grain-growth

These matlab codes simulate grain growth by solving the phase field equations using a centered finite difference method

PINNs-MPF is a comprehensive framework designed for simulating interface dynamics using Physics-Informed Neural Networks (PINNs). Leveraging machine learning techniques, this framework offers an efficient implementation for the multi-phase-field model

Optimising microstructures numerically (OMicroN). Full field physics-based simulation package for metallic microstructure during treatments. The package includes solid state transformations (phase transformations, recrystallization, grain growth) as well as solute redistribution (carbon partitioning / diffusion / trapping to defects).

The repository for the Physics-Regulated Interpretable Machine Learning Microstructure Evolution (PRIMME) framework for learning and emulating microstructure grain growth.

App for the visualization of grain growth using Cellular Automata, Monte carlo and MC static recrystallization algorithms

PINN-Phase: a physics-informed neural time integrator for curvature-driven multiphase-field evolution, built for long-horizon rollouts, transfer across unseen microstructures (2D&3D), and extension to new simulation settings. A reusable complement to traditional phase-field solvers for repeated studies, benchmarking, and collaborative development.

Cellular Automaton projects for Multiscale Modeling classes. So far, it includes Elementary CA (1D), Game of Life (2D) and Grain Growth CA (2D).

Grain growth simulation with cellural automaton.

RPI CSCI-6360 Parallel Programming & Computing group project

This repository demonstrates how to run MICRESS simulations using the pyiron workflow management framework, with a benchmark example of early-stage microstructure growth from the liquid state.

Interactive numerical simulation portfolio featuring a tested 2D Monte Carlo Potts grain-growth model.

code for mode filter with different kernel

Code, data, and figures for equal-exposure processing-order effects in conserved morphology and grain networks.

A spin-off code of the 'Voronoi PCC Analyser' software project. Created as a simulation tool for nucleation-and-growth (NAG) structure evolution processes based on the discrete combinatorial representation of 2D and 3D polycrystalline materials.

This repository provides an exemplary workflow for the SimStack workflow management system, demonstrating how to combine multiple Workflow Active Nodes (WaNos) for a streamlined and powerful simulation and visualization pipeline using MICRESS and MicPy.

Is there a threshold 2D simulation size below which the effects of changing driving forces gets lost in the noise?

PRIMME