Experimental Mechanics

, Volume 47, Issue 6, pp 761–773 | Cite as

Use of 3-D Digital Image Correlation to Characterize the Mechanical Behavior of a Fiber Reinforced Refractory Castable

  • L. Robert
  • F. Nazaret
  • T. Cutard
  • J.-J. Orteu


Refractory castables exhibit very low fracture strain levels when subjected to tension or bending. The main objective of this work is to show that 3-D digital image correlation (3-D DIC) allows such low strain levels to be measured. Compared to mechanical extensometer measurements, 3-D DIC makes it possible to reach similar strain resolution levels and to avoid the problem of position dependance related to the heterogeneous nature of the strain and to strain localization phenomena. First, the 3-D DIC method and the experimental set-up are presented. Secondly, an analysis of the 3-D DIC method is performed in order to evaluate the resolution, the standard uncertainty and the spatial resolution for both displacement and strain measurements. An optimized compromise between strain spatial resolution and standard uncertainty is reached for the configuration of the experimental bending test. Finally, the macroscopic mechanical behavior of a fiber reinforced refractory castable (FRRC) is studied using mechanical extensometry and 3-D DIC in the case of tensile and four-point bending tests. It is shown that similar results are obtained with both methods. Furthermore, in the case of bending tests on damaged castable, 3-D DIC results demonstrate the ability to determine Young’s modulus from heterogeneous strain fields better than by using classical beam deflection measurements.


3-D digital image correlation Refractory castable Fiber Full-field techniques Uncertainty assessment Resolution Spatial resolution 


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  1. 1.
    Cloud G (1998) Optical methods of engineering analysis. Cambridge University Press, iSBN 0-521-45087-X.Google Scholar
  2. 2.
    Rastogi P (ed.) (1999) Photomechanics. Springer Verlag, iSBN 3-540-65990-0.Google Scholar
  3. 3.
    Surrel Y (2004) Full-field optical methods for mechanical engineering: essential concepts to find one’s way. Invited Keynote at the 2nd International Conference on Composites Testing and Model Identification, Bristol, UK.Google Scholar
  4. 4.
    Grédiac M (2004) The use of full-field measurement methods in composite material characterization: interest and limitations. Composites Part A 35:751–761.CrossRefGoogle Scholar
  5. 5.
    Wang Y, Cuitiño A (2002) Full-field measurements of heterogeneous deformation patterns on polymeric foams using digital image correlation. Int J Solids Struct 39:3777–3796.CrossRefGoogle Scholar
  6. 6.
    Abanto-Bueno J, Lambros J (2002) Investigation of crack growth in functionally graded materials using digital image correlation. Eng Fract Mech 69:1695–1711.CrossRefGoogle Scholar
  7. 7.
    Chevalier L, Calloch S, Hild F, Marco Y (2001) Digital image correlation used to analyze the multiaxial behavior of rubber-like materials. Eur J Mech A - Solids 20:169–187.zbMATHCrossRefGoogle Scholar
  8. 8.
    Parsons E, Boyce M, Parks D (2004) An experimental investigation of the large-strain tensile behavior of neat and rubber-toughened polycarbonate. Polymer 45:2665–2684.CrossRefGoogle Scholar
  9. 9.
    Helm J, McNeill S, Sutton M (1996) Improved three-dimensional image correlation for surface displacement measurement. Opt Eng 35(7):1911–1920.CrossRefGoogle Scholar
  10. 10.
    Sutton M, McNeill S, Helm J, Chao Y (2000) Advances in two-dimensional and three-dimensional computer vision. Rastogi P (ed) Photomechanics. Topics in Applied Physics, Springer Verlag, Berlin.Google Scholar
  11. 11.
    Garcia D, Orteu J-J, Penazzi L (2002) A combined temporal tracking and stereo-correlation technique for accurate measurement of 3D displacements: application to sheet metal forming. J Mater Process Technol 125–126:736–742.CrossRefGoogle Scholar
  12. 12.
    Choi S, Shah S (1997) Measurement of deformations on concrete subjected to compression using image correlation. Exp Mech 37(3):307–313.CrossRefGoogle Scholar
  13. 13.
    Lawler J, Keane D, Shah S (2001) Measuring three-dimensional damage in concrete under compression. ACI Mater J 98:465–475.Google Scholar
  14. 14.
    Zhang J, Xiong C, Li H, Li M, Wang J, Fang J (2004) Damage and fracture evaluation of granular composite materials by digital image correlation method. Acta Mech Sin 20(4): 408–417.CrossRefGoogle Scholar
  15. 15.
    Lecompte D, Vantomme J, Sol H (2006) Crack detection in a concrete beam using two different camera techniques. Structural Health Monitoring 5(1):50–68.CrossRefGoogle Scholar
  16. 16.
    Puyo-Pain M, Lamon J (2005) Determination of elastic moduli and Poisson coefficient of thin silicon-based joint using digital image correlation. Proceedings of the 29th International Conference on Advanced Ceramics and Composites, Cocoa Beach, Florida, USA.Google Scholar
  17. 17.
    Orteu J-J, Cutard T, Garcia D, Cailleux E, Robert L (2007) Application of stereovision to the mechanical characterisation of ceramic refractories reinforced with metallic fibres. Strain 43(2):1–13.CrossRefGoogle Scholar
  18. 18.
    Schmitt N, Berthaud Y, Poirier J (2000) Tensile behaviour of magnesia carbon refractories. J Eur Ceram Soc 20: 2239–2248.CrossRefGoogle Scholar
  19. 19.
    Marzagui H, Cutard T, Yeugo Fogain E, Huger M, Gault C, Prompt N, Deteuf C (2004) Microstructural changes and high temperature mechanical behavior of an andalusite based low cement refractory castable. Proceedings of the International Conference of Metallurgists (com2004), Hamilton, Canada, pp 331–345.Google Scholar
  20. 20.
    Nazaret F, Marzagui H, Cutard T (2006) Influence of the mechanical behaviour specificities of damaged refractory castables on the Young’s modulus determination. J Eur Ceram Soc 76(8):1429–1438.CrossRefGoogle Scholar
  21. 21.
    Nazaret F, Cutard T, Bernhart G (2004) Thermomechanical behaviour of a fibre-reinforced refractory concrete: tests and FE analysis. Proceedings of the 6th RILEM Symposium on Fibre Reinforced Concrete (BEFIB 2004), Varenna, Lake Como, Italy, pp 689–698.Google Scholar
  22. 22.
    Sutton M, Wolters W, Peters W, McNiell S (1983) Determination of displacements using an improved digital correlation method. Image Vis Comput 1:133–139.CrossRefGoogle Scholar
  23. 23.
    Kahn-Jetter Z, Chu T (1990) Three-dimensional displacement measurements using digital image correlation and photogrammic analysis. Exp Mech 30(1):10–16.CrossRefGoogle Scholar
  24. 24.
    Luo P, Chao Y, Sutton M, Peters W (1993) Accurate measurement of three-dimensional deformations in deformable and rigid bodies using computer vision. Exp Mech 30(2): 123–132.CrossRefGoogle Scholar
  25. 25.
    Alpers B, Bergmann D, Galanulis K, Winter D (1999) Advanced deformation measurement in sheet metal forming. Proceedings of the 6th International Conference on Technology of Plasticity, Nuremberg, Germany.Google Scholar
  26. 26.
    Synnergren P, Sjödahl M (1999) A stereoscopic digital speckle photography system for 3-D displacement field measurements. Opt Lasers Eng 31:425–443.CrossRefGoogle Scholar
  27. 27.
    Schreier H, Sutton M (2002) Systematic errors in digital image correlation due to undermatched subset shape functions. Exp Mech 43(3):303–311.CrossRefGoogle Scholar
  28. 28.
    Schreier H, Braasch J, Sutton M (2000) Systematic errors in digital image correlation caused by intensity interpolation. Opt Eng 39(11):2915–2921.CrossRefGoogle Scholar
  29. 29.
    Garcia D (2001) Mesure de formes et de champs de déplacements tridimensionnels par stéréo-corrélation d’images. Ph.D. thesis, Institut National Polytechnique de Toulouse (France).Google Scholar
  30. 30.
    Vic-2D® and Vic-3D® softwares (2006) Correlated Solutions Incorporated,
  31. 31.
    ISO (1995) Guide to the Expression of Uncertainty in Measurements (GUM). International Organization for Standardization, Geneva (Switzerland).Google Scholar
  32. 32.
    Rubin D (2004) A simple autocorrelation algorithm for determining grain size from digital images of sediment. J Sediment Res 74(1):160–165.Google Scholar
  33. 33.
    Orteu J-J, Garcia D, Robert L, Bugarin F (2006) A speckle-texture image generator. Proceedings of the Speckle’06 International Conference, Nîmes, France.Google Scholar
  34. 34.
    Wattrisse B, Chrysochoos A, Muracciole J-M, Némoz-Gaillard M (2000) Analysis of strain localization during tensile tests by digital image correlation. Exp Mech 41(1): 29–39.CrossRefGoogle Scholar
  35. 35.
    Jin H, Bruck H (2005) Theoretical development for pointwise digital image correlation. Opt Eng 44(6):1–14.CrossRefGoogle Scholar
  36. 36.
    Davidovits J (1994) Geopolymers: man-made rock geosynthesis and resulting development of very early high strength cement. J Mater Educ 16:91–139.Google Scholar
  37. 37.
    Cutard T, Cailleux E, Lours P, Bernhart G (1999) Structural and mechanical properties of a refractory concrete for superplastic forming tools. Ind Ceram 19:100–102.Google Scholar
  38. 38.
    Cailleux E, Cutard T, and Bernhart G (2005) Pullout of steel fibres from a refractory castable: experiment and modelling. Mechanics of Materials, 37:427–445.CrossRefGoogle Scholar
  39. 39.
    Quinn G (1990) Flexure strength of advanced structural ceramics: a round robin. J Am Ceram Soc 73:2374–2384.CrossRefGoogle Scholar
  40. 40.
    Quinn G, Morrell R (1991) Design data for engineering ceramics: a review of the flexure test. J Am Ceram Soc 74: 2037–2066.CrossRefGoogle Scholar
  41. 41.
    Nazaret F (2005) Caractérisation et modélisation du comportement thermomécanique d’un béton réfractaire renforcé de fibres métalliques. Ph.D. thesis, École des Mines de Paris (France).Google Scholar

Copyright information

© Society for Experimental Mechanics 2007

Authors and Affiliations

  1. 1.Research Center on Tools, Materials and Forming Processes (CROMeP)École des Mines d’Albi, Campus JarlardALBI CT Cedex 9France

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