CFD Simulations AC2-08: Difference between revisions
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FASTEST / Hahn et al.<ref name='hahn_investigation_2008'>F. Hahn, C. Olbricht, C. Klewer, G. Kuenne, R. Ohnutek, J. Janicka, in: Proc. of the ISTP19 (2008d).</ref> | FASTEST / Hahn et al.<ref name='hahn_investigation_2008'>F. Hahn, C. Olbricht, C. Klewer, G. Kuenne, R. Ohnutek, J. Janicka, in: Proc. of the ISTP19 (2008d).</ref> | ||
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Ansys CFX / Kuenne et al.<ref name=' | Ansys CFX / Kuenne et al.<ref name='kuenne_les_2011'>G. Kuenne, A. Ketelheun, J. Janicka, Combustion and Flame (2011) Accepted for publication.</ref> | ||
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Revision as of 06:24, 26 January 2011
Premixed Methane-Air Swirl Burner (TECFLAM)
Application Challenge 2-08 © copyright ERCOFTAC 2011
Introduction
The Tecflam configuration has been investigated by means of RANS (Reynolds Averaged Navier Stokes) and LES (Large Eddy Simulation). An overview will be presented in this section. Some details of the simulation program and the employed turbulence and combustion model will be given. In order to avoid an overload of information the interested reader is referred to the cited references for a detailed discussion.
Overview of Simulations
Since measurements of temperature and species mass fractions exist only for the 30 kW configuration only this case has been investigated by means of numerical simulations. The studies are summarized in table 4.1.
CFD Code
The Academic Solver FASTEST
The three-dimensional finite volume code FASTEST uses block-structured, hexahedral, boundary fitted grids to represent complex geometries. Regarding the velocity, spatial discretization is based on multi-dimensional Taylor series expansion[3] to ensure second order accuracy on arbitrary grids. To assure boundedness of scalar quantities the TVD-limiter suggested by Zhou et al.[4] is used. Within LES an explicit Runge-Kutta scheme is used for the time advancement of momentum and species mass fractions with temperature dependent transport coefficients. The code solves the incompressible, variable density, Navier-Stokes equations where an equation for the pressure correction is solved within each Runge-Kutta stage to satisfy continuity. The solver is based on an ILU matrix decomposition and uses the strongly implicit procedure[5] to take advantage of the block-structure.
The Commercial Solver ANSYS CFX
ANSYS CFX employes a conservative fininte-element-based control volume method to solve the Navier-Stokes equations. The code supports unstructured meshes and the resulting system of equations is solved by a pressure-based algorithm. Since an extensive documentation exist for CFX a detailed description is omitted here.
Computational Domain, Spatial Discretization and Boundary Conditions
As illustrated in Fig. 4.1 and 4.2 the computational domain starts after the plenum chamber at the inlets of the tangential and radial channels. Here the mass flow given by the measurements has been set. No additional velocity fluctuation is forced here since the inclusion of the geometry upstream of the nozzle exit has been found to be sufficient to allow the turbulent structures to form. The equivalence ratio has been set to ϕ = 0.83 at the inlet since the methane-air mixture has been verified by the measurements to be mixed homogeneously. The diameter of the computational domain matches the extend of the coflowing air issuing with 0.5m/s. The boundaries in radial and axial direction have been found to be sufficiently far away from the region of interest (i.e. the swirler exit region). The block structured grid contains 3.2 million control volumes and has been elliptically smoothed to obtain a better orthogonality. The grid has been refined towards the near nozzle region whereas it gets coarser with increasing distance to spare cells.
Physical Modeling
RANS Closure
Within RANS the Reynolds stress tensor is modeled according to the standard k-ε model by Jones and Launder (1972), following a Boussinesq approximation where the turbulent viscosity is expressed dependent on the turbulent kinetic energy (k) and the dissipation rate (ε). FASTEST uses a flux blending to combining 1st order upwind with the 2nd order central differencing scheme. Within CFX the high resolutin scheme has been used which combines 1st and 2nd order discretization along the border of stability.
LES Closure
Within the LES carried out with FASTEST the sub grid fluxes of momentum are accounted for by the eddy viscosity approach proposed by Smagorinsky[6] where the model coefficient is obtained by the dynamic procedure of Germano et al.[7] with a modification by Lilly[8]. Outside of the reaction zone a gradient approach has been chosen for the sub grid flux of scalar quantities with a turbulent Schmidt number of 0.7.
Combustion Modeling
For the RANS simulations done with ANSYS CFX the implemented Turbulent Flame Speed Closure (TFC) model has been used. It is based on an tranport equation for the reaction progress and the mixture fraction to account for the chemical reaction and mixing with the coflowing air respectively. To close the chemical source term the correlation to express the turbulent flame speed in terms of turbulent scales developed by Zimont has been used and the sensitivity related to its model coefficient has been investigated (see the Evaluation section).
Within the LES simulations done with FASTES the method to treat the chemical reaction is based on a thickened flame approach[9][10][11][12][13] coupled to FGM (flamelet generated manifolds)[14][15] tabulated chemistry using the mixture fraction and a reaction progress variable. Details about the method and its verification can be found in Kuenne et al.[2].
References
- ↑ 1.0 1.1 F. Hahn, C. Olbricht, C. Klewer, G. Kuenne, R. Ohnutek, J. Janicka, in: Proc. of the ISTP19 (2008d).
- ↑ 2.0 2.1 2.2 2.3 G. Kuenne, A. Ketelheun, J. Janicka, Combustion and Flame (2011) Accepted for publication.
- ↑ T. Lehnhaeuser, M. Schaefer, International Journal for Numerical Methods in Fluids 38 (2002) 625–645.
- ↑ G. Zhou, L. Davidson, E. Olsson, in: Fourteenth International Conference on Numerical Methods in Fluid Dynamics, 1995, pp. 372–378.
- ↑ H.L. Stone, SIAM Journal on Numerical Analysis 5 (1968) 530–558.
- ↑ J. Smagorinsky, Monthly Weather Rev. 91 (1963) 99–164
- ↑ M. Germano, U. Piomelli, P. Moin, W.H. Cabot, Physics of Fluids A: Fluid Dynamics 3 (1991) 1760–1765.
- ↑ D.K. Lilly, Physics of Fluids A: Fluid Dynamics 4 (1992) 633–635.
- ↑ T. Butler, P. O’Rourke, Symposium (International) on Combustion 16 (1977) 1503–1515.
- ↑ P.J. O’Rourke, F.V. Bracco, Journal of Computational Physics 33 (1979) 185–203.
- ↑ C. Angelberger, D. Veynante, F. Egolfopoulos, T. Poinsot, in: Proceedings of the Summer Program 1998, Center for Turbulence Research, pp. 61–82.
- ↑ O. Colin, F. Ducros, D. Veynante, T. Poinsot, Physics of Fluids 12 (2000) 1843–1863.
- ↑ F. Charlette, C. Meneveau, D. Veynante, Combustion and Flame 131 (2002) 159–180.
- ↑ J.A. van Oijen, L.P.H. de Goey, Combustion Science and Technology 161 (2000) 113–137.
- ↑ J.A. van Oijen, F.A. Lammers, L.P.H. de Goey, Combustion and Flame 127 (2001) 2124–2134.
Contributors: Guido Kuenne (EKT), Andreas Dreizler (RSM), Johannes Janicka (EKT)
EKT: Institute of Energy and Power Plant Technology, Darmstadt University of Technology
RSM: Institute Reactive Flows and Diagnostics, Center of Smart Interfaces, Darmstadt University of Technology