A New Parameter Identification Approach by Experimental Design and Multiple Regressions Method: Application to the Elastoplastic Damage Constitutive Law of a Steel Thin Parts

Article Preview

Abstract:

In this paper, a new procedure for the identification of constitutive elastoplastic models coupled with an isotropic damage variable under large strains is presented. It is a statistical approach used for experimental characterization and identification based on a design of experiments of numerical simulations of mechanical characterization tests. The parameters for a reference material are determined by multiple linear regression as a function of shape indices.The material of reference is mild steel E24; it was characterized in a series of tensile tests of thin plate specimens. The Swift hardening law coupled with an isotropic damage variable that was identified by introducing in the established formulations shape indexes extracted from the experimental tension/elongation curves.The number of simulations required for the identification of the parameters of the reference material is roughly 18% of the number required by the inverse method (simplex).

You might also be interested in these eBooks

Info:

Periodical:

Pages:

71-79

Citation:

Online since:

April 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Pijaudier‐Cabot, G., Bažant, Z. (1987), J Eng Mech 113(10), 1512. doi: 10. 1061/(ASCE) 0733-9399(1987)113: 10(1512).

DOI: 10.1061/(asce)0733-9399(1987)113:10(1512)

Google Scholar

[2] Ghouati, O., Gelin, J.C. (1998), J Mater Process Technol 80–81, 560. doi: 10. 1016/S0924-0136(98)00159-9.

Google Scholar

[3] Flores, P. (2005), Development of experimental equipment and identification procedures for sheet metal constitutive laws. [Ph.D. Thesis], University of Liege, Belgium.

Google Scholar

[4] Cooreman, S., Lecompte, D., Sol, H., Vantomme, J., Debruyne, D. (2007), International Journal of Solids and Structures 44(13), 4329. doi: 10. 1016/j. ijsolstr. 2006. 11. 024.

DOI: 10.1016/j.ijsolstr.2006.11.024

Google Scholar

[5] Feng, X.T., Yang, C. (2001), Comput Methods Appl Mech Eng 190(45), 5957. doi: 10. 1016/S0045-7825(01)00207-9.

Google Scholar

[6] Huber, N., Tsakmakis, C. (2001), Comput Methods Appl Mech Eng 191(3–5), 353. doi: 10. 1016/S0045-7825(01)00278-X.

Google Scholar

[7] Papadrakakis, M., Lagaros, N.D. (2002), Comput Methods Appl Mech Eng 191(32), 3491. doi: 10. 1016/S0045-7825(02)00287-6.

Google Scholar

[8] Nelder, J.A., Mead, R. (1965), Comput J 7(4), 308. doi: 10. 1093/comjnl/7. 4. 308.

Google Scholar

[9] Ayadi, M., Cherouat, A., Slimani, F., Rezgui, M.A., Zghal, A. (2011), Appl Mech Mater 62, 37. doi: 10. 4028/www. scientific. net/AMM. 62. 37.

DOI: 10.4028/www.scientific.net/amm.62.37

Google Scholar

[10] Bonnet, M., Constantinescu, A. (2005), Inverse probl 21(2), R1. doi: 10. 1088/0266-5611/21/2/R01.

Google Scholar

[11] Avril, S., Bonnet, M., Bretelle, A.S., Grediac, M., Hild, F., Ienny, P., Latourte, F., Lemosse, D., Pagano, S., Pagnacco, E., Pierron, F. (2008), Exp Mech 48(4), 381. doi: 10. 1007/s11340-008-9148-y.

DOI: 10.1007/s11340-008-9148-y

Google Scholar

[12] Ramault, C., Makris, A., Sol, H., Van Hemelrijck, D., Lecompte, D., Lamkanfi, E. (2009).

Google Scholar

[13] Montgomery, D.C. (2006), Design and analysis of experiments, 5th, ed Wiley, New York.

Google Scholar

[14] Ayadi, M., Rezgui, M.A., Cherouat, A., Slimani, F., Nasri, T.M. (2009), Mec Ind 10(06), 503. doi: 10. 1051/meca/2010009.

Google Scholar

[15] Cherouat, A., Ayadi, M., Rezgui, M.A. (2011), Int J Comput Methods Eng Sci Mech 12(3), 114. doi: 10. 1080/15502287. 2011. 564268.

Google Scholar