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					         Damage Prognosis of Adhesively-Bonded Joints in Composite
            Structural Components of Unmanned Aerial Vehicles
 Maurizio Gobbato1, Joseph A. Oliver1, Joel P. Conte1, John B. Kosmatka1, Charles R. Farrar2
                                1
                                 Department of Structural Engineering
                                 University of California, San Diego
                              9500 Gilman Dr., La Jolla, CA 92093-0085
     mgobbato@ucsd.edu; jpconte@ucsd.edu; jkosmatka@ucsd.edu; jaoliver@ucsd.edu
                                 2
                                     The Engineering Institute, MS T-001
                                      Los Alamos National Laboratory
                                          Los Alamos, NM 87545
                                              farrar@lanl.gov


                                               ABSTRACT

The extensive use of lightweight advanced composite materials in unmanned aerial vehicles (UAVs)
drastically increases the sensitivity to both fatigue- and impact-induced damage of their most critical
structural components (such as the wings and the tail stabilizers) during service life. This may result
in localized debonding, inter-ply delamination, fiber breakage and matrix cracking thereby
compromising the structural performance and the level of safety of the entire vehicle. The skin-to-spar
adhesive joints are considered one of the most fatigue sensitive subcomponents of a lightweight UAV
composite wing with the damage progressively evolving from the wing root. A field deployable
integrated hardware-software system capable of monitoring the composite UAV airframe [1],
assessing its structural integrity, identifying a condition-based maintenance, and predicting the
remaining service life of its critical components (damage prognosis [2]) is therefore needed.
The poster illustrates a comprehensive probabilistic methodology for predicting the remaining service
life of adhesively-bonded joints in laminated composite structural components of UAVs. Non
Destructive Evaluation (NDE) techniques and Bayesian inference are used to (i) assess the current
damage state of the system and (ii) update the probability distribution of damage extensions at
multiple damaged locations. A probabilistic model for future loads and a mechanics-based damage
model for the adhesive interface are then used to stochastically propagate the damage throughout the
joint. Combined local (e.g., exceedance of a critical damage size) and global (e.g., flutter instability)
failure criteria are finally used to compute the probability of component failure at future times. The
applicability of the proposed methodology is then demonstrated by analyzing the debonding
propagation along a pre-defined adhesive interface in a simply supported laminated composite beam
with a solid rectangular cross section subjected to a random load. A specially developed shear
deformable beam finite element with interlaminar slip along the damageable adhesive interface is
used in combination with a cohesive zone model (CZM) to study the fatigue-induced degradation in
the adhesive material.

References
[1] F. Lanza di Scalea, H.M. Matt, I. Bartoli, S. Coccia, G. Park, C.R. Farrar, Health monitoring of
    UAV skin-to-spar joints using guided waves and macro fiber composite transducers. Journal of
    Intelligent Material Systems and Structures, 18(4), 373-388, 2007.
[2] D.J Inman, C.R. Farrar, V. Lopez Jr., V. Steffen Jr., Damage prognosis for aerospace, civil and
    mechanical systems, Wiley, 2005.

				
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posted:10/12/2012
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