TY - JOUR A1 - Reese, Daniel A1 - Ullner, Christian A1 - Tyulyukovskiy, E. A1 - Huber, N. T1 - Identification of viscoplastic material parameters from spherical indentation data: Part II. Experimental validation of the method JF - Journal of materials research N2 - A neural network-based analysis method for the identification of a viscoplasticity model from spherical indentation data, developed in the first part of this work [J. Mater. Res. 21, (2006)], was applied for different metallic materials. Besides the comparison of typical parameters like Young's modulus and yield stress with values from tensile experiments, the uncertainties in the identified material parameters representing modulus, hardening behavior, and viscosity were investigated in relation to different sources. Variations in the indentation position, tip radius, force application rate, and surface preparation were considered. The extensive experimental validation showed that the applied neural networks are very robust and show small variation coefficients, especially regarding the important parameters of Young's modulus and yield stress. On the other hand, important requirements were quantified, which included a very good spherical indenter geometry and good surface preparation to obtain reliable results. KW - Viskoplastizität KW - Spannungs-Dehnungs-Kurve KW - Neuronale Netze KW - Validierung PY - 2006 DO - https://doi.org/10.1557/JMR.2006.0077 SN - 0884-2914 N1 - Geburtsname von Reese, Daniel: Klötzer, D. - Birth name of Reese, Daniel: Klötzer, D. VL - 21 IS - 3 SP - 677 EP - 684 PB - Materials Research Society CY - Warrendale, Pa. AN - OPUS4-12274 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -