Uncertainty Quantification in Experimental Structural Dynamics Identification of Composite Material Structures

Author(s):  
Marcin Luczak ◽  
Bart Peeters ◽  
Maciej Kahsin ◽  
Simone Manzato ◽  
Kim Branner
Author(s):  
Kedar Sapkal ◽  
Peter J. Attar

An experimental and computational study of the flutter and limit cycle oscillations (LCOs) of a three layer, carbon fiber composite material 45° delta wing is presented. The computational aeroelastic model utilizes a set of nonlinear structural dynamics (modal) equations which are coupled to a vortex lattice aerodynamic model. The nonlinear modal equations for the structure are formulated using a system identification methodology. To reduce the computational time needed in the computation of the strain energy needed to construct the reduced order structural dynamics model, a new algorithm which uses a Smolyak sparse grid technique is proposed to perform the sampling of strain energy data used for generation of the equations of motion. Experiments and computations are performed, and compared, for a number of layup configuration angles. The qualitative agreement between experimental flutter and limit cycle results is good with both sets of results displaying similar trends with respect to variations in layup angle and a non-dimensional parameter which gives a measure of the bending-torsion coupling in the laminate.


2009 ◽  
Vol 79-82 ◽  
pp. 1519-1522
Author(s):  
Wei Bing Hu ◽  
Qiang Deng

In this paper, using piezoelectric patches bounded or embedded in composite material structures as actuators and sensors, the system for exciting the structure and sensing its dynamic response can be established. Extracting damage information from the response and monitoring the perturbations of structural dynamics can be implemented using wavelet analysis. This will conduce to the capture of the accurate time of damage occurrence. The method developed in this paper can help to build the system of online damage detection and health monitoring of composite material structures when they cannot be directly observed or measured.


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