Shashank Yellapantula
Shashank Yellapantula
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Modeling partially premixed combustion behavior in multiphase LES
E Knudsen, Shashank, H Pitsch
Combustion and Flame 162 (1), 159-180, 2015
Deep learning for presumed probability density function models
RWG Marc T. Henry de Frahan, Shashank Yellapantula, Ryan King, Marc S. Day
Combustion and Flame 208, 436-450, 2019
Adaptive mesh based combustion simulations of direct fuel injection effects in a supersonic cavity flame-holder
H Sitaraman, S Yellapantula, MTH de Frahan, B Perry, J Rood, R Grout, ...
Combustion and Flame 232, 111531, 2021
PeleC: An adaptive mesh refinement solver for compressible reacting flows
MT Henry de Frahan, JS Rood, MS Day, H Sitaraman, S Yellapantula, ...
The International Journal of High Performance Computing Applications 37 (2 …, 2023
A co-located incompressible Navier–Stokes solver with exact mass, momentum and kinetic energy conservation in the inviscid limit
Shashank, J Larsson, G Iaccarino
Journal of Computational Physics 229 (12), 4425-4430, 2010
Roadmap to advance heliostat technologies for concentrating solar-thermal power
G Zhu, C Augustine, R Mitchell, M Muller, P Kurup, A Zolan, ...
National Renewable Energy Lab.(NREL), Golden, CO (United States), 2022
Deep learning-based model for progress variable dissipation rate in turbulent premixed flames
S Yellapantula, BA Perry, RW Grout
Proceedings of the Combustion Institute 38 (2), 2929-2938, 2021
A comparison of classical and aggregation-based algebraic multigrid preconditioners for high-fidelity simulation of wind turbine incompressible flows
SJ Thomas, S Ananthan, S Yellapantula, JJ Hu, M Lawson, MA Sprague
SIAM Journal on Scientific Computing 41 (5), S196-S219, 2019
A numerical study of H2-air rotating detonation combustor
S Yellapantula, V Tangirala, K Singh, J Haynes
International Colloquium on the Dynamics of Explosions and Reactive Systems …, 2017
Machine learning of combustion LES models from reacting direct numerical simulation
S Yellapantula, MTH de Frahan, R King, M Day, R Grout
Data analysis for direct numerical simulations of turbulent combustion: from …, 2020
Wind farm response to mesoscale-driven coastal low level jets: a multiscale large eddy simulation study
T Chatterjee, J Li, S Yellapantula, B Jayaraman, E Quon
Journal of Physics: Conference Series 2265 (2), 022004, 2022
Towards multi-fidelity deep learning of wind turbine wakes
S Pawar, A Sharma, G Vijayakumar, CJ Bay, S Yellapantula, O San
Renewable Energy 200, 867-879, 2022
Co-optimized machine-learned manifold models for large eddy simulation of turbulent combustion
BA Perry, MTH de Frahan, S Yellapantula
Combustion and Flame 244, 112286, 2022
Deep reinforcement learning for dynamic control of fuel injection timing in multi-pulse compression ignition engines
MT Henry de Frahan, NT Wimer, S Yellapantula, RW Grout
International Journal of Engine Research 23 (9), 1503-1521, 2022
How equation of state selection impacts accuracy near the critical point: Forced convection supercritical CO2 flow over a cylinder
E Rasmussen, S Yellapantula, MJ Martin
The Journal of Supercritical Fluids 171, 105141, 2021
Enhancement of unsteady and 3D aerodynamics models using machine learning
G Vijayakumar, S Yellapantula, E Branlard, S Ananthan
Journal of Physics: Conference Series 1452 (1), 012065, 2020
Spray evaporation model sensitivities
Shashank, E Knuden, H Pitsch
Annual Research Briefs, Center for Turbulence Research 2011, 213-224, 2011
Visualizations of direct fuel injection effects in a supersonic cavity flameholder
H Sitaraman, N Brunhart-Lupo, MH de Frahan, S Yellapantula, B Perry, ...
Physical Review Fluids 6 (11), 110504, 2021
LES of spray and combustion in an internal combustion engine
D Kah, V MIttal, S Yellapantula, H Pitsch
Annual Research Briefs, Center for Turbulence Research 2012, 43-54, 2012
A DNN surrogate unsteady aerodynamic model for wind turbine loads calculations
S Ananthan, G Vijayakumar, S Yellapantula
Journal of Physics: Conference Series 1618 (5), 052060, 2020
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