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A comparison study on experimental characterization of unidirectional fiber reinforced composites using strain-gauges and virtual extensometers

  • Muhsin Alci

    Muhsin Alci was born in 1988. He received his undergraduate and graduate degrees from Erciyes University, Department of Mechanical Engineering. While continuing his doctoral studies at Erciyes University, he works as a research assistant at Erciyes University and Nigde Omer Halisdemir University. His study subjects include production and test methods of composite materials, modeling composite materials, and finite element analysis.

     ORCID logo EMAIL logo     and Recep Gunes

    Dr. Recep Gunes was born in 1974. He has a BSc. (1995) degree in Mechanical Engineering, a MSc (1998) and a PhD (2005) degree on the solid mechanics from Erciyes University, Turkey. He is a professor of Applied Mechanics in the Dept of Mechanical Engineering, Erciyes University, Turkey. Dr. Gunes’s research interests are solid mechanics, mechanics of composite materials, impact dynamics, non-linear finite element method.
Published/Copyright: February 3, 2023
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Materials Testing
From the journal Materials Testing Volume 65 Issue 2

Abstract

The aim of this study is to characterize E-glass/epoxy unidirectional fiber reinforced composites using the digital image correlation method with virtual extensometer, which is a less laborious method than strain gauges, compare the results and investigate whether virtual extensometers can be used instead of strain gauges. Measurements in tensile and Iosipescu shear tests were made with both strain gauge and virtual extensometer. Unlike full-field strain measurements in literature, the strains were measured using virtual extensometers. Tensile test and in-plane shear test results gave very consistent results. The differences between the strain gauge and the virtual extensometer for the tensile and in-plane shear tests were less than 3% in the linear region. However, the out-of-plane shear test showed a larger difference of 8.6%. This study showed that the 2D digital image correlation method with virtual extensometers is highly sufficient to find the elasticity moduli and shear moduli in tensile and shear tests in the linear region. In addition, after the damage has started, more measurement data can be obtained with virtual extensometers than with strain gauges.

Keywords: digital image correlation; fiber reinforced composites; Iosipescu; strain gauges; tensile and shear test; virtual extensometer
Corresponding author: Muhsin Alci, Graduate School of Natural and Applied Sciences, Erciyes University, Kayseri, 38039, Türkiye; and Mechanical Engineering Department, Nigde Omer Halisdemir University, Niğde, Türkiye, E-mail:

Funding source: The Division of Scientific Research Projects (BAP), Erciyes University

Award Identifier / Grant number: FDK-2018-8704

About the authors

Muhsin Alci

Muhsin Alci was born in 1988. He received his undergraduate and graduate degrees from Erciyes University, Department of Mechanical Engineering. While continuing his doctoral studies at Erciyes University, he works as a research assistant at Erciyes University and Nigde Omer Halisdemir University. His study subjects include production and test methods of composite materials, modeling composite materials, and finite element analysis.

Recep Gunes

Dr. Recep Gunes was born in 1974. He has a BSc. (1995) degree in Mechanical Engineering, a MSc (1998) and a PhD (2005) degree on the solid mechanics from Erciyes University, Turkey. He is a professor of Applied Mechanics in the Dept of Mechanical Engineering, Erciyes University, Turkey. Dr. Gunes’s research interests are solid mechanics, mechanics of composite materials, impact dynamics, non-linear finite element method.

Acknowledgment

The authors thank the Division of Scientific Research Projects (BAP), Erciyes University.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This study was funded by the Division of Scientific Research Projects (BAP), Erciyes University, Turkey (Project No. FDK-2018-8704).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

[1] M. Kashfuddoja, R. G. R. Prasath, and M. Ramji, “Study on experimental characterization of carbon fiber reinforced polymer panel using digital image correlation: a sensitivity analysis,” Opt Laser. Eng., vol. 62, pp. 17–30, 2014, https://doi.org/10.1016/j.optlaseng.2014.04.019.Search in Google Scholar

[2 ] F. Zhu, P. Bai, and D. Lei, “Measurement of tensile mechanical properties of fiber reinforced plastic rebars by 3D digital image correlation,” Mater. Test., vol. 62, no. 4, pp. 422–428, 2020, https://doi.org/10.3139/120.111501.Search in Google Scholar

[3] B. Pan, K. Qian, H. Xie, and A. Asundi, “Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review,” Meas. Sci. Technol., vol. 20, no. 6, Apr. 2009, Art. no. 062001, https://doi.org/10.1088/0957-0233/20/6/062001.Search in Google Scholar

[4] B. Pan, “Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals,” Meas. Sci. Technol., vol. 29, no. 8, Jun. 2018, Art. no. 082001, https://doi.org/10.1088/1361-6501/aac55b.Search in Google Scholar

[5] S. W. Khoo, S. Karuppanan, and C. S. Tan, “A review of surface deformation and strain measurement using two-dimensional digital image correlation,” Metrol. Meas. Syst., vol. 23, no. 3, pp. 461–480, 2016, https://doi.org/10.1515/mms-2016-0028.Search in Google Scholar

[6] A. Makeev, C. Ignatius, Y. He, and B. Shonkwiler, “A test method for assessment of shear properties of thick composites,” J. Compos. Mater., vol. 43, no. 25, pp. 3091–3105, 2009, https://doi.org/10.1177/0021998309345330.Search in Google Scholar

[7] M. Tekieli, S. De Santis, G. de Felice, A. Kwiecień, and F. Roscini, “Application of digital image correlation to composite reinforcements testing,” Compos. Struct., vol. 160, pp. 670–688, 2017, https://doi.org/10.1016/j.compstruct.2016.10.096.Search in Google Scholar

[8] F. Zhu, X. Gu, P. Bai, and D. Lei, “Application of 3D digital image correlation for the measurement of the tensile mechanical properties of high-strength steel,” Mater. Test., vol. 63, no. 4, pp. 303–310, 2021, https://doi.org/10.1515/mt-2020-0044.Search in Google Scholar

[9] Y. Sun, J. Huang, D. Shi, et al.., “Tension and compression moduli characterization of a bimodular ceramic-fiber reinforced SiO2 aerogel composite,” Mater. Test., vol. 62, no. 10, pp. 1003–1009, 2020, https://doi.org/10.3139/120.111577.Search in Google Scholar

[10] Y. Kalariya, M. Kashfuddoja, S. Khedkar, and M. Ramji, “Applications of digital image correlation technique in composite research,” in 9th International Symposium on Advanced Science and Technology in Experimental Mechanics, New Delhi, India, 2014, pp. 1–6.Search in Google Scholar

[11] B. P. Justusson, D. M. Spagnuolo, and J. H. Yu, Assessing the Applicability of Digital Image Correlation (DIC) Technique in Tensile Testing of Fabric Composites, Maryland, USA, U.S. Army Research Laboratory, ARL-TR-6343, 2013.10.21236/ADA571047Search in Google Scholar

[12] O. Orell, J. Vuorinen, J. Jokinen, et al.., “Characterization of elastic constants of anisotropic composites in compression using digital image correlation,” Compos. Struct., vol. 185, pp. 176–185, 2018, https://doi.org/10.1016/j.compstruct.2017.11.008.Search in Google Scholar

[13] M. Karny, “Determination of in-plane shear properties of laminate with V-notch rail shear test and digital image correlation,” Trans. Aerosp. Res., vol. 2019, no. 3, pp. 57–65, 2019, https://doi.org/10.2478/tar-2019-0017.Search in Google Scholar

[14] A. Bastani, S. Mitra, K. Gorospe, and S. Das, “Determination of mechanical properties of FRP materials using the DIC method,” J. Test. Eval., vol. 49, no. 5, pp. 3266–3281, 2021, https://doi.org/10.1520/Jte20180530.Search in Google Scholar

[15] A. A. C. Pereira and J. R. M. D’Almeida, “Development of a low-cost digital image correlation system to evaluate the behavior of polymers at large deformation,” Chem. Eng. Trans., vol. 74, pp. 1081–1086, 2019, https://doi.org/10.3303/CET1974181.Search in Google Scholar

[16] S. L. Kumar, H. B. Aravind, and N. Hossiney, “Digital image correlation (DIC) for measuring strain in brick masonry specimen using Ncorr open source 2D MATLAB program,” Results in Engineering, vol. 4, Dec. 2019, Art. no. 100061, https://doi.org/10.1016/j.rineng.2019.100061.Search in Google Scholar

[17] T. Brynk, R. M. Molak, M. Janiszewska, and Z. Pakiela, “Digital Image Correlation measurements as a tool of composites deformation description,” Comput. Mater. Sci., vol. 64, pp. 157–161, 2012, https://doi.org/10.1016/j.commatsci.2012.04.034.Search in Google Scholar

[18] A. F. A. Ghani, “Digital image correlation technique in measuring deformation and failure of composite and adhesive,” ARPN J. Eng. Appl. Sci., vol. 11, no. 22, pp. 13193–13202, 2016.Search in Google Scholar

[19] S. Rohde, J. Cantrell, A. Jerez, et al.., “Experimental characterization of the shear properties of 3D–printed ABS and polycarbonate parts,” Exp. Mech., vol. 58, no. 6, pp. 871–884, 2018, https://doi.org/10.1007/s11340-017-0343-6.Search in Google Scholar

[20] M. Quanjin, M. R. M. Rejab, Q. Halim, M. N. M. Merzuki, and M. A. H. Darus, “Experimental investigation of the tensile test using digital image correlation (DIC) method,” Mater. Today: Proc., vol. 27, pp. 757–763, 2020, https://doi.org/10.1016/j.matpr.2019.12.072.Search in Google Scholar

[21] B. G. Lakshmi, K. Kaushik, Y. J. Rao, Y. Deepika, and N. Hiremath, “Experimental investigation for the determination of material properties of a composite laminate using resin and DIC techniques,” Mater. Today: Proc., vol. 45, pp. 231–235, 2021, https://doi.org/10.1016/j.matpr.2020.10.423.Search in Google Scholar

[22] F. López-Santos, A. May-Pat, E. R. Ledesma-Orozco, A. Hernández-Pérez, and F. Avilés, “Measurement of in-plane and out-of-plane elastic properties of woven fabric composites using digital image correlation,” J. Compos. Mater., vol. 55, no. 9, pp. 1231–1246, 2021, https://doi.org/10.1177/0021998320967073.Search in Google Scholar

[23] N. Hedayati, R. Madoliat, and R. Hashemi, “Strain measurement and determining coefficient of plastic anisotropy using digital image correlation (DIC),” Mechanics & Industry, vol. 18, no. 3, pp. 311–321, 2017, https://doi.org/10.1051/meca/2016060.Search in Google Scholar

[24] C. Cerbu, D. Xu, H. Wang, and I. C. Roşca, “The use of digital image correlation in determining the mechanical properties of materials,” in 3rd China-Romania Science and Technology Seminar (CRSTS 2018), Brasov, Romania, IOP Publishing, 2018, Art. no. 012007.10.1088/1757-899X/399/1/012007Search in Google Scholar

[25] I. E. Tabrizi, B. Alkhateab, J. S. M. Zanjani, and M. Yildiz, “Using digital image correlation for in situ strain and damage monitoring in hybrid fiber laminates under in-plane shear loading,” Polym. Compos., vol. 42, no. 8, pp. 4029–4042, 2021, https://doi.org/10.1002/pc.26114.Search in Google Scholar

[26] B. Croop and H. Lobo, Use of Digital Image Correlation to Obtain Material Model Parameters for Composites, USA, Datapoint Labs, 2013 [Online]. Available at: https://www.testpaks.com/papers-ppts/nafems2013dtl.pdf [accessed: Jan. 31, 2021].Search in Google Scholar

[27] H. Schreier, J. J. Orteu, and M. A. Sutton, Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts, Theory and Applications, 1st ed. Boston, USA, Springer, 2009.10.1007/978-0-387-78747-3Search in Google Scholar

[28] V. T. Nguyen, S. J. Kwon, O. H. Kwon, and Y. S. Kim, “Mechanical properties identification of sheet metals by 2D-digital image correlation method,” Procedia Eng., vol. 184, pp. 381–389, 2017, https://doi.org/10.1016/j.proeng.2017.04.108.Search in Google Scholar

[29] Y. L. Dong, Z. Y. Zhang, and B. Pan, “High-throughput, high-accuracy determination of coefficient of thermal expansion of carbon fibre–epoxy composites using digital image correlation,” Strain, vol. 54, no. 1, Dec. 2017, Art. no. e12259, https://doi.org/10.1111/str.12259.Search in Google Scholar

[30] T. Yıldırım, K. T. Felekoğlu, E. Gödek, M. Keskinateş, B. Felekoğlu, and O. Önal, “Investigation of multiple cracking behavior of cement-based fiber composites by digital image correlation method,” J. Fac. Eng. Archit. Gazi Univ., vol. 34, no. 1, pp. 479–493, 2019. https://doi.org/10.17341/gazimmfd.416508.Search in Google Scholar

[31] G. Szebényi and V. Hliva, “Detection of delamination in polymer composites by digital image correlation—experimental test,” Polymers, vol. 11, no. 3, pp. 523–533, 2019, https://doi.org/10.3390/polym11030523.Search in Google Scholar PubMed PubMed Central

[32] S. Yoneyama, “Basic principle of digital image correlation for in-plane displacement and strain measurement,” Adv. Compos. Mater., vol. 25, no. 2, pp. 105–123, 2016, https://doi.org/10.1080/09243046.2015.1129681.Search in Google Scholar

[33] T. M. Fayyad and J. M. Lees, “Application of digital image correlation to reinforced concrete fracture,” Procedia Mater. Sci., vol. 3, pp. 1585–1590, 2014, https://doi.org/10.1016/j.mspro.2014.06.256.Search in Google Scholar

[34] Standard Test Method for Tensile Properties of Polymer Matrix Composite Materials, ASTM Standard D3039/D3039M-17, Dec. 2017 [Online]. Available at: https://www.astm.org/d3039_d3039m-17.html.Search in Google Scholar

[35] Standard Test Method for Shear Properties of Composite Materials by the V-Notched Beam Method, ASTM D5379/D5379M-12, Oct. 2019 [Online]. Available at: https://www.astm.org/d5379_d5379m-12.html.Search in Google Scholar
Published Online: 2023-02-03
Published in Print: 2023-02-23

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Effect of cyclic loading on mechanical properties and microstructure of die cast magnesium alloy AZ91D
  3. Selective laser melting of Ti6Al4V alloy: effects of process parameters at constant energy density on mechanical properties, residual stress, microstructure and relative density
  4. A comparison study on experimental characterization of unidirectional fiber reinforced composites using strain-gauges and virtual extensometers
  5. A modified Johnson–Cook constitutive model for titanium alloy TA31 and its implementation into FE
  6. Anisotropy of epoxy acrylate with magnetic field-induced Ni-MWNTs
  7. A novel generalized normal distribution optimizer with elite oppositional based learning for optimization of mechanical engineering problems
  8. Improvement of metallurgical properties of A356 aluminium alloy by AlCrFeSrTiBSi master alloy
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  10. Mechanical property improvement of a AA6082 alloy by the TV-CAP process as a novel SPD method
  11. Effect of high temperatures on dry sliding friction and wear behaviour of CuCrZr copper alloy
  12. Joint performance of medium carbon steel-austenitic stainless steel double-sided TIG welds
  13. Enhancing the wear performance of Ti-6Al-4V against Al2O3 and WC-6Co via TiBn layer produced by boriding
  14. Cutting parameters optimization of hybrid fiber composite during drilling
  15. Dry sliding wear behavior of energy density dependent PA 12/Cu composites produced by selective laser sintering
https://doi.org/10.1515/mt-2022-0274
Keywords for this article
digital image correlation; fiber reinforced composites; Iosipescu; strain gauges; tensile and shear test; virtual extensometer

Articles in the same Issue

  1. Frontmatter
  2. Effect of cyclic loading on mechanical properties and microstructure of die cast magnesium alloy AZ91D
  3. Selective laser melting of Ti6Al4V alloy: effects of process parameters at constant energy density on mechanical properties, residual stress, microstructure and relative density
  4. A comparison study on experimental characterization of unidirectional fiber reinforced composites using strain-gauges and virtual extensometers
  5. A modified Johnson–Cook constitutive model for titanium alloy TA31 and its implementation into FE
  6. Anisotropy of epoxy acrylate with magnetic field-induced Ni-MWNTs
  7. A novel generalized normal distribution optimizer with elite oppositional based learning for optimization of mechanical engineering problems
  8. Improvement of metallurgical properties of A356 aluminium alloy by AlCrFeSrTiBSi master alloy
  9. Precipitation of carbides in a nickel-based cast heat-resistant alloy during thermal exposure: evolution of microstructure, hardness and corrosion properties
  10. Mechanical property improvement of a AA6082 alloy by the TV-CAP process as a novel SPD method
  11. Effect of high temperatures on dry sliding friction and wear behaviour of CuCrZr copper alloy
  12. Joint performance of medium carbon steel-austenitic stainless steel double-sided TIG welds
  13. Enhancing the wear performance of Ti-6Al-4V against Al2O3 and WC-6Co via TiBn layer produced by boriding
  14. Cutting parameters optimization of hybrid fiber composite during drilling
  15. Dry sliding wear behavior of energy density dependent PA 12/Cu composites produced by selective laser sintering
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