Aeroelasticity & Structural Dynamics in a Fast Changing World
17 – 21 June 2024, The Hague, The Netherlands
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13:30   Aeroelastic testing 3
Chair: Johannes Meijer
13:30
30 mins
System-search The simulation and flight verification of active aeroelastic control
Yi Liu, Kaihua Yuan, Xiaolong Cao, Yi Jin, Yang Meng
Abstract: Aeroelastic active control is an active and reasonable method to change the aerodynamic and structural characteristics of the aircraft by using structural deformation, which can enhance the stability control ability of the aircraft and improve the manoeuvrability and aerodynamic performance. The final aim is to reduce the structural response, expand the flight envelope, and improve the flight performance and flight safety. In this paper, the simulation and flight verification of active aeroelastic control technology are completed based on a flexible aeroelastic active control fight platform. The highest flight speed reached 200 km/h and the reduction of wing vibration is 30%, which laid a foundation for further application of aeroelastic active control technology to engineering model.
14:00
30 mins
System-search Wind tunnel flutter test results comparison with computational results of a half-span wing
Amanda Perroni, Breno Castro, Eduardo Krupa, Jens Neumann, Manoela Lima, Marlus Kerninski, Michelle Westin
Abstract: A half-span wing was designed for wind tunnel test for verification of aeroelastic characteristics in 2017. This wing was quite flexible and fitted with a pylon and a flow thru nacelle, to represent the geometry and mass distribution of real-life aircraft, but without propulsion effects, see fig.1. The wind tunnel used in 2017 for aeroelastic tests was the DNW-HST in Amsterdam, The Netherlands. The test was divided in two parts: the first campaign focused on wing deflection for each test point and on how the flexibility affected the flutter characteristics. The second part was dedicated to higher Mach numbers and low angles of attack to verify the effect of both flexibility and shock waves on the aeroelastic characteristics of the system. The wind tunnel test instrumentation included steady and unsteady pressure taps, accelerometers, strain gauges, stereo pattern recognition, and others. All the obtained results were in good agreement to the computational results, obtained by using traditional tools, such as Nastran. However, for the second entry, considering Mach numbers from 0.75 to 0.90, the behaviour of both damping and frequency are slightly different from the computational analysis, especially for the first five aeroelastic modes. The results were obtained for three different configurations by varying the wing tip mass. Since there are some differences between the experimental and computational results for the transonic regime, further analysis could be performed to explore the effects of aerodynamic nonlinearities. To investigate it in more detail, analyses using different computational tools for the transonic unsteady aerodynamics from Embraer and DLR will be used in the present paper and compared with the experimental results obtained in 2017. The focus is to use high fidelity methodologies based on coupled CFD/CSM-methods (computational fluid dynamics, computational structure mechanics) for the flexible model to better capture nonlinear phenomena that might be occurring during the wind tunnel tests.
14:30
30 mins
System-search Investigation on Sensor Selection Applied on a Vehicle-as-a-Sensor Concept in High-Speed Flight
Ana C. Meinicke, Carlos E. S. Cesnik
Abstract: The ability to estimate aerodynamic loads and flight parameters in flight using only internal sensors is desirable for guidance, navigation, and control. This is particularly true for harsh aerothermal environments experienced in supersonic and hypersonic flight, but it is also applicable to any other flight regime. The vehicle-as-a-sensor concept is a novel nonintrusive sensing strategy for airframes in flight. It leverages the internal measurement of the deformed state of the vehicle, its temperatures, and its accelerations to infer its aerodynamic state. An inverse model consisting of a strain-to-load, or strain/temperature-to-load, neural network trained with static elastic solutions of a detailed finite element model of a slender hypersonic vehicle is considered here. The deformed state of the vehicle is assumed to be measured with high-density strain and temperature measurements on its internal surface, enabled by the application of continuous fiber optic sensors. Constraints pertaining to the use of fiber optic sensors are considered, where limitations such as applying the optical cables only on the internal surface of the vehicle, and the necessity of choosing adequate strain component directions to recover the aerodynamic state with sufficient accuracy are accounted for. Inverse models considering selected sensors based on the physics involved in the problem are shown to successfully recover pressure distribution on the outer surface of the vehicle.
15:00
30 mins
System-search Reliable monitoring of modal parameters during a flight vibration test using autonomous modal analysis and a Kalman filter
Robin Volkmar, Julian Sinske, Keith Soal, Yves Govers, Marc Böswald
Abstract: Lightweight construction is required for efficient aircraft design, but it poses challenges due to loads and vibration during flight. Aircraft dynamic aeroelastic behavior, described by modal parameters like eigenfrequencies and damping ratios, varies with altitude and velocity, potentially leading to flutter—an unstable self-excited vibration. Predicting and preventing flutter involves identifying modal parameters through ground and flight vibration tests. However, uncertainties in flight tests, especially concerning damping ratio estimates, result from conditions regarding time-varying systems, low signal-to-noise ratios, and unobservable or unmeasured influences. This study proposes a real-time uncertainty estimation method using clustering-based automated modal analysis and uncertainty reduction using a Kalman filter. For the first time, the Kalman filter-based monitoring has been applied in-flight during a flight vibration test (FVT). The German Aerospace Center (DLR) operates the ISTAR research aircraft (In-flight Systems and Technology Airborne Research), a modified Dassault Falcon 2000 LX. In 2023, an FVT with ISTAR was conducted in Germany. ISTAR, which is permanently equipped with 62 accelerometers and a certified measurement system, records vibration data and operational parameters during every flight. The study shows some of the flight data collected by this extensively instrumented aircraft. The system continuously processes online streamed data every two seconds during the FVT, conducting spectral analysis, modal parameter identification, automated modal analysis (AMA), and Kalman filtering for robust flutter monitoring. The flight test campaign included varying flight levels, fast and slow accelerations and decelerations with and without artificial excitation, enabling a comprehensive comparison of output-only modal parameter identification methods. Monitoring based on the Kalman filter was able to track eigenfrequencies and damping ratios of the aircraft robustly and continuously. These results are promising for online assessment and reliable online prediction of flutter critical speeds; however, the fight tests were performed with the aircraft in a baseline configuration, which is flutter stable in the whole flight test envelope.


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