Arvind T. Mohan
Citado por
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A deep learning based approach to reduced order modeling for turbulent flow control using LSTM neural networks
AT Mohan, DV Gaitonde
arXiv preprint arXiv:1804.09269, 2018
Compressed convolutional LSTM: An efficient deep learning framework to model high fidelity 3D turbulence
A Mohan, D Daniel, M Chertkov, D Livescu
arXiv preprint arXiv:1903.00033, 2019
Time-series learning of latent-space dynamics for reduced-order model closure
R Maulik, A Mohan, B Lusch, S Madireddy, P Balaprakash, D Livescu
Physica D: Nonlinear Phenomena 405, 132368, 2020
Model reduction and analysis of deep dynamic stall on a plunging airfoil
AT Mohan, DV Gaitonde, MR Visbal
Computers & Fluids 129 (28 April 2016), 1–19, 2016
From deep to physics-informed learning of turbulence: Diagnostics
R King, O Hennigh, A Mohan, M Chertkov
arXiv preprint arXiv:1810.07785, 2018
Embedding hard physical constraints in neural network coarse-graining of 3d turbulence
AT Mohan, N Lubbers, D Livescu, M Chertkov
arXiv preprint arXiv:2002.00021, 2020
Analysis of airfoil stall control using dynamic mode decomposition
AT Mohan, DV Gaitonde
Journal of Aircraft 54 (4), 1508-1520, 2017
Model reduction and analysis of deep dynamic stall on a plunging airfoil using dynamic mode decomposition
AT Mohan, MR Visbal, DV Gaitonde
53rd AIAA Aerospace Sciences Meeting, 1058, 2015
Spatio-temporal deep learning models of 3D turbulence with physics informed diagnostics
AT Mohan, D Tretiak, M Chertkov, D Livescu
Journal of Turbulence 21 (9-10), 484-524, 2020
Constraining fission yields using machine learning
A Lovell, A Mohan, P Talou, M Chertkov
EPJ Web of Conferences 211, 04006, 2019
Statistical Analysis and Model Reduction of Surface Pressure for Interaction of a Streamwise-Oriented Vortex with a Wing
AT Mohan, L Agostini, DV Gaitonde, DJ Garmann
22nd AIAA Computational Fluid Dynamics Conference, 3412, 2015
Quantifying uncertainties on fission fragment mass yields with mixture density networks
AE Lovell, AT Mohan, P Talou
Journal of Physics G: Nuclear and Particle Physics 47 (11), 114001, 2020
Wavelet-powered neural networks for turbulence
AT Mohan, D Livescu, M Chertkov
ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020
A Preliminary Spectral Decomposition and Scale Separation Analysis of a High-Fidelity Dynamic Stall Dataset
AT Mohan, LM Agostini, MR Visbal, DV Gaitonde
54th AIAA Aerospace Sciences Meeting, 1352, 2016
Model Reduction and Analysis of NS-DBD Based Control of Stalled NACA0015 Airfoil
AT Mohan, DV Gaitonde
ASME 2014 4th Joint US-European Fluids Engineering Division Summer Meeting …, 2014
Multiscale Reduced Order Modeling and Parameter Estimation for Climate Sciences
A Mohan
AI4ESP, 2021
Rapid Spatiotemporal Turbulence Modeling with Convolutional Neural ODEs
V Shankar, G Portwood, A Mohan, P Mitra, V Viswanathan, D Schmidt
Bulletin of the American Physical Society, 2020
Learning Physics-based Galerkin models of turbulence with Neural Differential Equations
A Mohan, K Nagarajan, D Livescu
Bulletin of the American Physical Society, 2020
Physics-Constrained Convolutional LSTM Neural Networks for Generative Modeling of Turbulence
A Mohan, D Livescu, M Chertkov
APS Division of Fluid Dynamics Meeting Abstracts, C17. 002, 2019
Spatio-temporal modeling of high-fidelity turbulence with convolutional long short-term memory neural networks
A Mohan, M Chertkov, D Livescu
Bulletin of the American Physical Society 63, 2018
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