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Particle impaction on a cylinder in a crossflow as function of Stokes and Reynolds numbers

Published online by Cambridge University Press:  27 July 2010

NILS ERLAND L. HAUGEN  and
STEINAR KRAGSET
NILS ERLAND L. HAUGEN
Affiliation:
SINTEF Energy Research, N-7465 Trondheim, Norway
STEINAR KRAGSET*
Affiliation:
SINTEF Energy Research, N-7465 Trondheim, Norway
*
†Email address for correspondence: steinar.kragset@sintef.no
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Abstract

A high-order direct numerical simulation code (The Pencil Code) has been used together with the immersed boundary method on a Cartesian grid to simulate particle impaction on a cylinder in a crossflow. The direct numerical scheme concerns only the fluid flow, into which the particles are subsequently coupled through a one-way drag-coefficient law. The immersed boundary method is extended to work with high-order discretization, and the particle impaction efficiency has been measured for Stokes numbers ranging from 0.001 to 40 for a range of different Reynolds numbers. Three modes of impaction on the front side of the cylinder are identified, where, for the large-Stokes-number mode (St > 0.3), an alternative to the traditional Stokes number is presented that provides better scaling. The intermediate impaction mode has a very steep decrease in impaction efficiency as the Stokes number is decreased, and this is identified as the range of Stokes numbers where the viscous boundary layer starts to take effect. The third mode of front-side impaction is for the very small particles with St < 0.1 exactly following the flow but impacting on the cylinder due to their finite radii. There will not be any capture on the front side of the cylinder for impact angles larger than ~56° for this mode. Finally, it is found that the particle impaction on the back side of the cylinder is strongly dependent on the flow Reynolds number, where large Reynolds numbers lead to larger impaction efficiencies. The upper limiting Stokes number of back-side impaction is around 0.13, apparently irrespective of the Reynolds number.

JFM classification

Complex Fluids: Complex Fluids Mathematical Foundations: Computational methods
Type
Papers
Information
Journal of Fluid Mechanics , Volume 661 , 25 October 2010 , pp. 239 - 261
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

Baxter, L. L. 1990 Coal combustion science: quarterly progress report. Tech. Rep. SAND 90-8247. Sandia National Laboratory.CrossRefGoogle Scholar
Borthwick, A. 1986 Comparison between two finite-difference schemes for computing the flow around a cylinder. Intl J. Numer. Methods Fluids 6 (5), 275–290.CrossRefGoogle Scholar
Bouhairie, S. & Chu, V. H. 2007 Two-dimensional simulation of unsteady heat transfer from a circular cylinder in crossflow. J. Fluid Mech. 570, 177–215.CrossRefGoogle Scholar
Chern, M. J., Borthwick, A. G. L. & Taylor, R. E. 2005 Pseudospectral element model for free surface viscous flows. Intl J. Numer. Methods Heat Fluid Flow 15 (6), 517–554.CrossRefGoogle Scholar
Dennis, S. C. R. & Chang, G.-Z. 1970 Numerical solutions for steady flow past a circular cylinder at Reynolds numbers up to 100. J. Fluid Mech. Digit. Arch. 42 (3), 471–489.CrossRefGoogle Scholar
Golovin, M. N. & Putnam, A. A. 1962 Inertial impaction on single elements. Ind. Engng Chem. Fundam. 1, 264–273.CrossRefGoogle Scholar
Goto, S. & Vassilicos, J. C. 2006 Self-similar clustering of intertial particles and zero-acceleration points in fully developed two-dimensional turbulence. Phys. Fluids 18, 115103.CrossRefGoogle Scholar
Huang, L. Y., Norman, J. S., Pourkashanian, M. & Williams, A. 1996 Prediction of ash deposition on superheater tubes from pulverized coal combustion. Fuel 75, 271–279.CrossRefGoogle Scholar
Ilias, S. & Douglas, P. L. 1989 Inertial impaction of aerosol particles on cylinders at intermediate and high Reynolds numbers. Chem. Engng Sci. 44, 81–99.Google Scholar
Ingham, D., Hildyard, M. & Heggs, P. 1990 On the critical Stokes' number for particle transport in potential and viscous flows near bluff bodies. J. Aerosol Sci. 21, 935–946.CrossRefGoogle Scholar
Israel, R. & Rosner, D. 1983 Use of a generalized Stokes number to determine the aerodynamical capture efficiency of non-Stokesian particles from a compressible gas flow. Aerosol Sci. Technol. 2, 45–51.CrossRefGoogle Scholar
Kasper, G., Schollmeier, S., Meyer, J. & Hoferer, J. 2009 The collection efficiency of a particle-loaded single filter fiber. J. Aerosol Sci. 40 (12), 993–1009.CrossRefGoogle Scholar
Kim, J., Kim, D. & Choi, H. 2001 An immersed-boundary finite-volume method for simulations of flow in complex geometries. J. Comput. Phys. 171 (1), 132–150.CrossRefGoogle Scholar
Konstandopoulos, A. G., Labowsky, M. J. & Rosner, D. E. 1993 Inertial deposition of particles from potential flows past cylinder arrays. J. Aerosol Sci. 24 (4), 471–483.CrossRefGoogle Scholar
Lai, M.-C. & Peskin, C. S. 2000 An immersed boundary method with formal second-order accuracy and reduced numerical viscosity. J. Comput. Phys. 160 (2), 705–719.CrossRefGoogle Scholar
Li, X., Zhou, H. & Cen, K. 2008 Influences of various vortex structures on the dispersion and deposition of small ash particles. Fuel 87, 1379–1382.CrossRefGoogle Scholar
Loehden, D., Walsh, P. M., Sayre, A. N., Beer, J. M. & Sarofim, A. F. 1989 Generation and deposition of fly ash in the combustion of pulverised coal. J. Inst. Energy pp. 119–127.Google Scholar
Marchioli, C. & Soldati, A. 2002 Mechanisms for particle transfer and segregation in a turbulent boundary flow. J. Fluid Mech. 468, 283–315.CrossRefGoogle Scholar
Marchioli, C., Soldati, A, Kuerten, J. G. M., Archen, B., Tanire, A., Goldensoph, G., Squires, K. D., Cargnelutti, M. F. & Portela, L. M. 2008 Statistics of particle dispersion in direct numerical simulations of wall-bounded turbulence: results of an international collaborative benchmark test. Intl J. Multiph. Flow 34, 879–893.CrossRefGoogle Scholar
Mittal, R. & Iaccarino, G. 2005 Immersed boundary methods. Annu. Rev. Fluid Mech. 37 (1), 239–261.CrossRefGoogle Scholar
Muhr, W. 1976 Theoretical and experimental investigation of particle deposition in fibrous filters by field and inertial forces. Dissertation, Institut für Mechanische Verfahrenstechnik und Mechanik, Universität Karlsruhe, Karlsruhe, Germany.Google Scholar
Noor, D., Chern, M.-J. & Horng, T.-L. 2009 An immersed boundary method to solve fluid–solid interaction problems. Comput. Mech. 44 (4), 447–453.CrossRefGoogle Scholar
Pan, D. 2006 An immersed boundary method on unstructured Cartesian meshes for incompressible flows with heat transfer. Numer. Heat Transfer Part B Fundam.: Intl J. Comput. Methodol. 49 (3), 277–297.CrossRefGoogle Scholar
The Pencil Code 2009 http://www.nordita.org/software/pencil-codeGoogle Scholar
Peskin, C. S. 2002 The immersed boundary method. In Acta Numerica (ed. Iserles, A.), vol. 11, pp. 479–517. Cambridge University Press.Google Scholar
Picano, F., Sardina, G. & Casciola, C. M. 2009 Spatial development of particle-laden turbulent pipe flow. Phys. Fluids 21, 093305.CrossRefGoogle Scholar
Poinsot, T. J. & Lele, S. K. 1992 Boundary conditions for direct simulations of compressible viscous flows. J. Comput. Phys. 101 (1), 104–129.CrossRefGoogle Scholar
Rouson, D. W. I. & Eaton, J. K. 2001 On the preferential concentration of solid particles in turbulent channel flow. J. Fluid Mech. 428, 149–169.CrossRefGoogle Scholar
Schweers, E., Umhauer, H. & Löffler, F. 1994 Experimental investigations of particle collection on single fibres of different configurations. Part. Syst. Charact. pp. 275–283.CrossRefGoogle Scholar
Su, S.-W., Lai, M.-C. & Lin, C.-A. 2007 An immersed boundary technique for simulating complex flows with rigid boundary. Comput. Fluids 36 (2), 313–324.CrossRefGoogle Scholar
Suneja, S. K. & Lee, C. H. 1974 Aerosol filtration by fibrous filters at intermediate Reynolds numbers (≤ 100). Atmos. Environ. 8, 1081–1094.CrossRefGoogle Scholar
Tritton, D. J. 1959 Experiments on the flow past a circular cylinder at low Reynolds numbers. J. Fluid Mech. Digit. Arch. 6 (4), 547–567.CrossRefGoogle Scholar
Tseng, Y.-H. & Ferziger, J. H. 2003 A ghost-cell immersed boundary method for flow in complex geometry. J. Comput. Phys. 192 (2), 593–623.CrossRefGoogle Scholar
Williamson, C. H. K. 1996 a Three-dimensional wake transition. J. Fluid Mech. Digit. Arch. 328, 345–407.CrossRefGoogle Scholar
Williamson, C. H. K. 1996 b Vortex dynamics in the cylinder wake. Annu. Rev. Fluid Mech. 28, 477–539.CrossRefGoogle Scholar
Ye, T., Mittal, R., Udaykumar, H. S. & Shyy, W. 1999 An accurate Cartesian grid method for viscous incompressible flows with complex immersed boundaries. J. Comput. Phys. 156 (2), 209–240.CrossRefGoogle Scholar
Yilmaz, S. & Cliffe, K. R. 2000 Particle deposition simulation using the CFD code fluent. J. Inst. Energy pp. 65–68.Google Scholar