Advertisement

Ultraviolet Digital Image Correlation for Molten Thermoplastic Composites under Finite Strain

  • Y. Denis
  • E. Guzman-Maldonado
  • F. Morestin
  • N. HamilaEmail author
Article
  • 60 Downloads

Abstract

The thermostamping process used to fabricate thermoplastic prepreg composites is widely studied due to its use in several applications in the automotive and aerospace industries. In recent years, different constitutive mechanical models and new numerical techniques have been proposed to simulate this process. However, from an experimental point of view, no substantial progress has been recorded on the experimental methods used for the characterisation of thermostamped thermoplastic prepreg composites. Moreover, there is currently no experimental protocol to visualize or analyse deformation fields at temperatures above the melting point of a material during the characterisation process. The knowledge of these fields allows precision modelling of the mechanical behaviour of this type of material. Therefore, the aim of this paper is to propose a new experimental protocol that uses a digital image correlation method, which faces constraints such as light reflections on either the yarns or the molten thermoplastic matrix. The proposed solution uses an ultraviolet light source and a photoluminescent powder to make the speckle pattern. This approach avoids any visible reflections, since the sample itself is the visible light source.

Keywords

Ultraviolet DIC Bias extension test Shear field measurement Thermoplastic composite materials 

Notes

Acknowledgements

The authors of this paper wish to thank the technical team of the LaMCoS laboratory and, in particular, Mr. Philippe Chaudet, Mr. Jean-Pascal Guilhermond and Mr. Paul Valverde for their help and availability.

References

  1. 1.
    Advani SG, Hsiao K-T (2012) 1 - introduction to composites and manufacturing processes. In: Manufacturing techniques for polymer matrix composites (PMCs). Woodhead Publishing, pp 1–12Google Scholar
  2. 2.
    Sherwood JA, Fetfatsidis KA, Gorczyca JL, Berger L (2012) 6 - fabric thermostamping in polymer matrix composites. In: Manufacturing techniques for polymer matrix composites (PMCs). Woodhead Publishing, pp 139–181Google Scholar
  3. 3.
    Hubert P, Fernlund G, Poursartip A (2012) 13 - autoclave processing for composites. In: Manufacturing techniques for polymer matrix composites (PMCs). Woodhead Publishing, pp 414–434Google Scholar
  4. 4.
    Schlimbach J, Ogale A (2012) 14 - out-of-autoclave curing process in polymer matrix composites. In: Manufacturing techniques for polymer matrix composites (PMCs). Woodhead Publishing, pp 435–480Google Scholar
  5. 5.
    Allaoui S, Hivet G, Wendling A et al (2010) Experimental approach for optimizing dry fabric formability. In: 14th European conference on composite materials. Budapest, Hungary, pp ID347–ECCM14Google Scholar
  6. 6.
    Guzman-Maldonado E, Hamila N, Boisse P, Bikard J (2015) Thermomechanical analysis, modelling and simulation of the forming of pre-impregnated thermoplastics composites. Compos A: Appl Sci Manuf 78:211–222.  https://doi.org/10.1016/j.compositesa.2015.08.017 CrossRefGoogle Scholar
  7. 7.
    Harrison P, Yu W-R, Long AC (2011) Rate dependent modelling of the forming behaviour of viscous textile composites. Compos A: Appl Sci Manuf 42(11):1719–1726Google Scholar
  8. 8.
    Chen Q, Boisse P, Park CH et al (2011) Intra/inter-ply shear behaviors of continuous fiber reinforced thermoplastic composites in thermoforming processes. Compos Struct 93(7):1692–1703.  https://doi.org/10.1016/j.compstruct.2011.01.002 CrossRefGoogle Scholar
  9. 9.
    Gabrion X, Placet V, Trivaudey F, Boubakar L (2016) About the thermomechanical behaviour of a carbon fibre reinforced high-temperature thermoplastic composite. Compos Part B 95:386–394.  https://doi.org/10.1016/j.compositesb.2016.03.068 CrossRefGoogle Scholar
  10. 10.
    Guzman-Maldonado E, Hamila N, Naouar N et al (2016) Simulation of thermoplastic prepreg thermoforming based on a visco-hyperelastic model and a thermal homogenization. Mater Des 93:431–442.  https://doi.org/10.1016/j.matdes.2015.12.166 CrossRefGoogle Scholar
  11. 11.
    Vieille B, Aucher J, Taleb L (2009) Influence of temperature on the behavior of carbon fiber fabrics reinforced PPS laminates. Mater Sci Eng A 517(1-2):51–60.  https://doi.org/10.1016/j.msea.2009.03.038 CrossRefGoogle Scholar
  12. 12.
    Abot J, Yasmin A, Jacobsen A, Daniel I (2004) In-plane mechanical, thermal and viscoelastic properties of a satin fabric carbon/epoxy composite. Compos Sci Technol 64(2):263–268.  https://doi.org/10.1016/S0266-3538(03)00279-3 CrossRefGoogle Scholar
  13. 13.
    Caminero MA, Lopez-Pedrosa M, Pinna C, Soutis C (2013) Damage monitoring and analysis of composite laminates with an open hole and adhesively bonded repairs using digital image correlation. Compos Part B 53:76–91.  https://doi.org/10.1016/j.compositesb.2013.04.050 CrossRefGoogle Scholar
  14. 14.
    Koerber H, Xavier J, Camanho PP (2010) High strain rate characterisation of unidirectional carbon-epoxy IM7-8552 in transverse compression and in-plane shear using digital image correlation. Mech Mater 42(11):1004–1019.  https://doi.org/10.1016/j.mechmat.2010.09.003 CrossRefGoogle Scholar
  15. 15.
    Gras R, Leclerc H, Roux S et al (2013) Identification of the out-of-plane shear Modulus of a 3D woven composite. Exp Mech 53(5):719–730.  https://doi.org/10.1007/s11340-012-9683-4 CrossRefGoogle Scholar
  16. 16.
    Canal LP, González C, Molina-Aldareguía JM et al (2012) Application of digital image correlation at the microscale in fiber-reinforced composites. Compos A: Appl Sci Manuf 43(10):1630–1638.  https://doi.org/10.1016/j.compositesa.2011.07.014 CrossRefGoogle Scholar
  17. 17.
    Dridi S, Morestin F, Dogui A (2012) Use of digital image correlation to analyse the shearing deformation in woven fabric. Exp Tech 36(5):46–52.  https://doi.org/10.1111/j.1747-1567.2011.00776.x CrossRefGoogle Scholar
  18. 18.
    Godara A, Raabe D (2007) Influence of fiber orientation on global mechanical behavior and mesoscale strain localization in a short glass-fiber-reinforced epoxy polymer composite during tensile deformation investigated using digital image correlation. Compos Sci Technol 67(11-12):2417–2427.  https://doi.org/10.1016/j.compscitech.2007.01.005 CrossRefGoogle Scholar
  19. 19.
    Lomov SV, Boisse P, Deluycker E et al (2008) Full-field strain measurements in textile deformability studies. Compos A: Appl Sci Manuf 39(8):1232–1244.  https://doi.org/10.1016/j.compositesa.2007.09.014 CrossRefGoogle Scholar
  20. 20.
    Blaber J, Adair BS, Antoniou A (2015) A methodology for high resolution digital image correlation in high temperature experiments. Rev Sci Instrum 86(3):035111.  https://doi.org/10.1063/1.4915345 CrossRefGoogle Scholar
  21. 21.
    Ho CC, Wu DS, Chang YJ, Hsu JC, Kuo CL, Kuo SK (2017) Experimental investigation of speckle pattern by laser scribing for digital image correlation. J Laser Micro NanoEn 12(2):97–101.  https://doi.org/10.2961/jlmn.2017.02.0009
  22. 22.
    Chen X, Xu N, Yang L, Xiang D (2012) High temperature displacement and strain measurement using a monochromatic light illuminated stereo digital image correlation system. Meas Sci Technol 23(12):125603.  https://doi.org/10.1088/0957-0233/23/12/125603 CrossRefGoogle Scholar
  23. 23.
    Lyons JS, Liu J, Sutton MA (1996) High-temperature deformation measurements using digital-image correlation. Exp Mech 36(1):64–70.  https://doi.org/10.1007/BF02328699 CrossRefGoogle Scholar
  24. 24.
    Pan B, Wu D, Wang Z, Xia Y (2011) High-temperature digital image correlation method for full-field deformation measurement at 1200 °C. Meas Sci Technol 22(1):015701.  https://doi.org/10.1088/0957-0233/22/1/015701 CrossRefGoogle Scholar
  25. 25.
    Pan B, Jiang T, Wu D (2014) Strain measurement of objects subjected to aerodynamic heating using digital image correlation: experimental design and preliminary results. Rev Sci Instrum 85(11):115102.  https://doi.org/10.1063/1.4900659 CrossRefGoogle Scholar
  26. 26.
    Grant BMB, Stone HJ, Withers PJ, Preuss M (2009) High-temperature strain field measurement using digital image correlation. J Strain Anal Eng Des 44(4):263–271.  https://doi.org/10.1243/03093247JSA478 CrossRefGoogle Scholar
  27. 27.
    Fang X, Jia J, Feng X (2015) Three-point bending test at extremely high temperature enhanced by real-time observation and measurement. Measurement 59:171–176.  https://doi.org/10.1016/j.measurement.2014.09.062 CrossRefGoogle Scholar
  28. 28.
    Su H, Fang X, Qu Z et al (2016) Synchronous full-field measurement of temperature and deformation of C/SiC composite subjected to flame heating at high temperature. Exp Mech 56(4):659–671.  https://doi.org/10.1007/s11340-015-0066-5 CrossRefGoogle Scholar
  29. 29.
    Meyer P, Waas AM (2015) Measurement of in situ-full-field strain maps on ceramic matrix composites at elevated temperature using digital image correlation. Exp Mech 55(5):795–802.  https://doi.org/10.1007/s11340-014-9979-7 CrossRefGoogle Scholar
  30. 30.
    Hu Y, Bao S, Dan X et al (2018) Improvement of high-temperature deformation measurement accuracy based on image restoration method. Meas Sci Technol 29:094003.  https://doi.org/10.1088/1361-6501/aacd72 CrossRefGoogle Scholar
  31. 31.
    Novak MD, Zok FW (2011) High-temperature materials testing with full-field strain measurement: experimental design and practice. Rev Sci Instrum 82(11):115101.  https://doi.org/10.1063/1.3657835 CrossRefGoogle Scholar
  32. 32.
    Lebrun G, Bureau MN, Denault J (2003) Evaluation of bias-extension and picture-frame test methods for the measurement of intraply shear properties of PP/glass commingled fabrics. Compos Struct 61(4):341–352.  https://doi.org/10.1016/S0263-8223(03)00057-6 CrossRefGoogle Scholar
  33. 33.
    Tian L, Pan B, Tian L, Pan B (2016) Remote bridge deflection measurement using an advanced video deflectometer and actively illuminated LED targets. Sensors 16(9):1344.  https://doi.org/10.3390/s16091344 CrossRefGoogle Scholar
  34. 34.
    Pan B, Wu D, Gao J (2014) High-temperature strain measurement using active imaging digital image correlation and infrared radiation heating. J Strain Anal Eng Des 49(4):224–232.  https://doi.org/10.1177/0309324713502201 CrossRefGoogle Scholar
  35. 35.
    LePage W, Hayes Daly S, Andrew Shaw J (2016) Cross polarization for improved digital image correlation. Exp Mech 56(6):969–985. https://doi.org/10.1007/s11340-016-0129-2Google Scholar
  36. 36.
    Keane RD, Adrian RJ (1992) Theory of cross-correlation analysis of PIV images. Appl Sci Res 49(3):191–215.  https://doi.org/10.1007/BF00384623
  37. 37.
    Scarano F (2002) Iterative image deformation methods in PIV. Meas Sci Technol 13(1):R1–R19.  https://doi.org/10.1088/0957-0233/13/1/201 CrossRefGoogle Scholar
  38. 38.
    Scarano F, Riethmuller ML (2000) Advances in iterative multigrid PIV image processing. Exp Fluids 29(1):S051–S060.  https://doi.org/10.1007/s003480070007 Google Scholar
  39. 39.
    Berke RB, Lambros J (2014) Ultraviolet digital image correlation (UV-DIC) for high temperature applications. Rev Sci Instrum 85(4):045121.  https://doi.org/10.1063/1.4871991 CrossRefGoogle Scholar
  40. 40.
    Schreier H, Orteu J-J, Sutton MA (2009) Image correlation for shape, motion and deformation measurements. Springer, New YorkCrossRefGoogle Scholar
  41. 41.
    Berfield TA, Patel JK, Shimmin RG et al (2006) Fluorescent image correlation for nanoscale deformation measurements. Small 2(5):631–635.  https://doi.org/10.1002/smll.200500289 CrossRefGoogle Scholar
  42. 42.
    Hu Z, Xu T, Luo H et al (2016) Measurement of thickness and profile of a transparent material using fluorescent stereo microscopy. Opt Express 24(26):29822–29829.  https://doi.org/10.1364/OE.24.029822
  43. 43.
    Pan B (2018) Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals. Meas Sci Technol 29(8):082001.  https://doi.org/10.1088/1361-6501/aac55b CrossRefGoogle Scholar
  44. 44.
    Pan B, Yu L, Wu D, Tang L (2013) Systematic errors in two-dimensional digital image correlation due to lens distortion. Opt Lasers Eng 51(2):140–147.  https://doi.org/10.1016/j.optlaseng.2012.08.012 CrossRefGoogle Scholar
  45. 45.
    Montanini R, Freni F (2014) Non-contact measurement of linear thermal expansion coefficients of solid materials by infrared image correlation. Meas Sci Technol 25(1):015013.  https://doi.org/10.1088/0957-0233/25/1/015013 CrossRefGoogle Scholar
  46. 46.
    Lava P, Coppieters S, Wang Y et al (2011) Error estimation in measuring strain fields with DIC on planar sheet metal specimens with a non-perpendicular camera alignment. Opt Lasers Eng 49(1):57–65.  https://doi.org/10.1016/j.optlaseng.2010.08.017 CrossRefGoogle Scholar
  47. 47.
    Xu J, Moussawi A, Gras R, Lubineau G (2015) Using image gradients to improve robustness of digital image correlation to non-uniform illumination: effects of weighting and normalization choices. Exp Mech 55(5):963–979.  https://doi.org/10.1007/s11340-015-9996-1 CrossRefGoogle Scholar
  48. 48.
    Bomarito GF, Hochhalter JD, Ruggles TJ (2018) Development of optimal multiscale patterns for digital image correlation via local grayscale variation. Exp Mech 58(7):1169-1180.  https://doi.org/10.1007/s11340-017-0348-1
  49. 49.
    Potter K (2002) Bias extension measurements on cross-plied unidirectional prepreg. Compos A: Appl Sci Manuf 33(1):63–73.  https://doi.org/10.1016/S1359-835X(01)00057-4 CrossRefGoogle Scholar
  50. 50.
    Wang P, Hamila N, Pineau P, Boisse P (2014) Thermomechanical analysis of thermoplastic composite prepregs using bias-extension test. J Thermoplast Compos Mater 27(5):679–698.  https://doi.org/10.1177/0892705712454289
  51. 51.
    Boisse P, Hamila N, Guzman-Maldonado E et al (2017) The bias-extension test for the analysis of in-plane shear properties of textile composite reinforcements and prepregs: a review. Int J Mater Form 10(4):473–492.  https://doi.org/10.1007/s12289-016-1294-7 CrossRefGoogle Scholar
  52. 52.
    Harrison P, Clifford M, Long A (2004) Shear characterisation of viscous woven textile composites: a comparison between picture frame and bias extension experiments. Compos Sci Technol 64(10-11):1453–1465.  https://doi.org/10.1016/j.compscitech.2003.10.015
  53. 53.
    Cao J, Akkerman R, Boisse P et al (2008) Characterization of mechanical behavior of woven fabrics: experimental methods and benchmark results. Compos A: Appl Sci Manuf 39(6):1037–1053.  https://doi.org/10.1016/j.compositesa.2008.02.016 CrossRefGoogle Scholar
  54. 54.
    Vieille B, Taleb L (2011) About the influence of temperature and matrix ductility on the behavior of carbon woven-ply PPS or epoxy laminates: notched and unnotched laminates. Compos Sci Technol 71(7):998–1007.  https://doi.org/10.1016/j.compscitech.2011.03.006 CrossRefGoogle Scholar
  55. 55.
    Zink AG, Davidson RW, Hanna RB (2007) Strain measurement in wood using a digital image correlation technique. Wood Fiber Sci 27(4):346–359Google Scholar
  56. 56.
    Hall SA, Muir Wood D, Ibraim E, Viggiani G (2010) Localised deformation patterning in 2D granular materials revealed by digital image correlation. Granul Matter 12(1):1–14.  https://doi.org/10.1007/s10035-009-0155-1 CrossRefGoogle Scholar
  57. 57.
    Wang W, Xu C, Jin H et al (2017) Measurement of high temperature full-field strain up to 2000 °C using digital image correlation. Meas Sci Technol 28(3):035007.  https://doi.org/10.1088/1361-6501/aa56d1 CrossRefGoogle Scholar
  58. 58.
    Sztefek P, Vanleene M, Olsson R et al (2010) Using digital image correlation to determine bone surface strains during loading and after adaptation of the mouse tibia. J Biomech 43(4):599–605.  https://doi.org/10.1016/j.jbiomech.2009.10.042 CrossRefGoogle Scholar
  59. 59.
    Thompson MS, Schell H, Lienau J, Duda GN (2007) Digital image correlation: a technique for determining local mechanical conditions within early bone callus. Med Eng Phys 29(7):820–823.  https://doi.org/10.1016/j.medengphy.2006.08.012 CrossRefGoogle Scholar
  60. 60.
    Dickinson AS, Taylor AC, Ozturk H, Browne M (2011) Experimental validation of a finite element model of the proximal femur using digital image correlation and a composite bone model. J Biomech Eng 133(1):014504.  https://doi.org/10.1115/1.4003129 CrossRefGoogle Scholar
  61. 61.
    Zhang DS, Arola DD (2004) Applications of digital image correlation to biological tissues. J Biomed Opt 9(4):691-700.  https://doi.org/10.1117/1.1753270
  62. 62.
    Wu L, Yin Y, Zhang Q et al (2018) Bi-prism-based single-lens three dimensional digital image correlation system with a long working distance: methodology and application in extreme high temperature deformation test. Sci China Technol Sci 61(1):37–50.  https://doi.org/10.1007/s11431-017-9082-3
  63. 63.
    Yoneyama S, Kitagawa A, Kitamura K, Kikuta H (2006) In-plane displacement measurement using digital image correlation with Lens distortion correction. JSME Int J A-Solid M 49(3):458–467.  https://doi.org/10.1299/jsmea.49.458 CrossRefGoogle Scholar

Copyright information

© Society for Experimental Mechanics 2019

Authors and Affiliations

  1. 1.Université de Lyon, INSA-Lyon, LaMCoS UMR 5259Villeurbanne CedexFrance

Personalised recommendations