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Balasubramaniam Radhakrishnan

Contact

RADHAKRISHNB@ORNL.GOV

Publications

August 2024

GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure

Journal: Journal of Computational Physics
February 2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Journal: Journal of Materials Science
December 2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations...

Conference Paper
April 2023

Development of HPC based phase field simulations tool for modification of alloy morphology to…

ORNL Report
February 2023

GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution…

Journal: Computational Materials Science

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Organizations

Computing and Computational Sciences Directorate
Computational Sciences and Engineering Division
Advanced Computing Methods for Physical Sciences Section
Multiscale Materials Group

Related News

News

Summit helps forge stronger flights

Research Highlight

GrainNN: A Neighbor-aware Long Short-term Memory Network for Predicting Microstructure Evolution During Polycrystalline Grain Formation

Research Highlight

MEUMAPPS C++: A Scalable, Performance-Portable, Open-Source Framework for Phase-Field Modeling

Research Highlight

Dendrite-resolved, full-melt-pool phase-field simulations to reveal non-steady-state effects and to test an approximate model
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