X-ray Micro-Computed Tomography and Deep Learning Segmentation of Progressive Damage in Hierarchical Nanoengineered Carbon Fiber Composites

Advanced composite laminates comprised of carbon (micro) fiber reinforced polymer (CFRP) have become widespread in modern high-performance aerospace structures, providing high, tailorable mass-specific stiffness and strength. However, while underpinning such performance benefits, CFRP microstructural heterogeneity and mechanical property anisotropy concomitantly give rise to complex damage mechanisms that lead to difficult-to-predict failure, limiting CFRP understanding. Progressive damage mechanisms in CFRPs generally encompasses a spectrum of modalities, interactions, and sequences across multiple scales, exhibiting broad sensitivity to loading conditions. Dominant damage mechanisms have been identified generally as polymer matrix cracking within (intralaminar) and between (interlaminar, termed ‘delamination’) plies, fiber fracture, fiber bundle microbuckling, and fiber/matrix interfacial debonding. Two emerging solutions aiming to suppress or delay such mechanisms toward enhanced strength and stiffness are considered in this dissertation: (i) aligned carbon nanotube (A-CNT) interlaminar reinforcement (termed ‘nanostitch’) that primarily targets delaminations, and (ii) thin-ply morphology that targets intralaminar cracking and delaminations. Both solutions have demonstrated significant mechanical improvements via standard ex situ tests that lack underlying progressive damage understanding. In view of these limitations, this dissertation advances understanding of composite progressive damage by modern ex situ and state-of-the-art in situ X-ray micro-computed tomography (µCT) studies, including advancing experimental techniques via artificial intelligence (AI), in the context of aerospace-grade CFRP strengthening and toughening effects of nanostitch, thin-ply, and their combination.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Aeronautics and Astronautics

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Kopp, Reed Alan

Advisor dc:contributor.advisor

• Wardle, Brian L.

• Aeronautics and Astronautics.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/138357

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/138357