Abstract
A stochastic sensitivity analysis and calibration of the cavitation model parameters in the URANS simulations of a configuration representative of high-pressure injectors for automotive applications is carried out. A popular homogeneous-flow cavitation model is considered, in which the mass transfer due to cavitation is given by the Schnerr–Sauer model together with the classical Rayleigh–Plesset equation. A stochastic approach based on the generalized Polynomial Chaos (gPC) expansion is adopted, which allows continuous response surfaces of the quantities of interest in the parameter space to be obtained starting from a few deterministic simulations. The considered uncertain parameters are the so-called scaling factors. The calibration of these parameters is carried out by using the gPC response surfaces for a axisymmetric simplified geometry against the experimental value of the critical cavitation point, i.e. the condition at which the injector is choked. The procedure is carried out for two different turbulence models, viz. the k − ω SST and RSM models. The so-obtained optimal parameter set-ups are then validated for the real three-dimensional geometry. The k − ω SST optimal set-up gives very accurate predictions also in the three-dimensional case. Finally, the results obtained with this optimal set-up are compared to those given by standard values, confirming that the predictions of the different flow regimes occurring in high-pressure injectors are highly sensitive to cavitation model parameters.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Altimira, M., Fuchs, L.: Numerical investigation of throttle flow under cavitating conditions. Int. J. Multiphase Flow 75, 124–136 (2015). https://doi.org/10.1016/j.ijmultiphaseflow.2015.05.006
Anderlini A., Salvetti, M.V., Agresta, A., Matteucci, L.: Stochastic sensitivity analysis of numerical simulations of high-pressure injectors to cavitation modeling parameters. In: Proceedings of ASME-FEDSM2017 (2017). https://doi.org/10.1115/FEDSM2017-69212
Bergwerk, W.: Flow pattern in diesel nozzle spray holes. Proc. Inst. Mech. Eng. 173, 655–660 (1959)
Blessing, M., König, G., Krüger, C., Michels, U., Schwarz, V.: Analysis of flow and cavitation phenomena in diesel injection nozzles and its effect on spray and mixture formation. In: Proceedings of SAE 2003 World Congress and Exhibition (2003). https://doi.org/10.4271/2003-01-1358
Brennen, C.E.: Cavitation and Bubble Dynamics. Oxford University Press, Oxford (1995)
Cazzoli, G., Falfari, S., Bianchi, G.M., Forte, C., Catellani, C.: Assessment of the cavitation models implemented in OpenFOAM under DI-like conditions. Energy Proc. 101, 638–645 (2016). https://doi.org/10.1016/j.egypro.2016.11.081
Chaves, H., Knapp, M., Kubitzek, A., Obermeier, F., Schneider, T.: Experimental study of cavitation in the nozzle hole of diesel injectors using transparent nozzles. SAE technical paper (1995). https://doi.org/10.4271/950290
Goncalves, E., Patella, R.F.: Numerical simulation of cavitating flows with homogeneous models. Comput. Fluids 38, 1682–1696 (2009). https://doi.org/10.1016/j.compfluid.2009.03.001
Kiplimo, R., Tomita, E., Kawahara, N., Yokobe, S.: Effects of spray impingement, injection parameters, and EGR on the combustion and emission characteristics of a PCCI diesel engine. Appl. Thermal Eng. 37, 165–175 (2012)
Launder, B.E., Reece, G.J., Rodi, W.: Progress in the development of a Reynolds-Stress turbulence closure. J. Fluid Mech. 68, 537–566 (1975)
Menter, F.R.: Two-equation eddy-viscosity turbulence models for engineering applications. AIAA J. 32, 1598–1605 (1994)
Nurick, W.H.: Orifice cavitation and its effect on spray mixing. J. Fluids Eng. Trans. ASME 98, 681–687 (1976)
Orley, F., Trummler, T., Hickel, S., Mihatsch, M.S., Schmidt, S.J., Adams, N.A.: Large-Eddy simulation of cavitating nozzle flow and primary jet break-up. Phys. Fluids 27, 086101 (2015). https://doi.org/10.1063/1.4928701
Payri, R., Guardiola, C., Salvador, F.J., Gimeno, J.: Critical cavitation number determination in diesel injection nozzles. Exp. Tech. 28, 49–52 (2004)
Sauer, J., Schnerr, G.H.: Unsteady cavitating flow—a new cavitation model based on a modified front capturing method and bubble dynamics. In: Proceedings of the ASME-FEDSM2000, vol. 251, pp. 1073–1076 (2000)
Soteriou, C.C.E., Andrews, R., Smith, M.: Direct injection diesel sprays and the effect of cavitation and hydraulic flip on atomization. SAE technical paper 950080 (1995). https://doi.org/10.4271/950080
Sou, A., Tomiyama, A., Hosokawa, S., Nigorikawa, S., Maeda, T.: Cavitation in a two-dimensional nozzle and liquid jet atomization. JSME Int. J. B Fluids Thermal Eng. 49, 1253–1259 (2006)
STAR-CCM+ : Users Manual. http://www.cd-adapco.com/products/star-ccmdocumentation
Tree, D.R., Svensson, K.I.: Soot processes in compression ignition engines. Prog. Energy Combust. Sci. 33, 272–309 (2007)
Venkatakrishnan, V.: On the convergence of limiters and convergence to steady state solutions. AIAA J. (1993) https://doi.org/10.2514/6.1993-880
Xiu, D., Karniadakis, G.E.: The Wiener–Askey polynomial chaos for stochastic differential equations. SIAM J. Sci. Comput. 24, 619–644 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 National Technology & Engineering Solutions of Sandia, and The Editor(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Anderlini, A., Salvetti, M.V., Agresta, A., Matteucci, L. (2020). Cavitation Model Parameter Calibration for Simulations of Three-Phase Injector Flows. In: D'Elia, M., Gunzburger, M., Rozza, G. (eds) Quantification of Uncertainty: Improving Efficiency and Technology. Lecture Notes in Computational Science and Engineering, vol 137 . Springer, Cham. https://doi.org/10.1007/978-3-030-48721-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-48721-8_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48720-1
Online ISBN: 978-3-030-48721-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)