Surrogate Based Reduced-Order Aerothermodynamic Modeling for Structural Response Prediction at High Mach Numbers

摘要

One of the primary challenges for hypersonic aerothermoelastic analysis of air-breathing hypersonic vehicles is accurate and efficient computation of the unsteady aerothermodynamic loads, where currently approaches are limited to either simple engineering level approximations or expensive Computational Fluid Dynamics. This study aims to fill the modeling gap between these two extremes by constructing computationally efficient surrogates for CFD predictions of the unsteady aerodynamic pressure loads. A novel aspect of the work is the use of steady-state CFD data for the surrogate, corrected for unsteady effects using piston-theory aerodynamics. Validation of the steady-state surrogate is achieved by comparing to 500 steady-state full order CFD cases. Results indicate that the surrogate generally has less than 1% RMS error. Comparison of the unsteady generalized aerodynamic forces computed using the corrected surrogate, third-order piston theory, unsteady Euler, and unsteady Navier-Stokes aerodynamics demonstrates that the developed surrogate method produces predictions superior to unsteady Euler solutions and piston theory, at a computational cost similar to that of piston theory. The surrogate is also implemented into a dynamic aerothermoelastic panel simultation, and compared with previous results using analytical approaches. The comparison reveals differences of over 100% in the onset time to flutter, and significantly altered post-flutter responses. The surrogate framework is found to enable a reasonably accurate, robust, and efficient method for incorporating CFD loads prediction, which would otherwise be impractical, into a long time-record aerothermoelastic analysis of structures for a complete hypersonic trajectory.