Algorithm Development in Materials Science and Engineering: Models and Algorithms for Study Microstructures and Mechanical Properties of Materials
Sponsored by: TMS Materials Processing and Manufacturing Division, TMS: Computational Materials Science and Engineering Committee, TMS: Integrated Computational Materials Engineering Committee, TMS: Phase Transformations Committee, TMS: Solidification Committee
Program Organizers: Mohsen Asle Zaeem, Colorado School of Mines; Mikhail Mendelev, NASA ARC; Bryan Wong, University of California, Riverside; Ebrahim Asadi, University of Memphis; Garritt Tucker, Colorado School of Mines; Charudatta Phatak, Argonne National Laboratory; Bryce Meredig, Travertine Labs LLC

Wednesday 8:30 AM
March 17, 2021
Room: RM 36
Location: TMS2021 Virtual

Session Chair: Garritt Tucker, Colorado School of Mines


8:30 AM  
Mechanistic Modeling of Point Diffusion in Polycrystals to Capture Different Diffusion-deformation Mechanisms: Aritra Chakraborty1; Veerappan Prithivirajan1; Nathan Beets1; Arul Kumar Mariyappan1; Ricardo Lebensohn1; Laurent Capolungo1; 1Los Alamos National Laboratory
    Vacancy diffusion-mediated plasticity can dominate the creep response of metals at elevated homologous temperatures and moderate stresses. In practice, diffusional flow can occur either by Coble creep (grain boundary diffusion), Nabarro–Herring creep (lattice diffusion) or dislocation creep. While standard deformation-mechanism (Ashby) maps represent the dominant governing mechanism under a given condition of stress and temperature, all the aforementioned deformation mechanisms can simultaneously be activated. In this work, we propose an advanced mechanistic model to capture both grain boundary and bulk vacancy diffusion, coupled within a full-field crystal plasticity framework that accounts for the plastic deformation mediated by dislocation motion. Kinematic coupling occurs through the chemical strain tensor having dilatational and shear strain components. Using austenitic steel as an example, we demonstrate that the framework can capture both Coble creep and Nabarro–Herring creep mechanisms as a function of microstructure, and generate the partial Ashby maps, through the full-field simulations.

8:50 AM  Cancelled
Quantitative Phase-field Model for Void Nucleation and Growth Under Ion Irradiation: Sreekar Rayaprolu1; Anter El-Azab1; 1Purdue University
    Crystalline materials subjected to irradiation in nuclear reactors can develop voids. We use the phase-field model (PFM) to study the nucleation and growth of these voids. To verify the physical consistency and fix parameters in material constants, PFM is required to asymptotically match with their sharp interface counterparts in the limit of vanishing interface thickness. The asymptotic analysis of the PFM has resulted in a quantitative vacancy-based phase-field model; however, matching is yet to be performed with the sharp interface model when included interstitials along with vacancies. In this communication, we introduce a thermodynamically consistent, quantitative diffuse interface formulation of type C for void evolution under irradiation, which includes vacancy, interstitial, and phase-field variables as order parameters. Test cases are presented to validate our new phase-field model.

9:10 AM  
Low Dimensional Polynomial Chaos Expansion Performance at Assessing Uncertainty in Creep Life Prediction of Grade 91 Steel: Timothy Truster1; Amirfarzad Behnam1; Varun Gupta2; Ramakrishna Tipireddy2; 1University of Tennessee; 2Pacific Northwest National Laboratory
    This talk examines time to minimum creep rate and its uncertainty with respect to a set of fourteen material parameters. The time elapsed to minimum rate correlates greatly to overall creep lifespan of materials and hence is an important quantity of interest. The microstructural model of Grade 91 steel includes both dislocation creep and grain boundary opening/sliding within a finite element model, and hence the simulations are relatively expensive and have several sources of nonlinearity. We will propagate uncertainty in the input material parameters of these two mechanisms and determine the aggregate uncertainty in the predicted time to minimum creep rate as well as the sensitivities of the parameters upon this prediction. The cost, stability, accuracy of the polynomial chaos expansion as a means for stochastic dimensional reduction using basis adaptation method is assessed against the classical Monte Carlo method.

9:30 AM  
Full-field Stress Computation from Measured Deformation Fields: A Hyperbolic Formulation: Benjamin Cameron1; Cem Tasan1; 1Massachusetts Institute of Technology
    Recent developments in microscopic imaging techniques and correlation algorithms enable measurement of strain fields on a deforming material at high spatial and temporal resolution. In such cases, the computation of the stress field from the known deformation field becomes an interesting possibility. This is known as an inverse problem. Current approaches to this problem can provide approximate solutions, however accuracy is still a significant challenge. Here, we show how the inverse problem can be exactly solved in two or three dimensions for large classes of materials including isotropic elastic solids, Newtonian fluids, non-Newtonian fluids, granular materials, plastic solids subject to co-directionality, and other plastic solids. A system of linear hyperbolic partial differential equations is derived and validated demonstrating exact results (within numerical error). Furthermore, the approach can be used in a wide range of geometries and loading conditions giving rise to great practical utility.

9:50 AM  
A Simulation Survey of Recrystallization Behavior in Al-xSi Microstructures Under Shear Loading Conditions: William Frazier1; Bharat Gwalani1; Lei Li1; Ayoub Soulami1; Arun Devaraj1; Petr Sushko1; 1Pacific Northwest National Laboratory
    A coupling of Finite Element Method (FEM) and Kinetic Monte Carlo (KMC) models was devised in order to model the deformation, recrystallization, and grain growth response to the shear loading and annealing of Al-Si alloys. The coupling was demonstrated through comparison to data in the literature, and then applied to simulate the recrystallization of pure Al, Al-1Si, and Al-4Si between temperatures of 200 ºC and 400 ºC. Loading conditions of uniform shear and tribometric shear were considered. Experimental observation of recrystallization under tribometric loading conditions further validated the fidelity of our model predictions. This allowed us to predict the recrystallization nucleation behavior, recrystallization kinetics, and recrystallized grain structure of the deformed material as a function of temperature, loading, and Si composition. We propose this powerful capability is invaluable for modeling microstructural evolution in shear processing.

10:10 AM  
Predicting Mechanical Property Parameters from Load-displacement Curve of Nanoindentation Test by Using Machine Learning Model: Jin Myoung Jeon1; Jungwook Cho1; Kyojun Hwang1; 1GIFT, POSTECH
    Nanoindentation test is a method that can measure the mechanical properties of the local region by applying compressive force. This method is effective on measuring the material properties of the multi-phase material or film layer. In this study, an artificial neural network model was trained to extract a stress-strain curve from load-displacement curve of a nanoindentation experiment using finite element method simulation. Target parameters were four mechanical property parameters of Ludwik's equation and the performance of model has been improved through strain distribution and load-displacement curve analysis. The performance of the artificial neural network model was verified with nanoindentation experiments on 304L stainless steel.