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Parameter covariance and non-uniqueness in material model calibration using the Virtual Fields Method

Journal Article · · Computational Materials Science
 [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
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Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Lastly, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.
Research Organization:
Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000; NA0003525
OSTI ID:
1457518
Alternate ID(s):
OSTI ID: 1582740
Report Number(s):
SAND--2018-6477J; 664481
Journal Information:
Computational Materials Science, Journal Name: Computational Materials Science Journal Issue: C Vol. 152; ISSN 0927-0256
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (19)

Incremental kinematics for finite element applications journal December 1993
Fitting hyperelastic models to experimental data journal August 2004
Identification of plastic constitutive parameters at large deformations from three dimensional displacement fields journal July 2011
Sensitivity-based virtual fields for the non-linear virtual fields method journal April 2017
Identification of Elasto-Plastic Constitutive Parameters from Statically Undetermined Tests Using the Virtual Fields Method journal November 2006
Stress Reconstruction and Constitutive Parameter Identification in Plane-Stress Elasto-plastic Problems Using Surface Measurements of Deformation Fields journal September 2007
Overview of Identification Methods of Mechanical Parameters Based on Full-field Measurements journal July 2008
Determination of Anisotropic Plastic Constitutive Parameters Using the Virtual Fields Method journal May 2014
Stereo-DIC Calibration and Speckle Image Generator Based on FE Formulations journal February 2017
On the identifiability of Anand visco-plastic model parameters using the Virtual Fields Method journal March 2015
A new approach for determination of material constants of internal state variable based plasticity models and their uncertainty quantification journal April 2012
Applying the Virtual Fields Method to the identification of elasto-plastic constitutive parameters journal April 2006
Application of the virtual fields method to the identification of the homogeneous anisotropic hardening parameters for advanced high strength steels journal June 2017
Extension of the virtual fields method to elasto-plastic material identification with cyclic loads and kinematic hardening journal November 2010
On the use of simulated experiments in designing tests for material characterization from full-field measurements journal February 2012
Characterization of the post-necking strain hardening behavior using the virtual fields method journal November 2013
Application of the virtual fields method to large strain anisotropic plasticity journal October 2016
Identification of elasto-visco-plastic parameters and characterization of Lüders behavior using digital image correlation and the virtual fields method journal September 2008
Identification of Johnson-Cook's Viscoplastic Model Parameters Using the Virtual Fields Method: Application to Titanium Alloy Ti6Al4V: Identification of JC Viscoplastic Model Parameters Using the VFM journal November 2012

Cited By (3)

Experimental Validation of the Sensitivity-Based Virtual Fields for Identification of Anisotropic Plasticity Models journal February 2020
Investigation of assumptions and approximations in the virtual fields method for a viscoplastic material model journal February 2019
Progress toward autonomous experimental systems for alloy development journal April 2019

Figures / Tables (24)

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Related Subjects

304L stainless steel
36 MATERIALS SCIENCE
97 MATHEMATICS AND COMPUTING
Bammann-Chiesa-Johnson (BCJ) material model
Digital Image Correlation (DIC)
Material identification
Virtual Fields Method (VFM)
Viscoplasticity