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Efficient Surrogate Models for Materials Science Simulations: Machine
  Learning-based Prediction of Microstructure Properties

Efficient Surrogate Models for Materials Science Simulations: Machine Learning-based Prediction of Microstructure Properties

1 September 2023
Binh Duong Nguyen
Pavlo Potapenko
Aytekin Dermici
Kishan Govind
Sébastien Bompas
Stefan Sandfeld
    AI4CE
ArXivPDFHTML

Papers citing "Efficient Surrogate Models for Materials Science Simulations: Machine Learning-based Prediction of Microstructure Properties"

1 / 1 papers shown
Title
Extreme time extrapolation capabilities and thermodynamic consistency of
  physics-inspired Neural Networks for the 3D microstructure evolution of
  materials
Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired Neural Networks for the 3D microstructure evolution of materials
Daniel Lanzoni
Andrea Fantasia
R. Bergamaschini
Olivier Pierre-Louis
F. Montalenti
AI4CE
29
0
0
29 Jul 2024
1