An Integrated Tool for Estimation of Material Model Parameters

Abstract

In this paper, we present results on estimating material model parameters from inverse analysis of full-field deformation data that was obtained with a prototype of a novel integrated tool consisting of a digital image correlation system and software for data analysis and parameter estimation. Such a tool is needed for characterizing the properties of new materials, and for calibrating and validating material models. The stereo microscope-based image analysis system may be used for measurements at temperatures up to 75°C, and field sizes of approximately 1 mm. The Graphical User Interface (GUI)-based parameter estimation tool integrates modules for image data analysis and inverse analysis, and incorporates features for interfacing the tool with commercial finite element (FEM) packages. The GUI, together with a micrograph of the sample, is used to select a subset of the imaged region for analysis, and for specifying sample grain boundaries needed for developing the FEM model. Data analysis includes data averaging to reduce measurement noise, and filtering to correct for rigid body translations and rotations. The inverse analysis module runs the FEM model under experimental loading conditions within its iterative loop, using the downhill simplex method for parameter estimation. The methodology was successfully validated from measurements on a superalloy sample.KeywordsPlastic ZoneDigital Image CorrelationMesh PointInverse AnalysisPlastic RegionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.