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Measurement of static loads is conventionally performed using a linear combination of strain gage measurements. For the case of a loading environment with energy content in the same frequency band as structural modes, measurements can be significantly corrupted. In this development, a method for accurately estimating the spectral content of an applied loading is presented. This is accomplished by performing system identification on the structural dynamic system using a prescribed forcing function. A linear filter is developed based on the identified plant that converts measured strain and acceleration data to an estimate of applied loads. Analytical and experimental results are presented for a simple structural dynamic system subjected to a prescribed forcing function.

A primary driver in cryogenic pump transfer functions is the presence of cavitation and cavitation instabilities in the pump's inducer. Fluid mode frequencies in a water test loop are measured and confirmed to be planar wave surge (cavitation surge) through analysis of an array of dynamic pressure transducers. In addition, steady computational fluid dynamics (CFD) simulations are conducted and used to estimate the cavitation compliance and mass flow gain factor at both room temperature and elevated temperature where thermal suppression effects are dominant. Excellent agreement is found between measured fluid mode frequencies and predictions using compliance estimated from steady CFD and the inlet feedline inertance. AbstractA primary driver in cryogenic pump transfer functions is the presence of cavitation and cavitation instabilities in the pump's inducer. Fluid mode frequencies in a water test loop are measured and confirmed to be planar wave surge (cavitation surge) through analysis of an array of dynamic pressure transducers. In addition, steady computational fluid dynamics (CFD) simulations are conducted and used to estimate the cavitation compliance and mass flow gain factor at both room temperature and elevated temperature where thermal suppression effects are dominant. Excellent agreement is found between measured fluid mode frequencies and predictions using compliance estimated from steady CFD and the inlet feedline inertance.

A computational aeroelastic model based on the ONERA M6 wing configuration is studied over a range of transonic flight conditions and structural stiffness parameters. A reduced-order modeling (ROM) approach is used, consisting of linear state-space models based on nonlinear CFD results. The structural component of the models is generated by converting a finite-element model to modal form, while the aerodynamic component is generated via Roger's Rational Function Approximation (RFA). It is shown that although the state-space models are linear, they are effective at predicting conditions where the full nonlinear model shows instabilities, including instabilities unique to the transonic regime such as high-altitude flutter and single-degree of freedom flutter. Nomenclature[A] State matrix of a state-space model [A 0 ] Constant term in Roger's Rational Function Approximation [A 1 ] Linear term in Roger's Rational Function Approximation [A 2 ] Quadratic term in Roger's Rational Function Approximation [A A ] Aerodynamic state matrix [a] Matrix of actuator delay constants [B l ] Curve fit term corresponding to aerodynamic lag term l in Roger's Rational Function Approximation [B 0 A ] Aerodynamic input matrix corresponding to displacement input [B 1 A ] Aerodynamic input matrix corresponding to velocity input [B 2 A ] Aerodynamic input matrix corresponding to acceleration input {B A } N l × 1 vector fully populated with values of 1.0 [C] Output matrix of a state-space model [C A ] Aerodynamic output matrix [C d ] Nodal damping matrix from structural model C d Modal damping matrix c Wing chord length [D] Feedthrough matrix of a state-space model [D 0 A ] Aerodynamic feedthrough matrix corresponding to displacement input [D 1 A ] Aerodynamic feedthrough matrix corresponding to velocity input [D 2 A ] Aerodynamic feedthrough matrix corresponding to acceleration input {d} Nodal displacement vector from structural model {F } Force vector from structural model {F } Modal force vector F (k) Generalized aerodynamic force as function of reduced frequency f (t) Generalized aerodynamic force as function of time f Aeroservoelastic modal frequency