NCAL: Plasticity Modeling

Summary

Successful modeling of the plastic (not recovered) deformation of a part of structure relies on an accurate model of the material deformation. This material model is typically used as an input to finite element analysis (FEA) software.  These material models can be quite complex and parameters are often tailored for the particular phenomena that is most crucial (springback, anisotropy, strain rate, heating) for the prediction of the shape or load response of a part or structure.

At the NIST Center for Automotive Lightweighting (NCAL), we are working to develop or validate new materials models for use in industry and apply inverse methods to use experimental data from mechanical tests to fit parameters for material models.

Description

FEA and Optimization

While FEA and optimization is a key part of many of our projects, two projects make the heaviest use of these techniques. Both of these projects have required detailed FEA models of the specimens, measured boundary conditions (instead of nominal), and iterative FEA optimization to match experimental data.

NCAL: Multiaxial Material Performance  

We are iterating on cruciform specimen design to with a goal to achieve significant strain in the center of the specimen before sample failure.  The strain localization that occurs at the corners of the cruciform geometry is often the limiting factor for strain in the center area.  In our research to obtain an accurate prediction of plastic deformation in the center area, we have found that predicting the extent of the strain localization is necessary and requires material models that incorporate local heating, strain rate effects, and include plastic deformation past uniform elongation.  

NCAL: Tension-Compression Testing

We are leveraging the Numisheet 2022 material data to verify the Yoshida-Uemeri (Y-U) model (by determining appropriate values of Y-U model parameters based on judicious choice of uniaxial and multiloop stress-strain cycle data) for predicting tension-compression asymmetry.  

Digital Twins

An effort is underway to construct a digital twin (DT) framework designed for rapid feedback and control of materials microstructure in the laser-based metals additive manufacturing (AM) processes such as laser powder bed fusion (L-PBF) and directed energy deposition (DED) processes. This is a joint project with the Thermodynamics and Kinetics Group. The objectives are to develop well verified multiscale physics-based models, integrate data assimilation (DA) techniques with ensemble and reduced order modeling approaches, develop surrogate models to accelerate DT framework predictions, and develop tools for workflow management. Some of the challenges in this project are:  developing robust surrogate models and data assimilation approaches, and building a high-fidelity approach for uncertainty quantification (UQ) associated with the DT framework development. This work is expected to help in developing surrogate models for the Material Testing 2.0 efforts. Additionally, data assimilation techniques are expected to aid in obtaining material model parameters efficiently for MT 2.0 efforts (e.g., VFM) while ensuring compatibility with experimental data during the fitting process.

Crystal Plasticity

Crystal Plasticity Modeling calculates multiaxial mechanical constitutive behavior by treating the specimen as an interacting aggregate of single crystals that interact at their boundaries. The mechanical response is determined from a weighted average of the single crystal behavior. Ideally, the constitutive law would not need to be "trained" using empirical mechanical property data alone, but would be able to compensate for changes in crystallographic texture of the incoming sheet.

To this end, this project seeks to develop constitutive laws based on the initial crystallographic texture and uniaxial stress-strain data, predicting the evolution of the yield surface in multiaxial tensile space. Crystal plasticity modeling treats the material as an assemblage of interacting single crystals with an orientation distribution recreated from the measured texture. As plastic yield evolves, the crystals slip according to the Schmid factor of each system, and each grain rotates to maintain boundary compatibility. The constitutive behavior is then calculated as an average mechanical response of the aggregate.

Major Accomplishments

• Jinjae Kim et al., “Multi-Interpolation Method to Linearize Stress Path in Cruciform Specimen for In-Plane Biaxial Test,” JOM 75, no. 12 (December 2023): 5505–14, https://doi.org/10.1007/s11837-023-06158-x.
• Dilip K. Banerjee et al., “Evaluation of Methods for Determining the Yoshida-Uemori Combined Isotropic/Kinematic Hardening Model Parameters from Tension-Compression Tests of Advanced Lightweighting Materials,” MATERIALS TODAY COMMUNICATIONS 33 (December 2022), https://doi.org/10.1016/j.mtcomm.2022.104270.
• Elizabeth M. Mamros et al., “Plastic Anisotropy Evolution of SS316L and Modeling for Novel Cruciform Specimen,” INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 234 (November 15, 2022), https://doi.org/10.1016/j.ijmecsci.2022.107663.
• Dilip K. Banerjee, Mark A. Iadicola, and Adam A. Creuziger, “Understanding Deformation Behavior in Uniaxial Tensile Tests of Steel Specimens at Varying Strain Rates,” Journal of Research of the National Institute of Standards and Technology 126 (2021): 126050, https://doi.org/10.6028/jres.126.050.
• Adam Creuziger, Whitney Poling, and Thomas Gnaeupel-Herold, “Assessment of Martensitic Transformation Paths Based on Transformation Potential Calculations,” Steel Research International 90 (January 2019), https://doi.org/10.1002/srin.201800370.
• Adam Creuziger, Whitney A. Poling, and Thomas Gnaeupel-Herold, “Supporting Information: Assessment of Martensitic Transformation Paths Based on Transformation Potential Calculations,” Steel Research International, January 2019, https://doi.org/10.1002/srin.201800370.
• Adam Creuziger, Whitney Poling, and Thomas Gnäupel-Herold, “DataSet: Assessment of Martensitic Transformation Paths Based on Transformation Potential Calculations” (National Institute of Standards and Technology, October 23, 2018), https://doi.org/10.18434/T4/1503156.
• M.S. Pham et al., “Roles of Texture and Latent Hardening on Plastic Anisotropy of Face-Centered-Cubic Materials during Multi-Axial Loading,” Journal of the Mechanics and Physics of Solids 99 (February 2017): 50–69, https://doi.org/10.1016/j.jmps.2016.08.011.
• Y. Jeong et al., “Uncertainty in Flow Stress Measurements Using X-Ray Diffraction for Sheet Metals Subjected to Large Plastic Deformations,” Journal of Applied Crystallography 49, no. 6 (December 1, 2016): 1991–2004, https://doi.org/10.1107/S1600576716013662.
• Y. Jeong et al., “Multiaxial Constitutive Behavior of an Interstitial-Free Steel: Measurements through X-Ray and Digital Image Correlation,” Acta Materialia 112 (June 15, 2016): 84–93, https://doi.org/10.1016/j.actamat.2016.04.013.
• Youngung Jeong et al., “Forming Limit Prediction Using a Self-Consistent Crystal Plasticity Framework: A Case Study for Body-Centered Cubic Materials,” Modelling and Simulation in Materials Science and Engineering 24, no. 5 (May 10, 2016): 055005, https://doi.org/10.1088/0965-0393/24/5/055005.
• Minh-Son Pham et al., “Thermally-Activated Constitutive Model Including Dislocation Interactions, Aging and Recovery for Strain Path Dependence of Solid Solution Strengthened Alloys: Application to AA5754-O,” International Journal of Plasticity 75 (December 2015): 226–43, https://doi.org/10.1016/j.ijplas.2014.09.010.
• Youngung Jeong et al., “Evaluation of Biaxial Flow Stress Based on Elasto-Viscoplastic Self-Consistent Analysis of X-Ray Diffraction Measurements,” International Journal of Plasticity 66 (March 2015): 103–18, https://doi.org/10.1016/j.ijplas.2014.06.009.
• M.A. Iadicola et al., “Crystal Plasticity Analysis of Constitutive Behavior of 5754 Aluminum Sheet Deformed along Bi-Linear Strain Paths,” International Journal of Solids and Structures 49, no. 25 (December 2012): 3507–16, https://doi.org/10.1016/j.ijsolstr.2012.03.015.
• L. Hu et al., “Constitutive Relations for AA 5754 Based on Crystal Plasticity,” Metallurgical and Materials Transactions A 43, no. 3 (March 2012): 854–69, https://doi.org/10.1007/s11661-011-0927-1.
• Adam Creuziger et al., “Crystallographic Texture Evolution in 1008 Steel Sheet during Multi-Axial Tensile Strain Paths,” Integrating Materials and Manufacturing Innovation 3, no. 1 (January 7, 2014): 1–19, https://doi.org/10.1186/2193-9772-3-1.
• Adam Creuziger et al., “Data Citation: Crystallographic Texture Evolution in 1008 Steel Sheet During Multi-Axial Tensile Strain Paths,” MatDL, December 30, 2013, https://materialsdata.nist.gov/handle/11115/231.
• Creuziger, Adam, and T. Foecke. “Transformation Potential Predictions for the Stress-Induced Austenite to Martensite Transformation in Steel.” Acta Materialia 58, no. 1 (January 2010): 85–91. https://doi.org/10.1016/j.actamat.2009.08.059.