11:00   High speed aeroelasticity 2 Chair: Xuerui Wang 11:00 30 mins Measurement of Natural Frequency and Damping of a Slender Model in Mach 5 Flow Benjamin Diaz Villa, Marc Eitner, Jayant Sirohi, Noel Clemens Abstract: Hypersonic vehicles that have a high slenderness ratio are prone to aerothermoelastic deformations that can affect maneuverability. The goal of this study is to assess the effectiveness of different types of structural excitation as well as damping extraction algorithms to identify the natural frequency and damping of a representative cone-cylinder model in Mach 5 flow. The conical and cylindrical sections were rigid, but were connected by a flexure element that restricted the cone’s dynamics to a pitching motion only. This single degree of freedom system was excited in Mach 5 flow using two different structural excitation methods: exposing the model to free-stream turbulence, and harmonically forcing the structure with an embedded vibrating motor. These excitation techniques were used to infer the aerodynamic stiffness and aerodynamic damping using several analysis techniques. Algorithms such as the Random Decrement technique and the Natural Excitation technique were used to generate a free-decay response from the free-stream turbulence forcing cases. The Moving-Block technique and the Continuous Wavelet Transform were used to calculate the wind-on damping ratio from all wind-on signals. Wind-off and wind-on comparisons of the structure’s natural frequency and damping ratio were made. Wind-on natural frequencies were measured to be lower than wind-off cases, while wind-on damping ratios were measured to be higher than the wind-off cases. These results indicate that aerodynamic forces contribute negative stiffness and positive damping to the system for this particular structural setup. In summary, both structural excitation methods prove useful for aeroelastic studies in long-duration hypersonic wind tunnels. 11:30 30 mins Experimental Validation of Strain-Load Neural Network Model on a Slender Hypersonic Vehicle Ana Cristine Meinicke, Carlos Cesnik, Brianna Blocher, Aditya Panigrahi, Jayant Sirohi, Noel Clemens Abstract: Recovery of in-flight loads is crucial for guidance, navigation, and control. The harsh aerothermal conditions experienced in hypersonic flight provide additional challenges for conventional sensors typically installed on the outer surface of the structure. This study investigates a novel vehicle-as-a-sensor concept, where internal measurements of the vehicle’s deformed state are used to infer the loading it is subjected to. The proposed inverse model for this problem consists of a neural network, where strain measured through fiber optic sensors characterizes the deformed state and is used as an input to the machine learning algorithm which outputs the load state. An experimental testbed consisting of an aluminum scaled representative version of the IC3X, a slender hypersonic vehicle, is used as a proof of concept. A finite element model is developed and verified against results of a ground vibration test. The testbed is instrumented with fiber optic strain sensors along the length of the vehicle and force is applied through four actuators attached to load cells. Several static loading cases consisting of combinations of the various actuators are used to evaluate discrepancies between the as-built structure’s response and the predictions from the model. Calibration factors are applied to the model strain results to account for manufacturing of the aluminum model and sensor installation uncertainties, such as thickness of the adhesive layer used to attach the optical fibers to the model surface. The neural network is trained with data consisting of numerical load and strain pairs under conditions spanning those of the experiment. The neural network-based inverse model is validated against the experimental data and compared with a Data-Driven Force Reconstruction method that assumes a linear relation between strain and force. Errors on load recovery given the strain measurements are quantified. 12:00 30 mins Hot-wall shock-wave boundary layer interaction of a compliant cantilever in hypersonic flow Dylan Dooner, Nicholas Giannelis, Andrew Neely Abstract: Two-dimensional coupled fluid-structure simulations have been performed using a commercial fluid simulation package to compare the response of a cantilever panel subject to laminar shock-impingement (UNSW's HyMAX) with baseline and elevated wall-temperatures at experimentally comparable flow conditions. This comparison serves as a preliminary study on the value of extending the existing HyMAX case to a heated condition. The thermal state was applied using an isothermal wall with altered elastic modulus and density in the structure. During the simulation, the tip x- and y-deflections, and x- and y-forces were tracked to produce timeseries. These timeseries were then processed using perturbation extraction, and autoregressive power spectral density estimation. Additionally, surface pressure coefficient distributions were extracted. From these results it is shown that the hot case experienced over double the y-force and y-deflection at a lower frequency within the same time-frame. At equivalent deflected states, the hot case experienced 8.4% more y-force when deflected down, and 3.5% less y-force when deflected up. This incremental force variance, coupled with a 28% reduction in elastic modulus and 2.5% reduction in density, leads to the aforementioned significant increase in deflection.

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