Preliminary characterization of bonding defects in multi-element spars

• Main Authors: Concilio, Antonio, Ciminello, Monica, Apuleo, Gianvito, Kressel, Iddo, Shoham, Shay, Bardenstein, David
• Format: Conference Proceeding
• Language: English
• Published: SPIE 01.04.2019
• ISBN: 1510625992; 9781510625990
• ISSN: 0277-786X
• DOI: 10.1117/12.2514297

Composite structures need structural monitoring systems to improve maintenance and design processes. Maintenance may be supported by prompt detection of damage insurgence, moving towards condition-based rather than scheduled approaches. Design can attain adequate safety levels with lighter structures, in force of a continuous knowledge of their status. Required practices and systems are dependent on damage type, each with its own particularity; therefore, complex systems are necessary to respond to such a necessity. Among the many, bonding defects are particularly important. They can be classified as bonding deficiency, as adhesive misses in some parts, or de-bonding, as attachment collapses. Moving from activities performed within OPTICOMS, a project funded within the European flagship Clean Sky 2 JTI, the present work focuses on the preliminary characterization of bonding imperfections effect on selected composite aircraft components. In detail, how local adhesive absence influences static structural response and how this flaw type can be detected through a proprietary algorithm is investigated. A multi-element beam is referred, representing a main spar of the primary structure. A large numerical campaign is conducted on a tuned FE model, implementing different defect layouts, for size and location. Numerical structural response is computed through a representation of a distributed strain sensing system. Supported by a basic theoretical discussion, results are processed and commented, to individuate specific parameters that can describe applied failures. Finally, an in-house code verifies preliminarily its capabilities in exposing presence and size of the applied imperfections, correlating numerical outcomes with performed estimations.