Presentation + Paper
18 April 2022 Understanding the elastic, plastic, and damage features in fracturing of self-reinforced thermoplastic composites via non-destructive digital imaging correlation
Author Affiliations +
Abstract
This work demonstrated the utilization of non-destructive Digital Imaging Correlation (DIC) method to characterize the elastic, plastic, and damage features during the Mode I intra-laminar fracturing process of self-reinforced thermoplastic composites by using a self-reinforced polypropylene (PP) composite as an example. The DIC results clearly showed the development of huge plastic zone (PZ) and non-negligible Fracture Process Zone (FPZ) in front of the notch tip during the fracturing process, and the geometries and sizes of the foregoing zones at the peak load were further quantified. Such an interesting fracturing behavior of self-reinforced thermoplastic composites is way different from brittle materials (e.g., glass, acrylic, etc.), ductile materials (e.g., aluminum, steel, etc.), and even quasi-brittle materials (e.g., concrete, nanoparticle-reinforced composites, tough ceramics, wood, carbon/glass fiber-reinforced polymers, etc.). Thus, understanding the elastic, plastic, and damage features is the first step before better characterizing the material fracture properties of self-reinforced thermoplastic composites through new analytical methods and computational modeling. These efforts are utmost of importance for wide applications of self-reinforced thermoplastic composites in various engineering fields in the future.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yao Qiao, Madhusudhan Reddy Pallaka, Ethan Nickerson, Lisa Fring, and Kevin Simmons "Understanding the elastic, plastic, and damage features in fracturing of self-reinforced thermoplastic composites via non-destructive digital imaging correlation", Proc. SPIE 12047, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVI, 1204707 (18 April 2022); https://doi.org/10.1117/12.2615378
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KEYWORDS
Composites

Polymers

Nondestructive evaluation

Digital image correlation

Digital imaging

Aluminum

Computational modeling

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