Arvind T. Mohan
Tytuł
Cytowane przez
Cytowane przez
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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
752018
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
382019
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
312020
From deep to physics-informed learning of turbulence: Diagnostics
R King, O Hennigh, A Mohan, M Chertkov
arXiv preprint arXiv:1810.07785, 2018
312018
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
272016
Analysis of airfoil stall control using dynamic mode decomposition
AT Mohan, DV Gaitonde
Journal of Aircraft 54 (4), 1508-1520, 2017
182017
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
15*2020
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
132015
Constraining Fission Yields Using Machine Learning
A Lovell, A Mohan, P Talou, M Chertkov
EPJ Web of Conferences 211, 04006, 2019
32019
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
32015
Spatio-temporal deep learning models of 3D turbulence with physics informed diagnostics
AT Mohan, D Tretiak, M Chertkov, D Livescu
Journal of Turbulence, 1-41, 2020
12020
Physics-Constrained Convolutional LSTM Neural Networks for Generative Modeling of Turbulence
A Mohan, D Livescu, M Chertkov
APS, C17. 002, 2019
12019
Wavelet-Powered Neural Networks for Turbulence
AT Mohan, D Livescu, M Chertkov
Second Workshop on Machine Learning and the Physical Sciences, NeurIPS, 2019
12019
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
12018
A Statistical Insight into the Onset of Deep Dynamic Stall using Multivariate Empirical Mode Decomposition
AT Mohan, LM Agostini
2018 AIAA Aerospace Sciences Meeting, 1053, 2018
12018
Data-Driven Analysis Methodologies for Unsteady Aerodynamics from High Fidelity Simulations
AT Mohan
The Ohio State University, 2017
12017
Analysis of non-stationary turbulent flows using Multivariate EMD and Matching Pursuits
A Mohan, L Agostini, D Gaitonde, MI Visbal
APS, A35. 007, 2016
12016
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
12016
Model Reduction and Analysis of NS-DBD Based Control of Stalled NACA0015 Airfoil
AT Mohan, DV Gaitonde
Fluids Engineering Division Summer Meeting 46216, V01AT09A001, 2014
12014
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
2020
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