16:00   Ground vibration testing Chair: Jack Hagelin 16:00 30 mins Contribution of the ground vibration tests for the preparation of flutter suppression flight test campaigns: Case of the flipased P-Flex UAV Nicolas Guérin, Keith Soal, Cyrille Stephan, Martin Tang, Pascal Lubrina, Robin Volkmar, Yves Govers, Julius Bartasevicius, Daniel Teubl, Szabolcs Toth, Thiemo Kier, Balint Vanek Abstract: With the everlasting reach for lighter and more fuel-efficient aircraft structures, aircraft designs become more and more flexible. This leads to both increased deformation of the airframe under aerodynamic load, as well as more coupling between the structural static and dynamic behaviour and the surrounding airflow, potentially leading to the dreaded phenomenon of flutter. This dangerous behaviour has limited potential aircraft design optimization, hence impaired carbon footprint reduction. In order to circumvent this constraint, active flutter suppression through fast actuators and control surfaces was investigated during the FLEXOP and subsequent FLIPASED projects, on a research high aspect ratio fixed wing UAV. Such control strategies, though of great interest thanks to their capability to control a wide variety of behaviour, also come with great risks if badly designed. They must therefore be conceived with very good knowledge of the controlled structure, as well as properly verified through an extensive test phase. This paper focuses on the identification of the structural dynamic behaviour of the FLIPASED P-FLEX UAV during a Ground Vibration Test (GVT) campaign. The paper presents the GVT organization, from instrumentation to analysis, including test configurations accounting for high-bandwidth actuators as well as devices, designed to help increase or decrease the flutter coupling, so-called flutter stoppers. The paper describes the structural dynamic behaviour of the P-FLEX UAV and the influence of the different mechanical components on this behaviour. Numeric and experimental modal models are compared and discussed to highlight the main differences. Due to multiple specific features of this aircraft including high aspect ratio and custom designed high-bandwidth actuators, this GVT proved difficult to achieve for both organizational and technical reasons. The paper presents the main problems associated with these specific features and proposes improved test strategies for future GVTs. Although the P-FLEX UAV is of a peculiar design with respect to commercial aircraft, the observations made on this aircraft will be of great interest for future civilian aircraft designs that tend towards very high aspect ratio wings equipped with numerous active flutter suppression control surfaces. 16:30 30 mins Explainable nonlinear state-space modelling: analysing the GVT of a battery-operated aircraft Péter Zoltán Csurcsia, Tim De Troyer Abstract: Traditionally, ground vibration tests (GVTs) of aircraft are processed using modal analysis algorithms. Most algorithms that are in commercial use today are grounded in the domain of linear system identification. These tools have proven their worth and are still the state of the art in commercial aviation, even though advances have been made in the research community. One of the more promising advances is the ability now to develop fully nonlinear models from experimental data. This capability could drastically improve the amount of information that can be extracted from a GVT. So far, non-linear effects, which are common in structural vibration of aircraft (freeplay of control surfaces, stick-and-slip behaviour at hinges, large deformations of slender wings, nonlinear friction,…), were considered a distortion of the underlying linear aircraft model that was sought. However, instead of trying to reduce the impact of the nonlinear distortion, we show the benefit of including nonlinearities in the model structure. In this work, we utilise recently developed concepts (a nonlinear state selection method, nonlinear function decoupling, a single-branch neural network) embedded in a nonlinear state space modelling framework, to build a nonlinear, explainable, data-driven model. We illustrate the methodology first on an analytical example containing multiple linear modes and a nonlinear distortion, and compare the performance of classical linear techniques to our nonlinear modelling framework. Then, we demonstrate this framework on a real-life multiple-input-multiple-output (MIMO) ground vibration test of the Magnus eFusion light sports aircraft. 17:00 30 mins Ground Vibration Testing and Model Update of a Transonic Flutter Wind Tunnel Model Anders Ellmo Abstract: Using complex composite structures in a wind tunnel model means that small differences in layup, thickness and other manufacturing outcomes will result in significant consequences for the structural dynamic properties of the model, and subsequently its aeroelastic behaviour. The KTH-NASA wind tunnel model has interchangeable wings, and it is shown that finite element representations of each individual wing are needed to make relevant comparisons to experimental data, and accurate predictions of flutter behaviour. The KTH-NASA wind tunnel model is constructed for acquiring flutter data in transonic conditions. It is specifically designed for the conditions at the NASA Transonic Dynamics Tunnel, and was tested there in 2016. That test ended pre- maturely since the wings were damaged in a flutter incident after recording two flutter points. The damage to the wings was an opportunity to re-design the wings to allow flutter without external stores mounted. The strategy chosen was to replace a plain weave in the glass fiber composite wing shells with a unidirectional material, and to vary the layup angle until desirable flutter speed was reached. Three pairs of wings were then manufactured using the new design. Experimental modal analysis of the three wing pairs shows differences in fre- quencies and mode shapes. Each wing was suspended in free-free conditions and excited with a force hammer. The analysis showed first elastic modes in the range 21.0 - 23.2 Hz, second elastic modes in the range of 43.1 - 45.8 Hz, and third elastic modes in the range 89.8 - 93.2 Hz. The experimental results forms the goal for a set of model update procedures. Structural optimization is used to reach a target level of correlation between each wing and its finite element representation. The updated finite element models are used to calculate flutter speeds for each set of wings. The span between the results represents a manufacturing related uncertainty on the flutter speed. Finally, all possible wing pairings are compared to each other in terms of the resulting flutter speed. 17:30 30 mins Modeling of shaker-structure coupling system and its application in ground aeroelastic stability test Wei Xiao, Changkun Yu, Zhigang Wu, Chao Yang Abstract: Ground Aeroelastic Stability Test (GAST) is an experimental method in the field of aerospace engineering that employs shakers to apply real-time condensed unsteady aerodynamic forces to an actual structure, evaluating its aeroelastic stability. GAST includes the ground flutter test and the ground aeroservoelastic test . However, existing work in this area lacks in-depth research on the underlying mechanism, particularly the force controller design problem arising from the coupling of the shaker and structure. This paper aims to address this gap by studying the modeling method of shaker-structure coupling system. The proposed method is specifically suitable for linear elastic structures that adhere to the principle of mode superposition, and where the power amplifier of the shaker works in current mode. To validate the feasibility and accuracy of this modeling method, ground tests of a cantilever beam and a wing were conducted. Applying this modeling method to the simulation of the GAST facilitates further research on force controller design methods, shaker-structure coupling interference, and system delay. In this paper, we integrate the shaker-structure coupling model into the simulation of a wing flutter ground test, conducting a study on the factors influencing the accuracy of flutter results.

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