Peetak P. Mitra
Peetak P. Mitra
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Turbulence forecasting via Neural ODE
GD Portwood, PP Mitra, MD Ribeiro, TM Nguyen, BT Nadiga, JA Saenz, ...
arXiv preprint arXiv:1911.05180, 2019
162019
Spatio-temporal patterns in fMRI data revealed by principal component analysis and subsequent low pass filtering
PP Mitra, DJ Thompson, S Ogawa, X Hu, K Ugurbil
Proceedings of the International Society for Magnetic Resonance in Medicine, 817, 1995
121995
A distributed fuzzy logic based n-body collision avoidance system
P Srivastava, S Satish, P Mitra
Proc of the 4th Int Symposium on Intelligent Robotic Systems, Bangalore, 166-172, 1998
81998
Identification and characterization of steady spray conditions in convergent, single-hole diesel injectors
P Mitra, K Matusik, D Duke, P Srivastava, K Yasutomi, J Manin, L Pickett, ...
SAE Technical Paper, 2019
62019
A comparison between CFD and 3D X-ray Diagnostics of Internal Flow in a Cavitating Diesel Injector Nozzle
A Tekawade, P Mitra, BA Sforzo, KE Matusik, AL Kastengren, DP Schmidt, ...
52019
A data-driven approach to modeling turbulent decay at non-asymptotic reynolds numbers
MD Ribeiro, GD Portwood, P Mitra, TM Nyugen, BT Nadiga, M Chertkov, ...
Bulletin of the American Physical Society, 2019
32019
A data-driven approach to modeling turbulent flows in an engine environment
P Mitra, M Dias Ribeiro, D Schmidt
APS Division of Fluid Dynamics Meeting Abstracts, G16. 003, 2019
32019
Propagation of Surface-to-Low Earth Orbit Vortex Rings for Orbital Debris Management
MA Noyes, P Mitra, A Dicholkar
Safety is Not an Option, Proceedings of the 6th IAASS Conference 715, 11, 2013
32013
Towards building robust neural network models for fluid simulations
P Mitra, M Haghshenas, N Dal Santo, C Daly, S Mitra, D Schmidt
Bulletin of the American Physical Society, 2020
22020
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
12020
LES Turbulence Model with Learnt Closure; Integration of DNN into a CFD Solver
M Haghshenas, P Mitra, N Dal Santo, M Dias Ribeiro, S Mitra, D Schmidt
Bulletin of the American Physical Society, 2020
12020
Learning non-linear spatio-temporal dynamics with convolutional Neural ODEs
V Shankar, GD Portwood, AT Mohan, P Mitra, C Rackauckas, L Wilson, ...
Neural Information Processing Systems Workshop, 2020
1*2020
Cfd simulations of a two-phase ejector for transcritical CO2 cycles applied to supermarket refrigeration systems
A Colombo, P Conti, M Orlandi, F Visconti, P Mitra, DP Schmidt
13th IIR Gustav Lorentzen Conference on Natural Refrigerants: Natural …, 2018
12018
Propagation of Surface-to-LEO Vortex Rings For Orbital Debris Management
MA Noyes
5th AIAA Atmospheric and Space Environments Conference, 2682, 2013
12013
Network compression for machine-learnt fluid simulations
P Mitra, V Venkatesan, N Jangid, A Nambiar, D Kumar, ND Santo, ...
Network compression workshop at ICLR 2021, 2021
2021
Improved Methods for Mixing-Limited Spray Modeling
M Haghshenas, P Mitra, C Wang, F Tagliante, L Pickett, D Schmidt
ILASS Americas, 2021
2021
Eulerian Lagrangian Mixing Oriented (ELMO) Model
DP Schmidt, M Haghshenas, P Mitra, C Wang, F Tagliante, PK Senecal, ...
International Journal of Multiphase Flow, 2021
2021
Analysis and Interpretation of data-driven closure models for Large Eddy Simulation of Internal Combustion Engines
P Mitra, M Haghshenas, N Dal Santo, M Dias Ribeiro, S Mitra, C Daly, ...
SAE World Congress Experience, 2021
2021
On the Effectiveness of Bayesian AutoML methods for Physics Emulators
P Mitra, N Dal Santo, M Haghshenas, S Mitra, C Daly, DP Schmidt
Preprints, 2020
2020
A comprehensive review of spray modeling strategies
P Mitra
2020
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Artículos 1–20