Articles with public access mandates - Rishikesh RanadeLearn more
Available somewhere: 7
Algorithmically-consistent deep learning frameworks for structural topology optimization
J Rade, A Balu, E Herron, J Pathak, R Ranade, S Sarkar, A Krishnamurthy
Engineering Applications of Artificial Intelligence 106, 104483, 2021
Mandates: US National Science Foundation
A hybrid iterative numerical transferable solver (hints) for pdes based on deep operator network and relaxation methods
E Zhang, A Kahana, E Turkel, R Ranade, J Pathak, GE Karniadakis
arXiv preprint arXiv:2208.13273, 198, 2022
Mandates: US Department of Energy, Swiss National Science Foundation, US Department of …
Investigation of deep learning methods for efficient high-fidelity simulations in turbulent combustion
KM Gitushi, R Ranade, T Echekki
Combustion and Flame 236, 111814, 2022
Mandates: US National Science Foundation
Experiment-based modeling of turbulent flames with inhomogeneous inlets
R Ranade, T Echekki, AR Masri
Flow, Turbulence and Combustion, 1-25, 2022
Mandates: US National Science Foundation, Australian Research Council
Physics-informed neural networks for turbulent combustion: Toward extracting more statistics and closure from point multiscalar measurements
A Taassob, R Ranade, T Echekki
Energy & Fuels 37 (22), 17484-17498, 2023
Mandates: US National Science Foundation
Turbulent Combustion Closure via Physic-Informed Neural Networks and Multiscalar Measurements
A Taassoba, R Ranadeb, T Echekkia
Conference: 13th National Meeting of the Combustion Institute, College …, 2023
Mandates: US National Science Foundation
Deep Learning of Joint Scalar PDFs in Turbulent Flames from Sparse Multiscalar Data
R Ranade, KM Gitushi, T Echekki
Combustion Science and Technology, 1-22, 2023
Mandates: US National Science Foundation
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