Dottorato in INGEGNERIA AERONAUTICA E SPAZIALE

Titolo della tesi: Developments in reverse engineering and testing of airborne structures

To verify a modified aircraft structural dynamic stability and fatigue resistance, a dynamic response prediction is required, followed by a Flight Vibration Test if further verification deems necessary. On the aircraft user perspective, in absence of a baseline modal model and lacking room on board a test aircraft for flight test instrumentation dedicated to input control, both modelling and flight testing are demanding tasks, opening to the possibility of some developments in the reverse engineering model updating and modal parameters extraction by flight test data. In this thesis, these two tasks are addressed, and possible solutions are proposed. Regarding the reverse engineering of a FEM structural dynamic model, a new approach for the use of laser scanner technology is proposed to measure small deflections typical of rigid aircraft structures, such as a fighter aircraft wing. The method was applied on a real test case, providing data for a static model updating which, in turn, allowed to create a dynamically representative structural dynamic model of a fighter aircraft wing. For Flight Vibration Test, two enhancing methods for tracking, automated mode detection and parameters extraction are proposed. The first method allows for FDD tracking even in presence of a slowly changing system, which is the case of an aircraft in-flight (burning fuel and changing airspeed), and a small number of measurement points causing spatial aliasing. The method is based on the MACXP correlation parameter, recognised to be the best replacement for the commonly known MAC in view of its effectiveness in dealing with spatial aliasing and modes complexity. The second proposed method consists in automating the modes identification and modal parameters extraction process by means of a clustering algorithm known as Gaussian Mixture Modelling. Given the stabilization diagram obtained by the application of a parametric mode identification method, such as the Stochastic Subspace Identification – Balanced Realisation, the proposed method identifies the best number of modes and determines the related modal parameters. Following numerical validation, both these methods are applied on a real test case of a new store on a fighter aircraft wing, showing consistent results. Overall, the proposed solutions provide aircraft users with some tools to improve their capability to respectively model and test the modal behaviour of an aircraft.