6/6/22    16:30 - 18:30
Deep Learning Approaches for Applied Sciences and Engineering III  
Minisymposium organized by M. Giselle FernŠndez-Godino, Charles F. Jekel and Christian Gogu
Room: Jan Mayen 3
Chair: Charles F. Jekel
A PINN-based model for coupled hydro-poromechanics in reservoir simulations
Caterina Millevoi, NicolÚ Spiezia and Massimiliano Ferronato

CoSTA: Improving physics-based models using deep learning
Sindre S. Blakseth, Adil Rasheed, Trond Kvamsdal and Omer San

Physics-informed neural networks applied to two-phase flow in porous media problems
John Hanna, Jose V. Aguado, Sebastien Comas-Cardona, Ramzi Askri and Domenico Borzacchiello

Towards understanding of boiling conjugate heat transfer using physics informed neural network
Robin Kamenicky, Konstantinos Ritos, Victorita Dolean, Jennifer Pestana, Katherine Tant and Salaheddin Rahimi

Deep learning model operating on graph structured data for assisting multiphase flows
George El Haber, Jonathan Viquerat, Aurelien Larcher, David Ryckelynck and Elie Hachem

Physics inspired neural network plasticity modeling
Knut Andreas Meyer and Fredrik Ekre