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Binary collision of CMAS droplets—Part I: Equal-sized droplets

Published online by Cambridge University Press:  23 June 2020

Himakar Ganti*
Affiliation:
Department of Aerospace Engineering, University of Cincinnati, Cincinnati, Ohio45221-0070, USA
Prashant Khare*
Affiliation:
Department of Aerospace Engineering, University of Cincinnati, Cincinnati, Ohio45221-0070, USA
Luis Bravo
Affiliation:
Vehicle Technology Directorate, Army Research Laboratory, Aberdeen Proving Ground, Maryland21005, USA
*
a)Address all correspondence to these authors. e-mail: [email protected]
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Abstract

This study focuses on binary droplet collisions of equal calcium–magnesium–aluminosilicate (CMAS) droplets formed by the melting of dust and sand ingested by gas turbine engines. Head-on, off-center, and grazing collision of 1 mm CMAS droplets traveling toward each other at a relative velocity of 100 m/s are numerically investigated using a volume-of-fluid-based direct numerical simulation approach at operating pressure and temperature of 20 atm and 1548 K, respectively. It is found that head-on and off-center collisions lead to droplet coalescence, whereas stretching behavior is observed for the grazing configuration. To elucidate the effect of viscosity, a fictitious fluid with all properties the same as CMAS except for viscosity (1/10 of CMAS) is also studied. It is found that the lower viscosity liquid deforms significantly as compared to CMAS for the head-on and off-center cases. These differences are quantified using the budgets of kinetic, surface, and dissipation energies. This paper represents the first study of its kind on the binary collision of CMAS droplets.

Type
Invited Paper
Copyright
Copyright © The Author(s), 2020, published on behalf of Materials Research Society by Cambridge University Press

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References

Filippone, A. and Bojdo, N.: Turboshaft engine air particle separation. Prog. Aerosp. Sci. 46, 224245 (2010).CrossRefGoogle Scholar
Murugan, M., Ghoshal, A., Nieto, A., Walock, M., Bravo, L., Jain, N., Pepi, M., Swab, J., Zhu, D., Pegg, R.T., Rowe, C., Flatau, A., and Kerner, K.: Prevention of molten sand attack on thermal barrier coatings for rotorcraft gas turbine blades – A round Robin test evaluation. In Annual Forum Proceedings (AHS International, Fairfax, VA, USA, 2018).Google Scholar
Larry Fehrenbacher, D.K., Kutsch, J., Vesnovsky, I., Fehrenbacher, E., Ghoshal, A., Walock, M., Murugan, M., and Nieto, A.: Advanced environmental barrier coatings for SiC CMCs. In Advances in Ceramics for Environmental, Functional, Structural, and Energy Applications II, Vol. 266. Mahmoud, M.M., Sridharan, K., Colorado, H., Bhalla, A.S., Singh, J.P., Gupta, S., Langhorn, J., Jitianu, A., and Manjooran, N. Jose, eds (John Wiley & Sons, Hoboken, NJ, USA, 2019); pp. 8393.Google Scholar
Ghoshal, A., Murugan, M., Walock, M.J., Nieto, A., Bravo, L., Barnett, B., Pepi, M., Hoffmeister Mock, C., Swab, J., and Hirsch, S.: Sandphobic coatings and surface modification of hot section components of next generation VTOL engines: Current and future research efforts. In Forum, Joint Propulsion Conference, Cincinnati, OH USA (AIAA, Reston, VA, USA, 2018); p. 4831.Google Scholar
Whitaker, S. M. and Bons, J. P.: An improved particle impact model by accounting for rate of strain and stochastic rebound. In Proceedings of ASME Turbo Expo (IGTI), Oslo, Norway (ASME, New York, NY, USA, 2018).Google Scholar
Yu, K. and Tafti, D.: Size- and temperature-dependent collision and deposition model for micron-sized sand particles. J. Turbomach. 141, 031001-1–031001-11 (2019).CrossRefGoogle Scholar
Song, W., Yang, S., Fukumoto, M., Lavallée, Y., Lokachari, S., Guo, H., You, Y., and Dingwell, D.B.: Impact interaction of in-flight high-energy molten volcanic ash droplets with jet engines. Acta Mater. 171, 119131 (2019).CrossRefGoogle Scholar
Singh, S. and Tafti, D.: Particle deposition model for particulate flows at high temperatures in gas turbine components. Int. J. Heat Fluid Flow 52, 7283 (2015).CrossRefGoogle Scholar
Pearson, D. and Brooker, R.: The accumulation of molten volcanic ash in jet engines: Simulating the role of magma composition, ash particle size and thermal barrier coatings. J. Volcanol. Geotherm. Res. 389, 106707 (2020).CrossRefGoogle Scholar
Libertowski, N., Plewacki, N., and Bons, J.P.: The effect of temperature and melting relative to particle deposition in gas turbines. In AIAA Scitech 2019 Forum, Jan 7 to 11, San Diego, CA, USA (American Institute of Aeronautics and Astronautics, Reston, VA, USA, 2019).Google Scholar
Hsu, K., Barker, B., Varney, B., Boulanger, A., Nguyen, V., and Ng, W.F.: Review of heated sand particle deposition models. In Proceedings of ASME Turbo Expo (IGTI), Oslo, Norway (ASME, New York, NY, USA, 2018).Google Scholar
Guha, A.: Transport and deposition of particles in turbulent and laminar flow. Annu. Rev. Fluid Mech. 40, 311341 (2008).CrossRefGoogle Scholar
Crowe, E.D. and Bons, J.P.: Effects of dust composition on particle deposition in an effusion cooling geometry. In Proceedings of ASME Turbo Expo (IGTI), Phoenix, AZ, USA (ASME, New York, NY, USA, 2019).Google Scholar
Bons, J.P., Prenter, R., and Whitaker, S.: A simple physics-based model for particle rebound and deposition in turbomachinery. J. Turbomach. 139, 081009-1–081009-12 (2017).CrossRefGoogle Scholar
Bojdo, N., Ellis, M., Filippone, A., Jones, M., and Pawley, A.: Particle-Vane interaction probability in gas turbine engines. J. Turbomach. 141, 091010-1–091010-13 (2019).CrossRefGoogle Scholar
Murugan, M., Ghoshal, A., Walock, M.J., Barnett, B.D., Pepi, M.S., and Kerner, K.A.: Sand particle-induced deterioration of thermal barrier coatings on gas turbine blades. Adv. Aircr. Spacecr. Sci. 4, 3752 (2017).CrossRefGoogle Scholar
Murugan, M., Ghoshal, A., Walock, M., Nieto, A., Bravo, L., Barnett, B., Pepi, M., Swab, J., Pegg, R.T., Rowe, C., Zhu, D., and Kerner, K.: Microstructure based materials and particulate interactions and assessment of coatings for high temperature turbine blades. In Proceedings of ASME Turbo Expo (IGTI), Charlotte, NC USA (ASME, New York, NY, USA, 2017).Google Scholar
Ghoshal, A., Murugan, M., Walock, M.J., Nieto, A., Barnett, B.D., Pepi, M.S., Swab, J.J., Zhu, D., Kerner, K.A., Rowe, C.R., Shiao, C.Y., Hopkins, D.A., and Gazonas, G.A.: Molten particulate impact on tailored thermal barrier coatings for gas turbine engine. J. Eng. Gas Turbines Power 140 (2018).CrossRefGoogle Scholar
Bravo, L.G., Xue, Q., Murugan, M., Ghoshal, A., Walock, M., and Flatau, A.: Particle transport analysis of sand ingestion in gas turbine jet engines. In 53rd AIAA/SAE/ASEE Joint Propulsion Conference, Jul 10 to Jul 12, Atlanta, GA, USA (AIAA, Reston, VA, USA, 2017); pp. 1–14Google Scholar
Jain, N., Bravo, L., Bose, S., Kim, D., Murugan, M., Ghoshal, A., and Flatau, A.: Turbulent multiphase flow and particle deposition of sand ingestion for high-temperature turbine blades. In Proceedings of the Summer Program, Jun 24 to Jul 20, Stanford, CA, USA (Center for Turbulence Research, Stanford, CA, USA, 2018); pp. 3544.Google Scholar
Qian, J. and Law, C.K.: Regimes of coalescence and separation in droplet collision. J. Fluid Mech. 331, 5980 (1997).CrossRefGoogle Scholar
Pan, K.-L., Law, C.K., and Zhou, B.: Experimental and mechanistic description of merging and bouncing in head-on binary droplet collision. J. Appl. Phys. 103, 064901 (2008).CrossRefGoogle Scholar
Nobari, M.R., Jan, Y.J., and Tryggvason, G.: Head-on collision of drops—A numerical investigation. Phys. Fluids 8, 2942 (1996).CrossRefGoogle Scholar
Liu, M. and Bothe, D.: Numerical study of head-on droplet collisions at high weber numbers. J. Fluid Mech. 789, 785805 (2016).CrossRefGoogle Scholar
Kuan, C.-K., Pan, K.-L., and Shyy, W.: Study on high-Weber-number droplet collision by a parallel, adaptive interface-tracking method. J. Fluid Mech. 759, 104133 (2014).CrossRefGoogle Scholar
Jia, X., Yang, J.-C., Zhang, J., and Ni, M.-J.: An experimental investigation on the collision outcomes of binary liquid metal droplets. Int. J. Multiphase Flow 116, 8090 (2019).CrossRefGoogle Scholar
Chen, X., Ma, D., Khare, P., and Yang, V.: Energy and mass transfer during binary droplet collision. In 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition (American Institute of Aeronautics and Astronautics: Orlando, FL, USA, 2011); pp. 1–17.Google Scholar
Ashgriz, N. and Poo, J.Y.: Coalescence and separation in binary collisions of liquid drops. J. Fluid Mech. 221, 183204 (1990).CrossRefGoogle Scholar
Chen, X., Ma, D., Khare, P., and Yang, V.: Energy and mass transfer during binary droplet collision. In 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Jan 4 to Jan 7, Orlando, FL, USA (AIAA, Reston, VA, USA, 2011); pp. 114.Google Scholar
Gotaas, C., Havelka, P., Jakobsen, H.A., Svendsen, H.F., Hase, M., Roth, N., and Weigand, B.: Effect of viscosity on droplet-droplet collision outcome: Experimental study and numerical comparison. Phys. Fluids 19, 102106 (2007).CrossRefGoogle Scholar
Focke, C. and Bothe, D.: Direct numerical simulation of binary off-center collisions of shear thinning droplets at high Weber numbers. Phys. Fluids 24, 073105 (2012).CrossRefGoogle Scholar
Sommerfeld, M. and Kuschel, M.: Modelling droplet collision outcomes for different substances and viscosities. Exp. Fluids 57, 187 (2016).CrossRefGoogle Scholar
Cohen, I.M., Kundu, P.K., and Dowling, D.R.: Fluid Mechanics, 5th ed. (Academic Press, Waltham, MA, USA, 2012).Google Scholar
White, F.. Viscous Fluid Flow, 3rd ed. (McGraw Hill, New York, NY, USA, 2006).Google Scholar
Desjardins, O. and Moureau, V.: Methods for multiphase flows with high density ratio. In Proceedings of the Summer Program, Jun 27 to Jul 23, Stanford, CA, USA (Center for Turbulence Research, Stanford, CA, USA, 2010); pp. 313–322.Google Scholar
Gorokhovski, M. and Herrmann, M.: Modeling primary atomization. Ann. Rev. Fluid Mech. 40, 343366 (2008).CrossRefGoogle Scholar
Popinet, S.: An accurate adaptive solver for surface-tension-driven interfacial flows. J. Comput. Phys. 228, 58385866 (2009).CrossRefGoogle Scholar
Gerlach, D., Tomar, G., Biswas, G., and Durst, F.: Comparison of volume-of-fluid methods for surface tension-dominant two-phase flows. Int. J. Heat Mass Transfer 49, 740754 (2006).CrossRefGoogle Scholar
Khare, P. and Yang, V.: Breakup of non-Newtonian liquid droplets. In 44th AIAA Fluid Dynamics Conference, Jan 16 to Jan 20, Atlanta, GA, USA (AIAA, Reston, VA, USA, 2014).Google Scholar
Tryggvason, G., Scardovelli, R., and Zaleski, S.: Direct Numerical Simulations of Gas-Liquid Multiphase Flows (Cambridge University Press, New York, NY, USA, 2011).Google Scholar
Brackbill, J.U.U., Kothe, D.B.B., and Zemach, C.: A continuum method for modeling surface tension. J. Comput. Phys. 100, 335354 (1992).CrossRefGoogle Scholar
Popinet, S.: Gerris: A tree-based adaptive solver for the incompressible Euler equations in complex geometries. J. Comput. Phys. 190, 572600 (2003).CrossRefGoogle Scholar
Almgren, A.S., Bell, J.B., and Crutchfield, W.Y.: Approximate projection methods: Part I. inviscid analysis. SIAM J. Sci. Comput. 22, 11391159 (2000).CrossRefGoogle Scholar
Khare, P.: Breakup of liquid droplets. Ph.D. thesis, Georgia Institute of Technology, Atlanta, GA, USA, 2014.Google Scholar
Bell, J.: AMR for low Mach number reacting flow. In Adaptive Mesh Refinement – Theory and Applications. Lecture Notes in Computational Science and Engineering, vol 41. Plewa, T., Linde, T., and Weirs, V. Gregory, eds (Springer, Berlin, Heidelberg, Germany, 2006); pp. 203221.Google Scholar
Jourdren, H.: HERA: A hydrodynamic AMR platform for multi-physics simulations. In Adaptive Mesh Refinement – Theory and Applications. Lecture Notes in Computational Science and Engineering, vol 41. Plewa, T., Linde, T., and Weirs, V. Gregory, eds (Springer, Berlin, Heidelberg, Germany, 2006); pp. 283294.Google Scholar
Myers, C.R.: The dynamics of localized coherent structures and the role of adaptive software in multiscale modeling. In Structured Adaptive Mesh Refinement (SAMR) Grid Methods, Baden, S.B., Chrisochoides, N.P., Gannon, D.B., and Norman, M.L., eds (Springer, New York, NY, USA, 2000); pp. 111125.CrossRefGoogle Scholar
Pernice, M., Bockelie, M.J., Swensen, D., and Smith, P.J.: Progress, results, and experiences in developing an adaptive solver for steady state turbulent reacting flows in industrial boilers and furnaces. In Structured Adaptive Mesh Refinement (SAMR) Grid Methods, Baden, S.B., Chrisochoides, N.P., Gannon, D.B., and Norman, M.L., eds (Springer, New York, NY, USA, 2000); pp. 127151.CrossRefGoogle Scholar
Gamertsfelder, J., Khare, P., and Bravo, L.G.: Investigation of atomization behaviour of liquid monopropellants in pintle injectors. In Proceedings of ASME Turbo Expo (IGTI) 2020, June 22-26, London, England (ASME, New York, NY, USA, 2020).Google Scholar
Notaro, V., Khare, P., and Lee, J.G.: Mixing characteristics of non-Newtonian impinging jets at elevated pressures. Flow Turbul. Combust. 102, 355372 (2019).CrossRefGoogle Scholar
Ma, D.-J., Chen, X.-D., Khare, P., and Yang, V.: Atomization patterns and breakup characteristics of liquid sheets formed by two impinging jets. In 49th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Jan 4 to Jan 7, Orlando, FL, USA (AIAA, Reston, VA, USA, 2011); pp. 2011–2097.Google Scholar