Low Poisson’s Ratio Measurement on Composites Based on DIC and Frequency Analysis on Tensile Tests
Accurate determination of elastic properties, especially Poisson’s ratio, is crucial for the design and modeling of composite materials. Traditional methods often struggle with low strain measurements and non-uniform strain distributions inherent in these anisotropic materials. This research work introduces a novel methodology that integrates Digital Image Correlation (DIC) with frequency analysis techniques to improve the precision of Poisson’s ratio determination during tensile tests, particularly at low strain ranges. The focus is on the evaluation of two distinct frequency-based approaches: Phase-Based Motion Magnification (PBMM) and Lock-in filtering. DIC + PBMM, while promising for motion amplification, encountered specific challenges in this application, particularly at very low strain amplitudes, leading to increased variability and computational demands. In contrast, the DIC + Lock-in filtering method proved highly effective. It provided stable, filtered strain distributions, significantly reducing measurement uncertainty compared to traditional DIC and other conventional methods like strain gauges and Video Extensometers. This study demonstrates the robust potential of Lock-in filtering for characterizing subtle periodic mechanical behaviors leading to a reduction of approximately 70% in the standard deviation of the measurement. This work lays a strong foundation for more precise and reliable material characterization, crucial for advancing composite design and engineering applications.
Authors
- Sebastian Schmeer (ORCID: https://orcid.org/0000-0002-3823-2179)
- Elías López‐Alba
- Andreas Kenf (ORCID: https://orcid.org/0000-0003-4749-1129)
- F.A. Díaz (ORCID: https://orcid.org/0000-0003-0467-542X)
- Luis Felipe-Sesé (ORCID: https://orcid.org/0000-0002-7119-512X)
Institutions
- Universidad de Jaén (ES)
- Leibniz-Institut für Verbundwerkstoffe GmbH (DE)
Publication Details
- Journal
- Journal of Composites Science
- Published
- 2025-10-16
- DOI
- https://doi.org/10.3390/jcs9100570
- Citations
- 2
- Primary Topic
- Structural Health Monitoring Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.91
Funders
- Ministerio de Ciencia, Innovación y Universidades
- Agencia Estatal de Investigación