CFD Simulations AC2-08: Difference between revisions

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'''Application Challenge 2-08'''                            © copyright ERCOFTAC 2011
'''Application Challenge 2-08'''                            © copyright ERCOFTAC 2011


====<span class="titlemark"> Introduction====
=== 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 most recent work done by Kuenne et al.<ref name='kuenne_les_2011'>G. Kuenne, A. Ketelheun, J. Janicka, Combustion and Flame (2011) Accepted for publication.</ref> will be given. In order to avoid an overload of information the interested reader is referred to the cited references for a detailed discussion.
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.


====<span class="titlemark"> Overview of Simulations====
=== 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.
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.
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</div>


====<span class="titlemark"> CFD Code====
=== CFD Code ===


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<ref name='lehnhaeuser_improved_2002'>T. Lehnhaeuser, M. Schaefer, International Journal for Numerical Methods in Fluids 38 (2002) 625–645.</ref> to ensure second order accuracy on arbitrary grids. To assure boundedness of scalar quantities the TVD-limiter suggested by Zhou et al.<ref name='zhou_transonic_1995'>G. Zhou, L. Davidson, E. Olsson, in: Fourteenth International Conference on Numerical Methods in Fluid Dynamics, 1995, pp. 372–378.</ref> is used. 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<ref name='stone_iterative_1968'>H.L. Stone, SIAM Journal on Numerical Analysis 5 (1968) 530–558.</ref> to take advantage of the block-structure.
==== 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<ref name='lehnhaeuser_improved_2002'>T. Lehnhaeuser, M. Schaefer, International Journal for Numerical Methods in Fluids 38 (2002) 625–645.</ref> to ensure second order accuracy on arbitrary grids. To assure boundedness of scalar quantities the TVD-limiter suggested by Zhou et al.<ref name='zhou_transonic_1995'>G. Zhou, L. Davidson, E. Olsson, in: Fourteenth International Conference on Numerical Methods in Fluid Dynamics, 1995, pp. 372–378.</ref> 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<ref name='stone_iterative_1968'>H.L. Stone, SIAM Journal on Numerical Analysis 5 (1968) 530–558.</ref> to take advantage of the block-structure.


====<span class="titlemark"> Computational Domain, Spatial Discretization and Boundary Conditions====
==== The Commercial Solver ANSYS CFX ====
ANSYS CFX employes a aconservative 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 <span class="math">ϕ </span><nowiki>= 0</nowiki><span class="math">.</span>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<span class="math">.</span>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.
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 <span class="math">ϕ </span><nowiki>= 0</nowiki><span class="math">.</span>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<span class="math">.</span>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.
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<br style='clear:both' />


====<span class="titlemark"> Physical Modeling====
===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<ref name='smagorinsky_general_1963'>J. Smagorinsky, Monthly Weather Rev. 91 (1963) 99–164</ref> where the model coefficient is obtained by the dynamic procedure of Germano et al.<ref name='germano_dynamic_1991'>M. Germano, U. Piomelli, P. Moin, W.H. Cabot, Physics of Fluids A: Fluid Dynamics 3 (1991) 1760–1765.</ref> with a modification by Lilly<ref name='lilly_proposed_1992'>D.K. Lilly, Physics of Fluids A: Fluid Dynamics 4 (1992) 633–635.</ref>. 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.


The turbulent flowfield is approximated by means of LES (Large Eddy Simulation). Sub grid fluxes of momentum are accounted for by the eddy viscosity approach proposed by Smagorinsky<ref name='smagorinsky_general_1963'>J. Smagorinsky, Monthly Weather Rev. 91 (1963) 99–164</ref> where the model coefficient is obtained by the dynamic procedure of Germano et al.<ref name='germano_dynamic_1991'>M. Germano, U. Piomelli, P. Moin, W.H. Cabot, Physics of Fluids A: Fluid Dynamics 3 (1991) 1760–1765.</ref> with a modification by Lilly<ref name='lilly_proposed_1992'>D.K. Lilly, Physics of Fluids A: Fluid Dynamics 4 (1992) 633–635.</ref>. 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 developed by Zimont has been used and the sensitivity related to its model coefficient has been investigated (see the Evaluation section).


The method to treat the chemical reaction is based on a thickened flame approach<ref name='butler_numerical_1977'>T. Butler, P. O’Rourke, Symposium (International) on Combustion 16 (1977) 1503–1515.</ref><ref name='orourke_two_1979'>P.J. O’Rourke, F.V. Bracco, Journal of Computational Physics 33 (1979) 185–203.</ref><ref name='angelberger_large_1998'>C. Angelberger, D. Veynante, F. Egolfopoulos, T. Poinsot, in: Proceedings of the Summer Program 1998, Center for Turbulence Research, pp. 61–82.</ref><ref name='colin_thickened_2000'>O. Colin, F. Ducros, D. Veynante, T. Poinsot, Physics of Fluids 12 (2000) 1843–1863.</ref><ref name='charlette_power-law_2002'>F. Charlette, C. Meneveau, D. Veynante, Combustion and Flame 131 (2002) 159–180.</ref> coupled to FGM (flamelet generated manifolds,<ref name='van_oijen_modelling_2000'> J.A. van Oijen, L.P.H. de Goey, Combustion Science and Technology 161 (2000) 113–137.</ref><ref name='van_oijen_modeling_2001'>J.A. van Oijen, F.A. Lammers, L.P.H. de Goey, Combustion and Flame 127 (2001) 2124–2134.</ref> 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.<ref name='kuenne_les_2011'> </ref>.
Within the LES simulations done with FASTES the method to treat the chemical reaction is based on a thickened flame approach<ref name='butler_numerical_1977'>T. Butler, P. O’Rourke, Symposium (International) on Combustion 16 (1977) 1503–1515.</ref><ref name='orourke_two_1979'>P.J. O’Rourke, F.V. Bracco, Journal of Computational Physics 33 (1979) 185–203.</ref><ref name='angelberger_large_1998'>C. Angelberger, D. Veynante, F. Egolfopoulos, T. Poinsot, in: Proceedings of the Summer Program 1998, Center for Turbulence Research, pp. 61–82.</ref><ref name='colin_thickened_2000'>O. Colin, F. Ducros, D. Veynante, T. Poinsot, Physics of Fluids 12 (2000) 1843–1863.</ref><ref name='charlette_power-law_2002'>F. Charlette, C. Meneveau, D. Veynante, Combustion and Flame 131 (2002) 159–180.</ref> coupled to FGM (flamelet generated manifolds,<ref name='van_oijen_modelling_2000'> J.A. van Oijen, L.P.H. de Goey, Combustion Science and Technology 161 (2000) 113–137.</ref><ref name='van_oijen_modeling_2001'>J.A. van Oijen, F.A. Lammers, L.P.H. de Goey, Combustion and Flame 127 (2001) 2124–2134.</ref> 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.<ref name='kuenne_les_2011'> </ref>.


====<span class="titlemark"> References====
=== References ===
<references/>
<references/>
<br>
<br>

Revision as of 17:52, 25 January 2011

Front Page

Description

Test Data

CFD Simulations

Evaluation

Best Practice Advice

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.

Table 4.1: Summary of simulations done of the 30 kW case.
Isothermal (30iso), CFD-Code / Publication Reacting (PSF-30), CFD-Code / Publication
RANS

FASTEST / Hahn et al.[1]

Ansys CFX / Kuenne et al.[2]

LES

FASTEST / Hahn et al.[1]

FASTEST / Kuenne et al.[3]

FASTEST / Kuenne et al.[3]

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[4] to ensure second order accuracy on arbitrary grids. To assure boundedness of scalar quantities the TVD-limiter suggested by Zhou et al.[5] 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[6] to take advantage of the block-structure.

The Commercial Solver ANSYS CFX

ANSYS CFX employes a aconservative 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.

Figure 4.1: Computational domain of the swirl nozzle. The blockstructure is indicated by the yellow block boundaries.


Figure 4.2: Dimensions of the computational domain with a cut-out of the elliptically smoothed mesh. Boundary conditions are indicated by arrows.


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[7] where the model coefficient is obtained by the dynamic procedure of Germano et al.[8] with a modification by Lilly[9]. 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 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[10][11][12][13][14] coupled to FGM (flamelet generated manifolds,[15][16] 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.[3].

References

  1. ↑ 1.0 1.1 F. Hahn, C. Olbricht, C. Klewer, G. Kuenne, R. Ohnutek, J. Janicka, in: Proc. of the ISTP19 (2008d).
  2. ↑ G. Kuenne, C. Klewer, J. Janicka, ASME Turbo Expo Conference Proceedings (2009) 369–381.
  3. ↑ 3.0 3.1 3.2 Cite error: Invalid <ref> tag; no text was provided for refs named kuenne_les_2011
  4. ↑ T. Lehnhaeuser, M. Schaefer, International Journal for Numerical Methods in Fluids 38 (2002) 625–645.
  5. ↑ G. Zhou, L. Davidson, E. Olsson, in: Fourteenth International Conference on Numerical Methods in Fluid Dynamics, 1995, pp. 372–378.
  6. ↑ H.L. Stone, SIAM Journal on Numerical Analysis 5 (1968) 530–558.
  7. ↑ J. Smagorinsky, Monthly Weather Rev. 91 (1963) 99–164
  8. ↑ M. Germano, U. Piomelli, P. Moin, W.H. Cabot, Physics of Fluids A: Fluid Dynamics 3 (1991) 1760–1765.
  9. ↑ D.K. Lilly, Physics of Fluids A: Fluid Dynamics 4 (1992) 633–635.
  10. ↑ T. Butler, P. O’Rourke, Symposium (International) on Combustion 16 (1977) 1503–1515.
  11. ↑ P.J. O’Rourke, F.V. Bracco, Journal of Computational Physics 33 (1979) 185–203.
  12. ↑ C. Angelberger, D. Veynante, F. Egolfopoulos, T. Poinsot, in: Proceedings of the Summer Program 1998, Center for Turbulence Research, pp. 61–82.
  13. ↑ O. Colin, F. Ducros, D. Veynante, T. Poinsot, Physics of Fluids 12 (2000) 1843–1863.
  14. ↑ F. Charlette, C. Meneveau, D. Veynante, Combustion and Flame 131 (2002) 159–180.
  15. ↑ J.A. van Oijen, L.P.H. de Goey, Combustion Science and Technology 161 (2000) 113–137.
  16. ↑ 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


Front Page

Description

Test Data

CFD Simulations

Evaluation

Best Practice Advice

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