Reliability-Based Framework for Damage Prognosis of Adhesively-Bonded Joints in Composite UAV Wings

The extensive use of lightweight composite materials in unmanned aerial vehicles (UAVs) drastically increases the sensitivity to both fatigue- and impact-induced damage of their critical structural components. The skin-to-spar adhesive joints are considered one of the most fatigue sensitive subcomponents of a lightweight composite UAV wing with the damage progressively evolving from the wing root. Therefore, a system capable of monitoring these joints, assessing the structural integrity of the wing, identifying a condition-based maintenance, and predicting the remaining life (damage prognosis) is ultimately needed. In contribution to this goal, the paper presents the theoretical development of a novel probabilistic methodology for predicting the remaining service life of adhesively-bonded joints in composite UAV wings. Non-destructive evaluation techniques and Bayesian inference are used to (i) assess the current state of damage and, (ii) update the probability distribution of the damage extent at various locations. A probabilistic model for future aerodynamic loads—turbulence and maneuver induced—and a mechanics-based damage model for the adhesive interfaces are then used to propagate damage through the joints. Combined local (e.g., exceedance of a critical damage size) and global (e.g., exceedance of the flutter instability boundary) failure criteria are finally employed to compute the probability of failure at future times by abstracting the UAV wing as a series system. ∆