Comparison of Hysteretic Models for Steel Beams Calibrated by Means of Multi-Objective Optimisation

Article Preview

Abstract:

Phenomenological models are often used to model post-elastic behaviour of steel members in the framework of concentrated-plasticity approach. Many of them can simulate degradation phenomena occurring during cyclic loading, but are dependent on model parameters without clear physical meaning. To overcome this issue, parameter calibration should be performed by curve fitting of experimental responses. In this work, several numerical models implemented in widely used software packages are calibrated against the results provided by an experimental programme involving cyclic and monotonic tests on open and closed cross-section profiles, according a multi-objective methodology recently developed by the authors. The extensive calibration analyses carried out show that the most reliable model among those investigated is the Sivalselvan-Reinhorn model, which is able to provide accurate simulation of both monotonic and cyclic responses. Extension of the calibration procedure is proposed, with an additional objective related to the envelope curve of the cyclic response, and it is shown that this improvement adds robustness to the results.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

487-494

Citation:

Online since:

February 2018

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2018 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] G. C. Lee and E. Lee, Local buckling of steel sections under cyclic loading, Journal of Constructional Steel Research, vol. 29, no. 1, pp.55-70, (1994).

DOI: 10.1016/0143-974x(94)90056-6

Google Scholar

[2] T. Takeda, M. Sozen and N. Nielsen, Reinforced Concrete Response to Simulated Earthquakes, Journal of the Structural Division, vol. 96, no. 12, pp.2557-2573, (1970).

DOI: 10.1061/jsdeag.0002765

Google Scholar

[3] R. Bouc, Forced vibration of mechanical systems with hysteresis, in Proceedings of the fourth conference on non-linear oscillation, Prague, Czechoslovakia, (1967).

Google Scholar

[4] Y. -K. Wen, Method for random vibration of hysteretic systems, ASCE J Eng Mech Div, vol. 102, no. 2, pp.249-263, (1976).

DOI: 10.1061/jmcea3.0002106

Google Scholar

[5] W. Ramberg and W. Osgood, Description of stress–strain curves by three parameters, National Advisory Committee on Aeronautics, Technical Note 902, (1943).

Google Scholar

[6] R. M. Richard and B. J. Abbott, Versatile Elasto-Plastic Stress-Strain Formula, Journal of the Engineering Mechanics Division, vol. 101, no. 4, pp.511-515, (1975).

DOI: 10.1061/jmcea3.0002047

Google Scholar

[7] R. K. Dowell, F. Seible and E. L. Wilson, Pivot hysteresis model for reinforced concrete members, ACI Structural Journal, vol. 95, no. 5, pp.607-617, (1998).

DOI: 10.14359/575

Google Scholar

[8] M. V. Sivaselvan and A. M. Reinhorn, Hysteretic models for deteriorating inelastic structures, J. Eng. Mech., vol. 126, no. 6, pp.633-640, (2000).

DOI: 10.1061/(asce)0733-9399(2000)126:6(633)

Google Scholar

[9] L. F. Ibarra, R. A. Medina and H. Krawinkler, Hysteretic models that incorporate strength and stiffness deterioration, Earthquake Engng Struct. Dyn., vol. 34, pp.1489-1511, (2005).

DOI: 10.1002/eqe.495

Google Scholar

[10] American Institute of Steel Construction, ANSI/AISC 341-10, AISC, (2010).

Google Scholar

[11] C. Chisari, A. B. Francavilla, M. Latour, V. Piluso, G. Rizzano and C. Amadio, Critical issues in parameter calibration of cyclic models for steel members, Engineering Structures, vol. 132, pp.123-138, (2017).

DOI: 10.1016/j.engstruct.2016.11.030

Google Scholar

[12] K. Miettinen, Nonlinear Multiobjective Optimization, Springer, (1999).

Google Scholar

[13] J. H. Holland, Adaptation in natural and artificial systems. an introductory analysis with applications to biology, control and artificial intelligence, The University of Michigan Press, Ann Arbor, USA, (1975).

Google Scholar

[14] K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp.182-197, (2002).

DOI: 10.1109/4235.996017

Google Scholar

[15] C. Chisari, G. Rizzano and C. Amadio, MultiCal - Multi-objective calibration of hysteretic models, July 2017. [Online]. Available: www. multical. unisa. it. [Accessed 29 August 2017].

Google Scholar

[16] M. D'Aniello, R. Landolfo, V. Piluso and G. Rizzano, Ultimate behavior of steel beams under non-uniform bending, Journal of Constructional Steel Research, vol. 78, pp.144-158, (2012).

DOI: 10.1016/j.jcsr.2012.07.003

Google Scholar

[17] OpenSees, Open System for Earthquake Engineering Simulation, 2010. [Online]. Available: http: /opensees. berkeley. edu/wiki/index. php/Main_Page. [Accessed 12 October 2016].

Google Scholar

[18] Seismosoft, SeismoStruct v7. 0 – A computer program for static and dynamic nonlinear analysis of framed structures, 2014. [Online]. Available: http: /www. seismosoft. com. [Accessed 13 April 2016].

Google Scholar