Abstract
It is not easy for the system identification-based reduced-order model (ROM) and even eigenmode based reduced-order model to predict the limit cycle oscillation generated by the nonlinear unsteady aerodynamics. Most of these traditional ROMs are sensitive to the flow parameter variation. In order to deal with this problem, a support vector machine- (SVM-) based ROM was investigated and the general construction framework was proposed. The two-DOF aeroelastic system for the NACA 64A010 airfoil in transonic flow was then demonstrated for the new SVM-based ROM. The simulation results show that the new ROM can capture the LCO behavior of the nonlinear aeroelastic system with good accuracy and high efficiency. The robustness and computational efficiency of the SVM-based ROM would provide a promising tool for real-time flight simulation including nonlinear aeroelastic effects.
Highlights
Aeroelasticity is the science concerned with the fluid-structure interaction including the inertial, elastic, and aerodynamic forces
With the development of computational aeroelasticity, the nonlinear aeroelastic response can be accurately predicted by the high-fidelity physics-based CFD/CSD couple solver
In order to reduce the expensive computational cost, a novel conception called reduced-order model ROM based on highfidelity physics model has been put forward in recent years
Summary
Aeroelasticity is the science concerned with the fluid-structure interaction including the inertial, elastic, and aerodynamic forces. Many approaches for constructing linear flow and aeroelastic ROMs have been developed and shown to produce good numerical results that compare well with high-fidelity nonlinear solvers. Most aeroelastic phenomena such as flutter and gust response can be deal with these ROMs based on the dynamically linearized equation. We proposed a new dynamically nonlinear NPOD/ROM, which enables the rapid modeling of nonlinear unsteady flows for the prediction and control of LCO 9, 10. These recently developed high-order ROMs for LCO simulation are much more complex than traditional ROMs and are not easy to realize in code. We gave a brief introduction about the regression SVM machine; secondly, we proposed a general construction framework of the SVM-based ROM for the aeroelastic system; we demonstrated the ROM by the two-DOF NACA 64A010 airfoil aeroelastic model in detail
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