A new efficient grain growth model using a random Gaussian-sampled mode filter

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics proces...

Full description

Bibliographic Details
Main Authors: Joseph Melville, Vishal Yadav, Lin Yang, Amanda R. Krause, Michael R. Tonks, Joel B. Harley
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Materials & Design
Subjects:
Grain growth
Microstructure
Mode filter
Anisotropy
Computational efficiency
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127523010201

Internet

http://www.sciencedirect.com/science/article/pii/S0264127523010201

Similar Items