  Indentation test is used with growing popularity for the characterization of
various materials on different scales. Developed methods are combining the test
with computer simulation and inverse analyses to assess material parameters
entering into constitutive models. The outputs of such procedures are expressed
as evaluation of sought parameters in deterministic sense, while for
engineering practice it is desirable to assess also the uncertainty which
affects the final estimates resulting from various sources of errors within the
identification procedure. In this paper an experimental-numerical method is
presented centered on inverse analysis build upon data collected from the
indentation test in the form of force-penetration relationship (so-called
indentation curve). Recursive simulations are made computationally economical
by an a priori model reduction procedure. Resulting inverse problem is solved
in a stochastic context using Monte Carlo simulations and non-sequential
Extended Kalman filter. Obtained results are presented comparatively as for
accuracy and computational efficiency.
