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Updated: Dec 24, 2025

Intermediate Strain Rate Material Characterization with Digital Image Correlation
Published on: March 1, 2019
Real-time quantification of damage in structural materials during mechanical testing
W J R Christian1, K Dvurecenska1, K Amjad1
1School of Engineering, University of Liverpool, Liverpool, UK.
A new method quantifies composite damage severity using digital image correlation. This technique tracks strain field changes, offering faster, more insightful analysis than traditional load-extension data for material testing.
Area of Science:
- Materials Science
- Mechanical Engineering
- Non-Destructive Testing
Background:
- Composite materials are crucial in various industries.
- Accurate damage assessment during mechanical testing is vital for safety and performance.
- Existing methods for damage quantification can be time-consuming and less informative.
Purpose of the Study:
- To introduce a novel methodology for quantifying damage severity in composite components during mechanical testing.
- To demonstrate the effectiveness of digital image correlation (DIC) and image processing for monitoring strain field evolution.
- To present a new approach for visualizing and interpreting damage distribution and timing.
Main Methods:
- Utilized digital image correlation (DIC) combined with image processing techniques.
- Monitored the rate of strain field changes during mechanical tests.
- Applied the methodology to ceramic matrix composites (CMCs) under tension at high temperatures and polymer matrix composites (PMCs) with fibre-waviness defects under bending.
Main Results:
- Changes in the strain field proved more effective in identifying the proportional limit than load-extension diagrams.
- Developed spatio-temporal damage maps for clear visualization of damage location, morphology, and occurrence.
- Demonstrated the method's applicability across different composite types and loading conditions.
Conclusions:
- The proposed methodology offers a more sensitive and efficient way to quantify composite damage severity.
- Spatio-temporal damage maps significantly enhance the interpretation of complex material test data.
- This approach has the potential to reduce data analysis time and increase knowledge extraction from material tests.
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