Field Strain Measurement on the Fiber-Epoxy Scale in CFRPs

Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)


Laminated composites are materials with complex architecture made of continuous fibers (usually glass or carbon) embedded within a polymeric resin. The properties of the raw materials can vary from one point to another due to different local processing conditions or complex geometrical features for example. A first step towards the identification of these spatially varying material parameters is to image with precision the displacement fields in this complex microstructure when subjected to mechanical loading. Secondary electron images obtained by scanning electron microscopy (SEM) and then numerically deformed are post-processed by either local subset-based digital image correlation (DIC) or global finite-element based DIC to measure the displacement and strain fields at the fiber-matrix scale in a cross-ply composite. It is shown that when global DIC is applied with a conformal mesh, it can capture more accurate local variations in the strain fields as it takes into account the underlying microstructure. In comparison to subset DIC, global DIC is better suited for capturing gradients across the fiber-matrix interfaces.


Numerical simulation Image correlation Electron microscopy Distortion Conformal mesh 


  1. 1.
    J. Llorca, C. González, J.M. Molina-Aldareguía, J. Segurado, R. Seltzer, F. Sket, M. Rodríguez, S. Sádaba, R. Muñoz, L.P. Canal, Multiscale modeling of composite materials: a roadmap towards virtual testing. Adv. Mater. 23, 5130–5147 (2011)CrossRefGoogle Scholar
  2. 2.
    G. Lubineau, A. Moussawi, J. Xu, R. Gras, A domain decomposition approach for digital image correlation based identification of local elastic parameters. Int. J. Solids Struct. 55, 44–57 (2015)CrossRefGoogle Scholar
  3. 3.
    E. Florentin, G. Lubineau, Identification of the parameters of an elastic material model using the constitutive equation gap method. Comput. Mech. 46(4), 521–531 (2010)zbMATHMathSciNetCrossRefGoogle Scholar
  4. 4.
    M. Grediac, The use of full-field measurement methods in composite material characterization: interest and limitations. Compos. A Appl. Sci. Manuf. 35, 751–761 (2004)CrossRefGoogle Scholar
  5. 5.
    B. Pan, K. Li, W. Tong, Fast, robust and accurate digital image correlation calculation without redundant computations. Exp. Mech. 53, 1277–1289 (2013)CrossRefGoogle Scholar
  6. 6.
    Y. Sun, J.H.L. Pang, C.K. Wong, F. Su, Finite element formulation for a digital image correlation method. Appl. Opt. 44, 7357–7363 (2005)CrossRefGoogle Scholar
  7. 7.
    L. Canal, C. González, J. Molina-Aldareguía, J. Segurado, J. LLorca, Application of digital image correlation at the microscale in fiber-reinforced composites. Compos. A: Appl. Sci. Manuf. 43, 1630–1638 (2012)CrossRefGoogle Scholar
  8. 8.
    B. Pan, B. Wang, G. Lubineau, A. Moussawi, Comparison of subset-based local and finite element-based global digital image correlation, Exp. Mech.55(5), 887–901 (2015) Google Scholar
  9. 9.
    M.A. Sutton, N. Li, D. Garcia, N. Cornille, J.J. Orteu, S.R. McNeill, H.W. Schreier, X. Li, Metrology in a scanning electron microscope: theoretical developments and experimental validation. Meas. Sci. Technol. 17, 2613–2622 (2006)CrossRefGoogle Scholar
  10. 10.
    H.W. Schreier, Calibrated sensor and method for calibrating same. Patent Pending 1 (2006)Google Scholar
  11. 11.
    A.D. Kammers, S. Daly, Digital image correlation under scanning electron microscopy: methodology and validation. Exp. Mech. 53, 1743–1761 (2013)CrossRefGoogle Scholar

Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  1. 1.Physical Science and Engineering Division, Cohmas LaboratoryKing Abdullah University of Science and Technology (KAUST)ThuwalSaudi Arabia
  2. 2.Institute of Solid MechanicsBeijing University of Aeronautics & AstronauticsBeijingChina

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