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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Johnson, D. A., Porter III, W. J., John, R., “Full-Field Techniques in the Study of Multi-Scale Nonlinear Material Behavior,” Proc. SEM Annual Conference, Experimentation and Modeling at the Nanoscale, Society for Experimental Mechanics, Charlotte, NC, 2–4 June 2003.
Chu, T. C., Ranson, W. F., Sutton, M. A., Peters, W. H., “Application of Digital Image Correlation Techniques to Experimental Mechanics,” Experimental Mechanics, 25 (3), pp 232–245, 1985.
Sutton, M. A., Cheng, M., Peters, W. H., Chao, Y. J., and McNeill, S. R., “Application of an Optimized Digital Correlation Method to Planar Deformation Analysis,” Image and Vision Computing, 4 (3), pp 143-150, 1986.
Helm JD, McNeill SR, Sutton MA (1996) Improved 3-D Image Correlation for Surface Displacement Measurement. Optical Engineering 35(7):1911–1920
Schreier, H. W., Braasch, J. R., Sutton, M. A., “Systematic Errors in Digital Image Correlation Caused by Intensity Interpolation,” Opt. Eng., 39(11), 2000.
Schreier, H. W., Sutton, M. A., “Systematic Errors in Digital Image Correlation Due to Undermatched Subset Shape Functions,” Experimental Mechanics, 43(2), 2002.
Jones, R. M., Mechanics of Composite Materials, 2nd Edition, Taylor and Francis, 1999.
ADINA R&D, ADINA Theory and Modeling Guide, Volume 1: ADINA Structures and Solids, p. 278, October 2005.
Lankford WT, Snyder SC, Bausher JA (1950) New Criteria for Predicting the Press Performance of Deep Drawing Sheets. Trans ASM 42:1197–1205
Press WH, Flannery BP, Teukolsky SA, Vetterling WT (1992) Numerical Recipes in C, 2nd edn. The Art of Scientific Computing, Cambridge University Press
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 The Society for Experimental Mechanics, Inc.
About this paper
Cite this paper
Ghosal, S., Acharya, N., Abrahamson, T.E., Porter, L.M., Schreier, H.W. (2013). An Integrated Tool for Estimation of Material Model Parameters. In: Proulx, T. (eds) Application of Imaging Techniques to Mechanics of Materials and Structures, Volume 4. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9796-8_12
Download citation
DOI: https://doi.org/10.1007/978-1-4419-9796-8_12
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-9528-5
Online ISBN: 978-1-4419-9796-8
eBook Packages: EngineeringEngineering (R0)