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Study on high-Weber-number droplet collision by a parallel, adaptive interface-tracking method

Published online by Cambridge University Press:  20 October 2014

Chih-Kuang Kuan
Affiliation:
Department of Aerospace Engineering, University of Michigan, Ann Arbor, 1320 Beal Avenue, Ann Arbor, MI 48109, USA
Kuo-Long Pan
Affiliation:
Department of Mechanical Engineering, National Taiwan University, No. 1 Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, ROC
Wei Shyy*
Affiliation:
Department of Mechanical and Aerospace Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
*
Email address for correspondence: [email protected]

Abstract

We have established a parallel, adaptive interface-tracking framework in order to conduct, based on the framework, direct simulation of binary head-on droplet collision in the high-Weber-number regime (from 200 to 1500) that exhibits complex topological changes and substantial length scale variations. The overall algorithms include a combined Eulerian and Lagrangian solver to track moving interfaces, conservative Lagrangian mesh modification and reconstruction, cell-based unstructured adaptive mesh refinement (AMR) in the Eulerian solver, and associated Eulerian and Lagrangian domain partitions to minimize communication overhead. Based on the combined computational and experimental efforts, we have resolved for the first time the free-surface instabilities of the colliding droplets at such high Weber number. We detail the characteristics of coalescence, stretch, end pinching, fingering, free-surface movement and drop breakup. The Taylor–Culick rim is present soon after the collision. Furthermore, we observe two types of longitudinal instabilities on the rim, namely, the Rayleigh–Taylor (RT)-type instability in the initial deceleration phase of the circular sheet right after droplet coalescence, and later the Rayleigh–Plateau (RP) instabilities. As the Taylor–Culick rim disintegrates in the retraction phase, fingering effect is profound and resulting in wider droplet size distribution.

Type
Papers
Copyright
© 2014 Cambridge University Press 

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References

Agbaglah, G., Delaux, S., Fuster, D., Hoepffner, J., Josserand, C., Popinet, S., Ray, P., Scardovelli, R. & Zaleski, S. 2011 Parallel simulation of multiphase flows using octree adaptivity and the volume-of-fluid method. C. R. Méc 339, 194207.Google Scholar
Agbaglah, G., Josserand, C. & Zaleski, S. 2013 Longitudinal instability of a liquid rim. Phys. Fluids 25, 022103.Google Scholar
Anderson, W. E., Ryan, H. M. & Santoro, R. J. 1995 Impinging jet injector atomization. In Liquid Rocket Engine Combustion Instability (ed. Yang, V. & Anderson, W. E.), pp. 220222. AIAA.Google Scholar
Ashgriz, N. & Poo, J. Y. 1990 Coalescence and separation in binary collisions of liquid drops. J. Fluid Mech. 221, 183204.CrossRefGoogle Scholar
Ashgriz, N. & Yarin, A. L. 2011 Capillary instability of free liquid jets. In Handbook of Atomization and Sprays: Theory and Applications (ed. Ashgriz, N.), pp. 3134. Springer.Google Scholar
Balay, S., Brown, J., Buschelman, K., Eijkhout, V., Gropp, W. D., Kaushik, D., Knepley, M. G., McInnes, L. C., Smith, B. F. & Zhang, H.2012 PETSc users manual. Tech. Rep. Argonne National Laboratory.Google Scholar
Bo, W., Liu, X., Glimm, J. & Li, X. 2011 A robust front tracking method: verification and application to simulation of the primary breakup of a liquid jet. SIAM J. Sci. Comput. 33, 15051524.Google Scholar
Burstedde, C., Wilcox, L. C. & Ghattas, O. 2011 Scalable algorithms for parallel adaptive mesh refinement on forests of octrees. SIAM J. Sci. Comput. 33, 11031133.Google Scholar
Capecelatro, J. & Desjardins, O. 2013 An Euler–Lagrange strategy for simulating particle-laden flows. J. Comput. Phys. 238, 131.Google Scholar
Chen, X. & Yang, V. 2014 Thickness-based adaptive mesh refinement methods for multi-phase flow simulations with thin regions. J. Comput. Phys. 269, 2239.Google Scholar
Correa, S. M. & Shyy, W. 1987 Computational models and methods for continuous gaseous turbulent combustion. Prog. Energy Combust. Sci. 13, 249292.Google Scholar
Culick, F. E. C. 1960 Comments on a ruptured soap film. J. Appl. Phys. 31, 11281129.Google Scholar
Darmana, D., Deen, N. G. & Kuipers, J. A. M. 2006 Parallelization of an Euler–Lagrange model using mixed domain decomposition and a mirror domain technique: application to dispersed gas–liquid two-phase flow. J. Comput. Phys. 220, 216248.Google Scholar
Deiterding, R. 2009 A parallel adaptive method for simulating shock-induced combustion with detailed chemical kinetics in complex domains. Comput. Struct. 87, 769783.CrossRefGoogle Scholar
Faeth, G. M. 1983 Evaporation and combustion of sprays. Prog. Energy Combust. Sci. 9, 176.Google Scholar
Falgout, R. D. & Yang, U. M. 2002 hypre: a library of high performance preconditioners. In Computational Science—ICCS 2002 (ed. Sloot, P. M. A., Tan, C. J. K., Dongarra, J. J. & Hoekstra, A. G.), vol. 2331, pp. 632641. Springer.Google Scholar
Gotaas, C., Havelka, P., Jakobsen, H. A., Svendsen, H. F., Hase, M., Roth, N. & Weigand, B. 2007 Effect of viscosity on droplet–droplet collision outcome: experimental study and numerical comparison. Phys. Fluids 19, 102106.CrossRefGoogle Scholar
Gunney, B. T. N., Wissink, A. M. & Hysom, D. A. 2006 Parallel clustering algorithms for structured AMR. J. Parallel Distrib. Comput. 66, 14191430.Google Scholar
Herrmann, M. 2010 A parallel Eulerian interface tracking/Lagrangian point particle multi-scale coupling procedure. J. Comput. Phys. 229, 745759.CrossRefGoogle Scholar
Karypis, G. & Kumar, V.METIS: unstructured graph oartitioning and sparse matrix ordering system, version 4.0. Available at http://www.cs.umn.edu/metis.Google Scholar
Kuan, C.-K.2013 Parallel processing of Eulerian–Lagrangian, cell-based adpative method for moving boundary problems. PhD thesis, University of Michigan, Ann Arbor.Google Scholar
Kuan, C.-K., Sim, J. & Shyy, W. 2012 Adaptive thermo-fluid moving boundary computations for interfacial dynamics. Acta Mechanica Sin. 28, 9991021.Google Scholar
Law, C. K. 2010 Combustion Physics. pp. 559564. Cambridge University Press.Google Scholar
MacNeice, P., Olson, K. M., Mobarry, C., de Fainchtein, R. & Packer, C. 2000 PARAMESH: a parallel adaptive mesh refinement community toolkit. Comput. Phys. Commun. 126, 330354.Google Scholar
Nkonga, B. & Charrier, P. 2002 Generalized parcel method for dispersed spray and message passing strategy on unstructured meshes. Parallel Comput. 28, 369398.CrossRefGoogle Scholar
Ongaro, T. E., Cavazzoni, C., Erbacci, G., Neri, A. & Salvetti, M. V. 2007 A parallel multiphase flow code for the 3D simulation of explosive volcanic eruptions. Parallel Comput. 33, 541560.Google Scholar
Pan, K.-L., Chou, P.-C. & Tseng, Y.-J. 2009 Binary droplet collision at high Weber number. Phys. Rev. E 80, 036301.Google Scholar
Pan, K.-L., Law, C. K. & Zhou, B. 2008 Experimental and mechanistic description of merging and bouncing in head-on binary droplet collision. J. Appl. Phys. 103, 064901.Google Scholar
Pan, Y. & Suga, K. 2005 Numerical simulation of binary liquid droplet collision. Phys. Fluids 17, 082105.Google Scholar
Pan, K.-L. & Yin, G.-C. 2012 Parallel strategies of front-tracking method for simulation of multiphase flows. Comput. Fluids 67, 123129.Google Scholar
Peskin, C. S. 2002 The immersed boundary method. Acta Numerica 11, 479517.Google Scholar
Plimpton, S. 1995 Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117, 119.Google Scholar
Qian, J. & Law, C. K. 1997 Regimes of coalescence and separation in droplet collision. J. Fluid Mech. 331, 5980.Google Scholar
Roisman, I. V., Berberović, E. & Tropea, C. 2009 Inertia dominated drop collisions. I. On the universal flow in the lamella. Phys. Fluids 21, 052103.Google Scholar
Savva, N. & Bush, J. W. M. 2009 Viscous sheet retraction. J. Fluid Mech. 626, 211240.CrossRefGoogle Scholar
Shyy, W., Correa, S. M. & Braaten, M. E. 1988 Computation of flow in a gas turbine combustor. Combust. Sci. Technol. 58, 97117.Google Scholar
Sim, J. & Shyy, W. 2012 Interfacial flow computations using adaptive Eulerian–Lagrangian method for spacecraft applications. Intl J. Numer. Meth. Fluids 68, 14381456.CrossRefGoogle Scholar
Singh, R. & Shyy, W. 2007 Three-dimensional adaptive Cartesian grid method with conservative interface restructuring and reconstruction. J. Comput. Phys. 224, 150167.CrossRefGoogle Scholar
Song, M. & Tryggvason, G. 1999 The formation of thick borders on an initially stationary fluid sheet. Phys. Fluids 11, 24872493.Google Scholar
Strutt, J. W. & Rayleigh, L. 1878 On the instability of jets. Proc. Lond. Math. Soc. 10, 413.Google Scholar
Sussman, M. 2005 A parallelized, adaptive algorithm for multiphase flows in general geometries. Comput. Struct. 83, 435444.Google Scholar
Taylor, G. I. 1950 The instability of liquid surfaces when accelerated in a direction perpendicular to their planes. I. Waves on fluid sheets. Proc. R. Soc. Lond. A 201, 192196.Google Scholar
Taylor, G. I. 1959 The dynamics of thin sheets of fluid. III disintegration of fluid sheets. Proc. R. Soc. Lond. A 253, 313321.Google Scholar
Uzgoren, E., Sim, J. & Shyy, W. 2009 Marker-based, 3-D adaptive Cartesian grid method for multiphase flow around irregular geometries. Commun. Comput. Phys. 5, 141.Google Scholar
Uzgoren, E., Singh, R., Sim, J. & Shyy, W. 2007 Computational modeling for multiphase flows with spacecraft application. Prog. Aerosp. Sci. 43, 138192.Google Scholar
Zhang, L. V., Brunet, P., Eggers, J. & Deegan, R. D. 2010 Wavelength selection in the crown splash. Phys. Fluids 22, 122105.Google Scholar