
- Z. Ren and S. B. Pope, An investigation of the performance of turbulent mixing models, Combust. Flame 136, 208 (2004).
- H. Zhou, Z. Ren, M. Kuron, T. Lu, and J. H. Chen, Investigation of reactive scalar mixing in transported PDF simulations of turbulent premixed methane-air Bunsen flames, Flow Turbul. Combust. 103, 667 (2019).
- M. A. Gregor, F. Seffrin, F. Fuest, D. Geyer, and A. Dreizler, Multi-scalar measurements in a premixed swirl burner using 1D Raman/Rayleigh scattering, Proc. Combust. Inst. 32, 1739 (2009).
- A. Nauert, P. Petersson, M. Linne, and A. Dreizler, Experimental analysis of flashback in lean premixed swirling flames: Conditions close to flashback, Exp. Fluids 43, 89 (2007).
- C. Schneider, A. Dreizler, and J. Janicka, Fluid dynamical analysis of atmospheric reacting and isothermal swirling flows, Flow Turbul. Combust. 74, 103 (2005).
- D. Butz, Y. Gao, A. M. Kempf, and N. Chakraborty, Large eddy simulations of a turbulent premixed swirl flame using an algebraic scalar dissipation rate closure, Combust. Flame 162, 3180 (2015).
- M. Freitag and M. Klein, Direct numerical simulation of a recirculating, swirling flow, Flow Turbul. Combust. 75, 51 (2005).
- G. Kuenne, A. Ketelheun, and J. Janicka, LES modeling of premixed combustion using a thickened flame approach coupled with FGM tabulated chemistry, Combust. Flame 158, 1750 (2011).
- S. B. Pope, Ten questions concerning the large-eddy simulation of turbulent flows, New J. Phys. 6, 35 (2004).
- K. J. Hsieh, F.-S. Lien, and E. Yee, Towards a unified turbulence simulation approach for wall-bounded flows, Flow Turbul. Combust. 84, 193 (2010).
- S. T. Johansen, J. Wu, and W. Shyy, Filter-based unsteady RANS computations, Int. J. Heat Fluid Flow 25, 10 (2004).
- S. B. Pope, Turbulent Flows (Cambridge University Press, Cambridge, UK, 2000).
- J. B. Perot and J. Gadebusch, A self-adapting turbulence model for flow simulation at any mesh resolution, Phys. Fluids 19, 11 (2007).
- M. Germano, Properties of the hybrid RANS/LES filter, Theor. Comput. Fluid Dyn. 17, 225 (2004).
- S. Viswanathan, H. Wang, and S. B. Pope, Numerical implementation of mixing and molecular transport in LES/PDF studies of turbulent reacting flows, J. Comput. Phys. 230, 6916 (2011).
- S. B. Pope, A model for turbulent mixing based on shadow-position conditioning, Phys. Fluids 25, 110803 (2013).
- T. Yang, Q. Xie, H. Zhou, and Z. Ren, On the modeling of scalar mixing timescale in filtered density function simulation of turbulent premixed flames, Phys. Fluids 32, 115130 (2020).
- A. Sirivat and Z. Warhaft, The effect of a passive cross-stream temperature gradient on the evolution of temperature variance and heat flux in grid turbulence, J. Fluid Mech. 128, 323 (1983).
- X. Wang, J. Wei, X. Su, H. Zhou, and Z. Ren, Investigation of reaction-induced subgrid scalar mixing in LES/FDF simulations of turbulent premixed flames, Phys. Rev. Fluids 7, 124603 (2022).
- H. Zhou, S. Li, Z. Ren, and D. H. Rowinski, Investigation of mixing model performance in transported PDF calculations of turbulent lean premixed jet flames through Lagrangian statistics and sensitivity analysis, Combust. Flame 181, 136 (2017).
- P. J. Colucci, F. A. Jaberi, P. Givi, and S. B. Pope, Filtered density function for large eddy simulation of turbulent reacting flows, Phys. Fluids 10, 499 (1998).
- F. A. Jaberi, P. J. Colucci, S. James, P. Givi, and S. B. Pope, Filtered mass density function for large-eddy simulation of turbulent reacting flows, J. Fluid Mech. 401, 85 (1999).
- U. Schumann, Realizability of Reynolds-stress turbulence models, Phys. Fluids 20, 721 (1977).
- F. Archambeau, N. Méchitoua, and M. Sakiz, Code Saturne: A finite volume code for the computation of turbulent incompressible flows-Industrial applications, Int. J. Numer Methods Fluids 1, 1 (2004).
- J. P. Van Doormaal and G. D. Raithby, Enhancements of the SIMPLE method for predicting incompressible fluid flows, Numer. Heat Tr. 7, 147 (1984).
- P. P. Popov, H. Wang, and S. B. Pope, Specific volume coupling and convergence properties in hybrid particle/finite volume algorithms for turbulent reactive flows, J. Comput. Phys. 294, 110 (2015).
- H. Wang, P. P. Popov, and S. B. Pope, Weak second-order splitting schemes for Lagrangian Monte Carlo particle methods for the composition PDF/FDF transport equations, J. Comput. Phys. 229, 1852 (2010).
- P. P. Popov and S. B. Pope, Implicit and explicit schemes for mass consistency preservation in hybrid particle/finite-volume algorithms for turbulent reactive flows, J. Comput. Phys. 257, 352 (2014).
- H. Wang, H. Zhou, Z. Ren, and C. K. Law, Transported PDF simulation of turbulent flames under MILD conditions with particle-level sensitivity analysis, Proc. Combust. Inst. 37, 4487 (2019).
- V. S. Arpaci and P. S. Larsen, Convection Heat Transfer (Prentice-Hall, New York, 1984).
- S. Mazumder and M. F. Modest, A stochastic Lagrangian model for near-wall turbulent heat transfer, J. Heat Transfer 119, 46 (1997).
- S. B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combust. Theory Model. 1, 41 (1997).
- C. Friess, R. Manceau, and T. B. Gatski, Toward an equivalence criterion for Hybrid RANS/LES methods, Comput. Fluids 122, 233 (2015).
- L. Davidson and C. Friess, A new formulation of fk for the PANS model, J. Turbul. 20, 322 (2019).
- A. Fadai-Ghotbi, C. Friess, R. Manceau, T. B. Gatski, and J. Borée, Temporal filtering: A consistent formalism for seamless hybrid RANS–LES modeling in inhomogeneous turbulence, Int. J. Heat Fluid Flow 31, 378 (2010).
- S. Heinz, A review of hybrid RANS-LES methods for turbulent flows: Concepts and applications, Prog. Aerosp. Sci. 114, 100597 (2020).
- F. Nicoud and F. Ducros, Subgrid-scale stress modelling based on the square of the velocity gradient tensor, Flow Turbul. Combust. 62, 183 (1999).