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Meeting MS&T24: Materials Science & Technology
Symposium Integrated Computational Materials Engineering for Physics-Based Machine Learning Models
Presentation Title PRISMS-MultiPhysics: An Open-Source Coupled Phase Field-Crystal Plasticity Framework and its Application to Simulate Twinning in Magnesium Alloys
Author(s) David Montiel, Chaitali Patil, Mohammadreza Yaghoobi, Brian Puchala, Anton Van der Ven, Katsuyo Thornton, Veera Sundararaghavan, John Allison
On-Site Speaker (Planned) David Montiel
Abstract Scope Twinning is one of the main deformation mechanisms in Magnesium alloys, resulting in strongly anisotropic strength and poor formability. Therefore, a fundamental understanding of the formation and propagation mechanisms of twins is needed for the design of Mg alloys with improved mechanical properties. We discuss the development of a multi-scale framework to model the nucleation, propagation, and growth of twins. This framework (PRISMS-MP) features concurrent integration of phase-field and crystal plasticity models to describe the evolution of twins while considering the effects of elastic and plastic deformation. We demonstrate the application of the model to simulate the evolution of twins in Mg. In addition, we discuss integration with the PRISMS Cluster Approach to Statistical Mechanics (CASM) framework to obtain twin boundary energies and mobilities required to parameterize the coupled model. Finally, we discuss plans to employ the framework to investigate the effects of different solutes on twinning in Mg alloys.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Multiscale Simulation Investigation of Cavity Evolution in a Ni TPBAR Coating
Advanced Coupling of an FFT-Based Mesoscale Modeling Method to a Macroscale Finite Element Method
B-1: Statistically Equivalent Virtual Microstructures for Modeling of Complex Polycrystalline Alloys Using a Generative Adversarial Network (GAN)-Enabled Computational Platform
Deep Generative Model for Reproducing Microstructure of Low-Carbon Steel During Continuous Cooling
Deep Learning for Early Detection and Localization of Damage in Metal Plates
Developing Data-Driven Strength Models Incorporating Temperature and Strain-Rate Dependence
Hybrid Machine Learning Informed Design Guidelines for Structural Gradient Alloys with Enhanced Performances
Phase-Field Modeling of Grain Evolution and Recrystallization in Friction Stir Processing
PRISMS-MultiPhysics: An Open-Source Coupled Phase Field-Crystal Plasticity Framework and its Application to Simulate Twinning in Magnesium Alloys
Thermodynamic Integration for Dynamically Unstable Systems Using Interatomic Force Constants without Molecular Dynamics
Utilizing Convex Neural Networks to Predict the Yield Surfaces of Polycrystalline Samples with Complex Crystallographic Textures

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