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2026 (English)In: Composites Part B: Engineering, ISSN 1359-8368, E-ISSN 1879-1069, Vol. 311, article id 113240Article in journal (Refereed) Published
Abstract [en]
Delamination severely degrades the residual strength of glass-fibre-reinforced plastic (GFRP) laminates impacted by ballistic projectiles. This study introduces TopoPrior-UNet, a U-Net variant named for its novel loss function that embeds Topological Prior knowledge (specifically, a persistent-homology shape-prior loss to enforce the global topological structure of the damage, and a level-set active-contour loss to refine fuzzy boundaries) to segment multi-layer delamination images from a digital single lens reflex camera (DSLR). An initial set of 24 raw panel images was expanded to a 480-image set through three augmentation schemes, enabling learning under extreme data scarcity. Compared with a vanilla U-Net, TopoPrior-UNet improved mean Intersection-over-Union to 0.9832 (+9.9pp) and mean Dice to 0.9915 (+5.3pp), achieving the best scores across six metrics. These gains stem from jointly refining fuzzy boundaries and enforcing global ply topology, as corroborated by an ablation study. The trained model operates in quasi-real-time (i.e., inference in seconds per image) and requires only surface imagery, offering a cost-effective and rapid alternative to traditional NDT methods like X-ray or ultrasonic inspection, which often require minutes to hours for acquisition. Such rapid, non-destructive quantification of delamination extent lays the foundation for on-site residual-strength estimation and timely structural maintenance.
Place, publisher, year, edition, pages
Elsevier BV, 2026
Keywords
GFRP delamination, TopoPrior-UNet, Semantic segmentation, Persistent homology, Level-set active contour, Non-destructive testing
National Category
Materials Engineering
Identifiers
urn:nbn:se:kth:diva-376678 (URN)10.1016/j.compositesb.2025.113240 (DOI)001633123400002 ()2-s2.0-105023159656 (Scopus ID)
Note
QC 20260223
2026-02-232026-02-232026-02-23Bibliographically approved