About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithms Development in Materials Science and Engineering
|
Presentation Title |
Surrogate Models for Accelerating CALPHAD-Informed Materials Simulations in MOOSE |
Author(s) |
Parikshit Bajpai, Daniel Schwen |
On-Site Speaker (Planned) |
Parikshit Bajpai |
Abstract Scope |
Understanding thermodynamic properties and resulting phase equilibria is crucial for simulating material microstructure, property evolution, and behavior. Thermodynamic and kinetic information derived from CALPHAD databases have been used to inform various process and material models and the coupling of CALPHAD calculations with multiphysics simulation tools such as the Multiphysics Object Oriented Simulation Environment (MOOSE) is becoming increasingly popular. However, due to the high cost of direct coupling of CALPHAD-based Gibbs energy minimization, the applications of this approach have been limited to relatively small systems. To accelerate the direct coupling of CALPHAD calculations with MOOSE-based codes, a thermochemistry surrogate modeling framework is being developed. This work will demonstrate an on-the-fly surrogate modeling capability developed for the MOOSE framework and explore its applications to phase field and engineering scale simulations of nuclear materials and reactors. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Modeling and Simulation, Nuclear Materials |