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Photo of Shashank Yellapantula

Shashank Yellapantula

Researcher IV-Mechanical Engineering


303-275-4806

Dr. Shashank Yellapantula is a staff scientist in the High Performance Algorithms and Complex Fluids Group in the Computational Science Center where he leads development of exascale application software in wind energy and combustion. He is also actively involved in using Machine Learning techniques to improve and augment simulation based models for industrially relevant flow physics problems.

Research Interests

Combustion modeling

Design of industrial combustion technology

Turbulence modeling, atmospheric boundary layers

Machine learning-based augmentation of simulation models

Education

Ph.D., Mechanical Engineering, Stanford University

M.S., Mechanical Engineering, Stanford University

B. Tech., Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology

Professional Experience

Senior Scientist, NREL (2020–present)

Scientist, NREL (2017–2020)

Lead Research Engineer, GE Global Research (2016–2017)

Research Engineer, GE Global Research (2013–2016)

Associations and Memberships

Member, Gas Turbine Engineering Technical Committee (GTETC) American Institute of Aeronautics and Astronautics (AIAA)

Board member, Western States Section of the Combustion Institute (WSSCI) 

Featured Work

Deep Learning-Based Model for Progress Variable Dissipation Rate in Turbulent Premixed Flames, Proceedings of the Combustion Institute, (2020)

A DNN Surrogate Unsteady Aerodynamic Model for Wind Turbine Loads Calculations, Journal of Physics: Conference Series (2020)

Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation, Book Chapter in Data Analysis for Direct Numerical Simulations of Turbulent Combustion (2020)

Deep Learning for Presumed Probability Density Function Models, Combustion and Flame (2019)

A Comparison of Classical and Aggregation-Based Algebraic Multigrid Preconditioners for High-Fidelity Simulation of Wind Turbine Incompressible Flows, SIAM Journal on Scientific Computing (2020)

Patents

Combustors and methods of assembling the same, U.S. Patent No. 10,724,741 (2020)

Turbine engine assembly including a rotating detonation combustor, U.S. Patent No. 15/705,954 (2019)

Turbine engine fuel injection system and methods of assembling the same, U.S. Patent No. 9,803,552 (2017)