Abstract By the computer-aided method of material characterization many complex identification cases, where classic experimental–analytical methods of physical properties identification fail, can be successfully solved. Such an example is the standard tensile test of a flat steel sample, where the yield curve cannot be identified after the occurrence of the necking phenomenon. Yet, in deep drawing of metal sheets, strains and stresses beyond the limits derived by classic analytic expressions upon the tensile test measurements are often met. In order to enable physically objective numerical simulations of those processes, reliable material properties data must be provided. To cope with the problem of the extended yield curve identification, a special combined experimental/numerical technique has been developed. The technique relies on the comparison between the real material response, measured by the standard tensile test, and the response, obtained from a numerical simulation of the same test under assumption of a prescribed material behaviour. By proper tuning of some characteristic parameters of this tentative material behaviour law, the numerical response can be drawn close to the measured one. For this purpose a special numerical approach, based on mathematical optimization methods is employed.
[1]
Huang Yuan,et al.
Investigations of size effects in tensile tests based on a nonlocal micro-mechanical damage model
,
2003
.
[2]
Fpt Frank Baaijens,et al.
Prediction of ductile fracture in metal blanking
,
2000
.
[3]
J. Chenot,et al.
An inverse analysis using a finite element model for identification of rheological parameters
,
1996
.
[4]
W. Bleck,et al.
Modelling of sheet metal testing
,
1996
.
[5]
Vassili Toropov,et al.
Material parameter identification for large deformation plasticity models
,
1997
.
[6]
Elisabeth Massoni,et al.
Experimental and numerical determination of texture evolution during deep drawing tests
,
2001
.
[7]
Jasbir S. Arora,et al.
Introduction to Optimum Design
,
1988
.
[8]
James V. Beck,et al.
Parameter Estimation in Engineering and Science
,
1977
.