Advanced Characterization Techniques for Quantifying and Modeling Deformation: Session V
Sponsored by: TMS Extraction and Processing Division, TMS Structural Materials Division, TMS: Advanced Characterization, Testing, and Simulation Committee, TMS: Materials Characterization Committee
Program Organizers: Mariyappan Arul Kumar, Los Alamos National Laboratory; Irene Beyerlein, University of California, Santa Barbara; Wolfgang Pantleon, Technical University of Denmark; C. Tasan, Massachusetts Institute of Technology; Olivia Underwood Jackson, Sandia National Laboratories
Wednesday 8:30 AM
March 2, 2022
Location: Anaheim Convention Center
Session Chair: Donovan Leonard, Oak Ridge National Laboratory; Martin Diehl, KU Leuven
8:30 AM Invited
Full Field Crystal Plasticity Simulations of Measured Microstructures: Going 3D: Martin Diehl1; Nikhil Prabhu1; 1KU Leuven
Full field crystal plasticity simulations of measured microstructures have been routinely employed in the last years. However, typically these microstructures have been obtained using Electron Backscatter Diffraction (EBSD), i.e. the simulations are limited to two dimensions. Unfortunately, the stress and strain partitioning predicted by two dimensional simulations differs significantly from the realistic three dimensional case. A common approach to overcome the limitations of two dimensional simulation is the creation of artificial microstructure based on the statistical properties obtained from surface measurements. While this approach is very suitable for studying statistical properties, it does not allow to perform one to one comparison to experimental measurements which are especially helpful for investigating the predictive capabilities of the chosen constitutive model. Here, we present full field simulation of microstructures obtained from 3D synchrotron characterization. The comparison between experimental and simulated results is used to discuss the limitations of the employed crystal plasticity model
Identification of Crystal Plasticity Model Parameters by Multi-objective Optimization Integrating Texture Evolution: Daniel Savage1; Marko Knezevic2; Zhangxi Feng2; 1Los Alamos National Laboratory; 2University of New Hampshire
Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. A set of model parameters are typically calibrated through the fitting of mechanical data such as stress–strain curves and lattice strains. Whereas, microstructural data such as texture evolution or twin fractions are used for verifying slip and twin activities are reasonable. In this work, we use a multi-objective genetic algorithm to identify crystal plasticity hardening parameters and incorporate texture into the optimization. The utility of the developed methodology is demonstrated through two case studies: 1) A series of textures from plane-strain compression of Nb is used to recover a dislocation hardening law; representing one of the first applications in which texture alone has been used to recover model parameters. 2) A large Ti texture and stress-strain dataset is demonstrated to constrain per mode Hall-Petch and hierarchical twin contributions in a complex dislocation hardening law.
9:20 AM Invited
Centimeter to Nanometer Materials Characterization Informed Phase Field Modeling of Mechanical Failure in 6022/EK100 Linear Friction Stir Welds: Donovan Leonard1; Kubra Karayagiz2; Adam Powell2; Brajendra Mishra2; Qingli Ding2; Piyush Upadhyay3; Tim Skszek4; 1Oak Ridge National Laboratory; 2WPI; 3PNNL; 4Magna International Inc.
Phase field modeling, of a linear friction stir weld (FSW) between 1.27mm 6022 Al and 1.5mm EK100 Mg sheet, was being used to understand the effects of corrosion on a joint’s lap shear strength. The mechanical deformation model predicted a 150 N/mm joint strength, higher than the measured joint strength at 110-120 N/mm. Model refinement and validation is being aided through advanced materials characterization that reported evolution of 2nd phase nanostructures (Mg2Si), intermetallic growth, elemental segregation and grain size refinement. Xray CT, EBSD, SANS, transmission Kikuchi diffraction (TKD) and STEM/EDS were also combined to determine changes in grain size and 2nd particle morphology. A complex mixing of metals within the FSW, leaving ribbons of ~100nm thick Al30Mg23 and Al12Mg17 layers were discovered through correlation of TKD/EDS with nanoindentation measurements. This work was supported by the Vehicle Technologies Office, U.S. Department of Energy, Award DE-EE0008454.
9:50 AM Break
A Thermo-elasto-viscoplastic Finite Element Model to Study Polycrystalline Evolution during Metal AM: Nikhil Mohanan1; Jérémy Bleyer2; Thomas Helfer3; Manas Upadhyay1; 1LMS, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris; 2Navier Laboratory, CNRS, École des Ponts ParisTech; 3DEC, CEA
During Additive Manufacturing (AM) of metals, the material undergoes rapid solidification just after deposition. Then, until the end of the AM process, it is subjected to Solid-State Thermal Cycling (SSTC). It is important to study the role of SSTC on microstructure evolution during AM because microstructural features determining the material response such as texture, internal strains, etc., are affected by it. Recently, the group of Manas Upadhyay developed (i) a miniature laser metal deposition machine for synchrotron XRD experiments, and (ii) a laser-integrated SEM system, to characterize the SSTC-induced microstructural changes.To complement these experimental techniques, we propose a Thermal Elasto-ViscoPlastic Finite Element (T-EVP-FE) polycrystalline model that can (i) simulate the local and macroscopic response of a material subjected to strong thermal gradients and (ii) act as a basis for future couplings/extensions to model recrystallization, grain growth, damage, fracture, etc. A preliminary comparison with aforementioned experiments is presented.
Meso-scale Characterization and Strain-gradient Enabled Simulation of the Multi-strain Path Deformation of AA6016-T4: Rishabh Sharma1; Md Zahidul Sarkar2; Dane Sargeant1; Marko Kenezevic2; Michael Miles3; David Fullwood3; 1Brigham Young University Student; 2University of New Hampshire; 3Brigham Young University
During forming operations, heterogeneous microstructures and complex strain paths lead to local strain gradients and associated backstress resulting from geometrically necessary dislocations (GNDs). At the macro scale, this contributes to springback and Bauschinger effects that must be accounted for in the process design. Accurate incorporation of the effect of the local strain gradients facilitates a better design of forming operations. The current paper reports on a combined mesoscale experimental/simulation study of strain gradient effects during multi-strain path deformation of AA6016-T4. The novel strain gradient elasto-plastic self-consistent (SG-EPSC) model builds on the recently formulated backstress-enabled EPSC. Development of GNDs and related backstresses and hardening at subgrain level will be measured using high-resolution electron backscatter diffraction and high-resolution digital image correlation techniques. A 3D representative volume element for the model will be generated via incremental ion-milling and scanning. The performance of the model at the macro and mesoscale will be experimentally determined.
Modeling and Experimental Characterization of Intragranular Residual Stresses, Statistically Stored and Geometrically Necessary Dislocations: Ritwik Bandyopadhyay1; Sven Gustafson1; Hemant Sharma2; Peter Kenesei2; Michael Sangid1; 1Purdue University; 2Argonne National Laboratory
Residual stress, defined as long-range internal stress inside a solid in the absence of externally applied load, is present in all engineering materials. In crystalline solids, such stress primarily exists due to defects (e.g., point defects, dislocations and dislocation structures, precipitates, grain boundaries) and can influence the performance of structural components. However, there are limited methods to initialize intragranular residual stress and dislocation densities in crystal plasticity models. This research lays out a mathematical framework to compute statistically stored and geometrically necessary dislocations and their contributions to intragranular residual stress. We test the efficacy of the framework using near-field and far-field high-energy x-ray microscopy experimental data for Ti-7Al. Good agreement between model prediction and experimental observations adds trust to our formulation. The proposed framework offers a path to better characterize structure-performance relationships in designing materials using an integrated computational materials engineering (ICME) approach.