Evaluation AC3-03: Difference between revisions
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=='''Conclusions - Recommendations and Future Work'''== | =='''Conclusions - Recommendations and Future Work'''== | ||
The CFD study was carried out using a relatively coarse unstructured hexahedral mesh. A mesh sensitivity study was not carried out, however, a comparison of the experimental data with the results of the CFD analysis have shown good agreement. In each case, the shape of the velocity profile was accurately predicted. In a recent study it was demonstrated that only a marginal improvement in the accuracy of the predicted velocity profiles was achieved when the same cyclone was modelled using an LES turbulence model on a computational mesh that consisted of 640,000 cells [13]. | The CFD study was carried out using a relatively coarse unstructured hexahedral mesh. A mesh sensitivity study was not carried out, however, a comparison of the experimental data with the results of the CFD analysis have shown good agreement. In each case, the shape of the velocity profile was accurately predicted. In a recent study it was demonstrated that only a marginal improvement in the accuracy of the predicted velocity profiles was achieved when the same cyclone was modelled using an LES turbulence model on a computational mesh that consisted of 640,000 cells [[#13|13]]. | ||
It is concluded therefore that the mean flow pattern within a cyclone chamber can be accurately modelled using CFD and the approach described in this document. | It is concluded therefore that the mean flow pattern within a cyclone chamber can be accurately modelled using CFD and the approach described in this document. | ||
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• The RSM turbulence model was used to account for the anisotropic nature of the turbulence in a cyclone (it is the author’s experience that standard isotropic k-ε turbulence models do not accurately predict the shape of the measured axial velocity profile within the cyclone chamber and are wholly inappropriate for cyclone modelling of this type). | • The RSM turbulence model was used to account for the anisotropic nature of the turbulence in a cyclone (it is the author’s experience that standard isotropic k-ε turbulence models do not accurately predict the shape of the measured axial velocity profile within the cyclone chamber and are wholly inappropriate for cyclone modelling of this type). | ||
• As described by Slack et al. [8], false or numerical diffusion [11] is particularly prominent in highly swirling contained flows such as cyclones. Discretisation schemes therefore play an important part in cyclone simulations and the effect of numerical diffusion can be reduced by using higher order discretisation schemes. In the AC described here the higher order Quadratic Upwind Scheme (QUICK) was used. | • As described by Slack et al. [[#8|8]], false or numerical diffusion [[#11|11]] is particularly prominent in highly swirling contained flows such as cyclones. Discretisation schemes therefore play an important part in cyclone simulations and the effect of numerical diffusion can be reduced by using higher order discretisation schemes. In the AC described here the higher order Quadratic Upwind Scheme (QUICK) was used. | ||
In the steady state simulations described in this document, the asymmetrical nature of the axial velocity in the cyclone may be explained by the asymmetry introduced by the cyclone inlet. As explained by Slack et al. [13] steady state simulations using a Reynolds stress turbulence model on a relatively coarse unstructured mesh provides a computationally inexpensive method for examining in detail the time averaged flow field in cyclonic flows of this type. The computationally more expensive LES model on a finer mesh reveals time dependent vortex oscillations, which potentially impact the separation efficiency and wall erosion. | In the steady state simulations described in this document, the asymmetrical nature of the axial velocity in the cyclone may be explained by the asymmetry introduced by the cyclone inlet. As explained by Slack et al. [[#13|13]] steady state simulations using a Reynolds stress turbulence model on a relatively coarse unstructured mesh provides a computationally inexpensive method for examining in detail the time averaged flow field in cyclonic flows of this type. The computationally more expensive LES model on a finer mesh reveals time dependent vortex oscillations, which potentially impact the separation efficiency and wall erosion. | ||
It is recommended that the study be extended to address the effect of numerical and physical parameters (mesh size, discretisation scheme, inlet turbulence parameters etc) on the [[DOAPs]]. | It is recommended that the study be extended to address the effect of numerical and physical parameters (mesh size, discretisation scheme, inlet turbulence parameters etc) on the [[DOAPs]]. | ||
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[8] Slack, M.D, Boysan, F. and Ewan, B.C. (1997). ''Advances in Cyclone Modelling using Unstructured Grids''. Fluent Scandinavia User Group Meeting | [8] Slack, M.D, Boysan, F. and Ewan, B.C. (1997). ''Advances in Cyclone Modelling using Unstructured Grids''. Fluent Scandinavia User Group Meeting | ||
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<span id="9"> | <span id="9"> | ||
Latest revision as of 16:05, 11 February 2017
Cyclone separator
Application Challenge 3-03 © copyright ERCOFTAC 2004
Comparison of Test data and CFD
Conclusions - Recommendations and Future Work
The CFD study was carried out using a relatively coarse unstructured hexahedral mesh. A mesh sensitivity study was not carried out, however, a comparison of the experimental data with the results of the CFD analysis have shown good agreement. In each case, the shape of the velocity profile was accurately predicted. In a recent study it was demonstrated that only a marginal improvement in the accuracy of the predicted velocity profiles was achieved when the same cyclone was modelled using an LES turbulence model on a computational mesh that consisted of 640,000 cells 13.
It is concluded therefore that the mean flow pattern within a cyclone chamber can be accurately modelled using CFD and the approach described in this document.
• The RSM turbulence model was used to account for the anisotropic nature of the turbulence in a cyclone (it is the author’s experience that standard isotropic k-ε turbulence models do not accurately predict the shape of the measured axial velocity profile within the cyclone chamber and are wholly inappropriate for cyclone modelling of this type).
• As described by Slack et al. 8, false or numerical diffusion 11 is particularly prominent in highly swirling contained flows such as cyclones. Discretisation schemes therefore play an important part in cyclone simulations and the effect of numerical diffusion can be reduced by using higher order discretisation schemes. In the AC described here the higher order Quadratic Upwind Scheme (QUICK) was used.
In the steady state simulations described in this document, the asymmetrical nature of the axial velocity in the cyclone may be explained by the asymmetry introduced by the cyclone inlet. As explained by Slack et al. 13 steady state simulations using a Reynolds stress turbulence model on a relatively coarse unstructured mesh provides a computationally inexpensive method for examining in detail the time averaged flow field in cyclonic flows of this type. The computationally more expensive LES model on a finer mesh reveals time dependent vortex oscillations, which potentially impact the separation efficiency and wall erosion.
It is recommended that the study be extended to address the effect of numerical and physical parameters (mesh size, discretisation scheme, inlet turbulence parameters etc) on the DOAPs.
Further work should also address the issue of pressure drop across the cyclone and of particle separation and classification within cyclones.
References
[1] Svarkovsky, L (1984). Hydrocyclones, Holt, Rinehart and Winston, London
[2] Reitma, K (1961). Performance and Design of Hydrocyclones i-iv, Chem. Engng. Sci. Vol 15 pp298-325
[3] Kelsall, D. F. (1952). A Study of the Motion of Solid Particles in a Hydraulic Cyclone, Trans. Inst. Chem. Engrs. Vol 30 pp87-108
[4] Bloor, M.I.G and Ingham, D.B (1987). The Flow in Industrial Cyclones. J. Fluid Mech., Vol 178 pp507-519.
[5] Slack, M.D and Wraith, A.E (1997). Modelling the Velocity Distribution in a Hydrocyclone. 4th International Colloquium on Process Simulation, pp65-83
[6] Knowlton. (1994). The Importance of Storage, Transfer and Collection. Chem. Eng. Prog. April, pp44-45
[7] Ayers, W.H, Boysan, F, Swithenbank, J and Ewan, B.C.R (1983). Theoretical Modelling of Cyclone Performance. Filtech Conference
[8] Slack, M.D, Boysan, F. and Ewan, B.C. (1997). Advances in Cyclone Modelling using Unstructured Grids. Fluent Scandinavia User Group Meeting
[9] Fluent 5 User Guide (1998)
[10]Launder, B.E, Reece, G.J and Rodi, W. (1975). Progress in the development of a Reynolds-stress Turbulence Closure. J. Fluid Mech, 68(3):537-566, April.
[11]Patankar, S V. (1980). Numerical Heat Transfer and Fluid Flow. Hemisphere, Washington, D.C.
[12]Launder, B.E and Spalding, D.B. (1974). The Numerical Computation of Turbulent Flows. Computer Methods in Applied Mechanics and Engineering, 3:269-289
[13]Slack, M.D., Prasad, R.O., Bakker, A. and Boysan, F. (2000). Advances in Cyclone Modelling Using Unstructured Grids. Trans IchemE, Vol 78, Part A, November
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