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Title: Implementation and Evaluation of the Virtual Fields Method: Determining Constitutive Model Parameters From Full-Field Deformation Data.

Abstract

The Virtual Fields Method (VFM) is an inverse method for constitutive model parameter identication that relies on full-eld experimental measurements of displacements. VFM is an alternative to standard approaches that require several experiments of simple geometries to calibrate a constitutive model. VFM is one of several techniques that use full-eld exper- imental data, including Finite Element Method Updating (FEMU) techniques, but VFM is computationally fast, not requiring iterative FEM analyses. This report describes the im- plementation and evaluation of VFM primarily for nite-deformation plasticity constitutive models. VFM was successfully implemented in MATLAB and evaluated using simulated FEM data that included representative experimental noise found in the Digital Image Cor- relation (DIC) optical technique that provides full-eld displacement measurements. VFM was able to identify constitutive model parameters for the BCJ plasticity model even in the presence of simulated DIC noise, demonstrating VFM as a viable alternative inverse method. Further research is required before VFM can be adopted as a standard method for constitu- tive model parameter identication, but this study is a foundation for ongoing research at Sandia for improving constitutive model calibration.

Authors:
;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1158669
Report Number(s):
SAND2014-17871
537632
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Kramer, Sharlotte Lorraine Bolyard, and Scherzinger, William M. Implementation and Evaluation of the Virtual Fields Method: Determining Constitutive Model Parameters From Full-Field Deformation Data.. United States: N. p., 2014. Web. doi:10.2172/1158669.
Kramer, Sharlotte Lorraine Bolyard, & Scherzinger, William M. Implementation and Evaluation of the Virtual Fields Method: Determining Constitutive Model Parameters From Full-Field Deformation Data.. United States. doi:10.2172/1158669.
Kramer, Sharlotte Lorraine Bolyard, and Scherzinger, William M. Mon . "Implementation and Evaluation of the Virtual Fields Method: Determining Constitutive Model Parameters From Full-Field Deformation Data.". United States. doi:10.2172/1158669. https://www.osti.gov/servlets/purl/1158669.
@article{osti_1158669,
title = {Implementation and Evaluation of the Virtual Fields Method: Determining Constitutive Model Parameters From Full-Field Deformation Data.},
author = {Kramer, Sharlotte Lorraine Bolyard and Scherzinger, William M.},
abstractNote = {The Virtual Fields Method (VFM) is an inverse method for constitutive model parameter identication that relies on full-eld experimental measurements of displacements. VFM is an alternative to standard approaches that require several experiments of simple geometries to calibrate a constitutive model. VFM is one of several techniques that use full-eld exper- imental data, including Finite Element Method Updating (FEMU) techniques, but VFM is computationally fast, not requiring iterative FEM analyses. This report describes the im- plementation and evaluation of VFM primarily for nite-deformation plasticity constitutive models. VFM was successfully implemented in MATLAB and evaluated using simulated FEM data that included representative experimental noise found in the Digital Image Cor- relation (DIC) optical technique that provides full-eld displacement measurements. VFM was able to identify constitutive model parameters for the BCJ plasticity model even in the presence of simulated DIC noise, demonstrating VFM as a viable alternative inverse method. Further research is required before VFM can be adopted as a standard method for constitu- tive model parameter identication, but this study is a foundation for ongoing research at Sandia for improving constitutive model calibration.},
doi = {10.2172/1158669},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Sep 01 00:00:00 EDT 2014},
month = {Mon Sep 01 00:00:00 EDT 2014}
}

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