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Arabian Journal for Science and Engineering

, Volume 44, Issue 2, pp 1221–1231 | Cite as

A New Approach to Modeling the Ductile Cast Iron Microstructure for a Finite Element Analysis

  • Jesus A. Basurto-Hurtado
  • G. I. Perez-Soto
  • Roque A. Osornio-Rios
  • Aurelio Dominguez-Gonzalez
  • L. A. Morales-Hernandez
Research Article - Mechanical Engineering
  • 12 Downloads

Abstract

In this article, a methodology for the generation of geometric models representing the microstructure of a ductile cast iron (DCI) is presented. This methodology is based on a series of image processing algorithms to extract the graphite nodules contours and the utilization of the Bezier curves to smooth the geometric models curves. For the contours obtained by the image processing stage and generated geometric models, the circularity is calculated using the circular shape factor index, in order to analyze the induced error through the discretization process by the image processing stage and the variation of the circularity as the design parameters of the geometric modeling change. On the other hand, the design parameters effect of the geometric models on the stress behavior in the microstructure, through a finite element analysis, is also analyzed. It is shown that as the Bezier curve degree increases, the circularity of the geometric models decreases, thus increasing the maximum stresses produced in the DCI microstructure. Further, it is also found that the number of interpolation points has a significant effect on the mechanical properties when the Bezier curves degrees are equal to 10 and 12 than for the lower degrees.

Keywords

Bezier curves Geometric modeling Finite element analysis Circularity Ductile cast iron Image processing 

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Notes

Acknowledgements

The first author would like to thank CONACYT for the scholarship (CVU: 419770) given. The author is also grateful to the English Department of Engineer Faculty in San Juan del Rio, Qro. Mex., for proofreading this article.

Compliance with Ethical Standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

References

  1. 1.
    Basurto-Hurtado, J.A.; Morales-Hernndez, L.A.; Osornio-Rios, R.A.; Dominguez-Gonzalez, A.: An approach based on the exploratory data analysis to relate the wear behavior with the microstructure of ductile cast irons. Adv. Mater. Sci. Eng. 2016, 11 (2016)CrossRefGoogle Scholar
  2. 2.
    Zhang, J.; Zhang, N.; Zhang, M.; Lu, L.; Zeng, D.; Song, Q.: Microstructure and mechanical properties of austempered ductile iron with different strength grades. Mater. Lett. 119, 47–50 (2014)CrossRefGoogle Scholar
  3. 3.
    Durmu, A.; Aydn, H.; Tutar, M.; Bayram, A.; Yiit, K.: Effect of the microstructure on the notched tensile strength of as-cast and austempered ductile cast irons. Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 226, 2214–2229 (2012)CrossRefGoogle Scholar
  4. 4.
    Konen, R.; Nicoletto, G.; Bubenko, L.; Fintov, S.: A comparative study of the fatigue behavior of two heat-treated nodular cast irons. Eng. Fract. Mech. 108, 251–262 (2013)CrossRefGoogle Scholar
  5. 5.
    Likhite, A.; Peshwe, D.R.; Pathak, S.U.: Effect of graphite morphology on modulus of elasticity of low carbon equivalent ductile iron. Trans. Indian Inst. Met. 61, 497–501 (2008)CrossRefGoogle Scholar
  6. 6.
    Iacoviello, F.; Di Bartolomeo, O.; Di Cocco, V.; Piacente, V.: Damaging micromechanisms in ferriticpearlitic ductile cast irons. Mater. Sci. Eng. A 478, 181–186 (2008)CrossRefGoogle Scholar
  7. 7.
    Murcia, S.C.; Ossa, E.A.; Celentano, D.J.: Nodule evolution of ductile cast iron during solidification. Metall. Mater. Trans. B 45, 707–718 (2014)CrossRefGoogle Scholar
  8. 8.
    Hervas, I.; Bettaieb, M.B.; Thuault, A.; Hug, E.: Graphite nodule morphology as an indicator of the local complex strain state in ductile cast iron. Mater. Des. 52, 524–532 (2013)CrossRefGoogle Scholar
  9. 9.
    Vako, A.: Evaluation of shape of graphite particles in cast irons by a shape factor. Mater. Today: Proc. 3, 1199–1204 (2016)CrossRefGoogle Scholar
  10. 10.
    Htter, G.; Zybell, L.; Kuna, M.: Micromechanical modeling of crack propagation in nodular cast iron with competing ductile and cleavage failure. Eng. Fract. Mech. 147, 388–397 (2015)CrossRefGoogle Scholar
  11. 11.
    Collini, L.; Pirondi, A.: Fatigue crack growth analysis in porous ductile cast iron microstructure. Int. J. Fatigue 62, 258–265 (2014)CrossRefGoogle Scholar
  12. 12.
    Di Cocco, V.; Iacoviello, D.; Iacoviello, F.; Rossi, A.: Graphite nodules influence on DCIs mechanical properties: experimental and numerical investigation. Proc. Eng. 109, 135–143 (2015)CrossRefGoogle Scholar
  13. 13.
    Ljustina, G.; Larsson, R.; Fagerstrm, M.: A FE based machining simulation methodology accounting for cast iron microstructure. Finite Elem. Anal. Des. 80, 1–10 (2014)CrossRefGoogle Scholar
  14. 14.
    Fernandino, D.O.; Cisilino, A.P.; Boeri, R.E.: Determination of effective elastic properties of ferritic ductile cast iron by computational homogenization, micrographs and microindentation tests. Mech. Mater. 83, 110–121 (2015)CrossRefGoogle Scholar
  15. 15.
    Carazo, F.D.; Giusti, S.M.; Boccardo, A.D.; Godoy, L.A.: Effective properties of nodular cast-iron: a multi-scale computational approach. Comput. Mater. Sci. 82, 378–390 (2014)CrossRefGoogle Scholar
  16. 16.
    Vijayaragavan, A.; Visumathi, J.; Shunmuganathan, K.L.: Cubic Bezier curve approach for automated offline signature verification with intrusion identification. Math. Probl. Eng. 2014, 7 (2014)CrossRefGoogle Scholar
  17. 17.
    Ghomanjani, F.; Farahi, M.H.; Klman, A.; Kamyad, A.V.; Pariz, N.: Bezier curves based numerical solutions of delay systems with inverse time. Math. Probl. Eng. 2014, 16 (2014)MathSciNetGoogle Scholar
  18. 18.
    Ghomanjani, F.; Farahi, M.H.; Klman, A.: Bezier curves for solving Fredholm integral equations of the second kind. Math. Probl. Eng. 2014, 6 (2014)MathSciNetGoogle Scholar
  19. 19.
    Soille, P.: Morphological Image Analysis: Principles and Applications, 2nd edn, pp. 190–191. Springer Science & Business Media, Berlin (2004)CrossRefGoogle Scholar
  20. 20.
    Morales-Hernndez, L.A.; Terol-Villalobos, I.R.; Domnguez-Gonzlez, A.; Manriquez-Guerrero, F.; Herrera-Ruiz, G.: Spatial distribution and spheroidicity characterization of graphite nodules based on morphological tools. J. Mater. Process. Technol. 210, 335–342 (2010)CrossRefGoogle Scholar
  21. 21.
    Talbot, H.; Terol-Villalobos, I.R.: San Diego, binary image segmentation using weighted skeletons. In: SPIE Proceedings Image Algebra and Morphological Image Processing III, San Diego, California, USA, 19 July 1992, vol. 1769, pp. 393–404.Google Scholar
  22. 22.
    Pal, S.; Ganguly, P.; Biswas, P.K.: Cubic Bezier approximation of a digitized curve. J. Pattern Recognit. 40, 2730–2741 (2007)CrossRefzbMATHGoogle Scholar
  23. 23.
    Da, F.M.; Gomes, O.; Paciornik, S.: Automatic classification of graphite in cast iron. J. Microsc. Microanal. 11, 363–371 (2005)CrossRefGoogle Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.CA Mecatronica, Facultad de IngenieriaUniversidad Autonoma de Queretaro (UAQ)San Juan del RioMexico
  2. 2.Facultad de IngenieriaUniversidad Autonoma de Queretaro (UAQ)Santiago de QueretaroMexico

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