INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS Int. J. Numer. Meth. Fluids 2008; 58:969–1007 Published online 17 March 2008 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/fld.1779 Surrogate model-based strategy for cryogenic cavitation model validation and sensitivity evaluation Tushar Goel 1, ‡ , Siddharth Thakur 1, § , Raphael T. Haftka 1, ¶ , Wei Shyy 2, ∗, †, ‖ and Jinhui Zhao 2 1 Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, U.S.A. 2 Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109, U.S.A. SUMMARY The study of cavitation dynamics in cryogenic environment has critical implications for the performance and safety of liquid rocket engines, but there is no established method to estimate cavitation-induced loads. To help develop such a computational capability, we employ a multiple-surrogate model-based approach to aid in the model validation and calibration process of a transport-based, homogeneous cryogenic cavitation model. We assess the role of empirical parameters in the cavitation model and uncertainties in material properties via global sensitivity analysis coupled with multiple surrogates including polynomial response surface, radial basis neural network, kriging, and a predicted residual sum of squares-based weighted average surrogate model. The global sensitivity analysis results indicate that the performance of cavitation model is more sensitive to the changes in model parameters than to uncertainties in material properties. Although the impact of uncertainty in temperature-dependent vapor pressure on the predictions seems significant, uncertainty in latent heat influences only temperature field. The influence of wall heat transfer on pressure load is insignificant. We find that slower onset of vapor condensation leads to deviation of the predictions from the experiments. The recalibrated model parameters rectify the importance of evaporation source terms, resulting in significant improvements in pressure predictions. The model parameters need to be adjusted for different fluids, but for a given fluid, they help capture the essential fluid physics with different geometry and operating conditions. Copyright 2008 John Wiley & Sons, Ltd. Received 15 February 2007; Revised 31 December 2007; Accepted 2 January 2008 KEY WORDS: cavitation; code validation; cryogenics; multiple surrogates; global sensitivity analysis ∗ Correspondence to: Wei Shyy, Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109, U.S.A. † E-mail: weishyy@umich.edu ‡ Currently with Livermore Software Technology Corporation, Livermore, CA, U.S.A. § Visiting Professor. ¶ Distinguished Professor. ‖ Clarence L. ‘Kelly’ Johnson Professor. Contract/grant sponsor: Institute for Future Space Transport Contract/grant sponsor: National Science Foundation; contract/grant number: 0423280 Copyright 2008 John Wiley & Sons, Ltd.