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Title: Damage prognosis of adhesively-bonded joints in laminated composite structural components of unmanned aerial vehicles

Conference ·
OSTI ID:988322

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 critical structural components (e.g., wings and tail stabilizers) during service life. The spar-to-skin adhesive joints are considered one of the most fatigue sensitive subcomponents of a lightweight UAV composite wing with damage progressively evolving from the wing root. This paper presents a comprehensive probabilistic methodology for predicting the remaining service life of adhesively-bonded joints in laminated composite structural components of UAVs. Non-destructive evaluation techniques and Bayesian inference are used to (i) assess the current state of damage of the system and, (ii) update the probability distribution of the damage extent at various locations. A probabilistic model for future loads and a mechanics-based damage model are then used to stochastically propagate damage through 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 and the partial validation of the proposed methodology are then briefly discussed by analyzing the debonding propagation, along a pre-defined adhesive interface, in a simply supported laminated composite beam with solid rectangular cross section, subjected to a concentrated load applied at mid-span. A specially developed Eliler-Bernoulli beam finite element with interlaminar slip along the damageable interface is used in combination with a cohesive zone model to study the fatigue-induced degradation in the adhesive material. The preliminary numerical results presented are promising for the future validation of the methodology.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC52-06NA25396
OSTI ID:
988322
Report Number(s):
LA-UR-09-02234; LA-UR-09-2234; TRN: US201018%%487
Resource Relation:
Conference: ECCOMAS Thematic Conference on Computational Methods in Structural ; June 22, 2009 ; Rhodes, Greece
Country of Publication:
United States
Language:
English