
Predicting the vibration response of panels under a turbulent boundary layer excitation from their measured sensitivity functions
This work investigates the possibility of predicting the actual flow-induced vibration of a panel from a measurement of its sensitivity functions and a priori knowledge of the auto spectral and cross spectral density functions defining the excitation. The method takes advantage of an
explicit separation in the wave number domain of the structure behavior (defined by the sensitivity functions) and of the random excitation characteristics (defined by the spectral density functions). The validity of the approach was previously confirmed for the case of an isotropic aluminum
panel with controlled simply-supported boundary conditions, and excited by a diffuse acoustic field and a turbulent boundary layer. To verify the robustness of the methodology, it is here applied on two plane panels with different aspect ratios, both made of a composite material representative
of those used in interior trim panels. A blind approach is followed, in the sense that the mechanical properties of the panels are voluntarily kept unknown, their boundary conditions are not especially controlled and the test sequence is executed step by step without any intermediate verification.
Tests are conducted in a wind tunnel facility, with two flow speeds considered. A direct vibration measurement under turbulent flow excitation is first conducted using an accelerometer fixed at a given point on each panel. The vibratory response of the panel when excited by the flow is then
deduced at the same point, now using the measured wall-pressure fluctuations statistics that are combined with the sensitivity functions. The predicted vibration velocity autospectra using the proposed method are in very good agreement with those directly measured whatever the considered panel
or flow velocity.
Keywords: Flow induced vibration; Sensitivity functions; Turbulent boundary layer; Vibroacoustics of plane panels
Document Type: Research Article
Publication date: 01 December 2018
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