Kevin Griffin is a postdoctoral researcher in NREL's Computational Science Center. He works on goal-driven automatic model training and data-driven models for turbulent flows. 

For additional information, see Kevin Griffin’s LinkedIn profile.

Disclaimer: Any opinions expressed on LinkedIn are the author’s own, made in the author's individual capacity, and do not necessarily reflect the views of NREL.

Research Interests

Computational fluid dynamics

Multi-fidelity and data-driven modeling

Turbulence modeling and simulation

Education

Ph.D., Mechanical Engineering, Stanford University

M.S., Mechanical Engineering, Stanford University

B.S.E., Mechanical and Aerospace Engineering, Princeton University

Professional Experience

Academic Service

Co-Editor, Proceedings of the 2022 Summer Program, Stanford Engineering | Center for Turbulence Research (2022)

Member, Stanford Mechanical Engineering Graduate Student Committee (2018–2022)

President, See Mechanical Engineering Outreach (2018–2022)

Teaching

Principle Instructor, ME 492 Mechanical Engineering Teaching Assistance Training, Stanford University  (2021–2022)

Teaching Assistant, ME 361 Turbulence, Stanford University (2019)

Leadership in Inclusive Teaching Fellow, Stanford University (2021–2022)

Internships

Cascade Technologies, Inc. (2016)

Max Planck Institute for Dynamics and Self-Organization (2015)

Princeton Plasma Physics Laboratory, U.S. Department of Energy (2014)

Associations and Memberships

Member, American Physical Society

Member, Tau Beta Pi National Engineering Honor Society

Member, Sigma Xi National Research Honor Society

Featured Work

Near-Wall Model for High-Speed Turbulent Boundary Layers Based on an Inverse Velocity Transformation, Journal of Fluid Mechanics (2023) 
 
A Universal Velocity Transformation for Boundary Layers With Pressure Gradients, Center for Turbulence Research Proceedings of the Summer Program (2022) 

Non-Boussinesq Subgrid-Scale Model with Dynamic Tensorial Coefficients, Physical Review Fluids (2022)

Current State and Future Trends in Boundary Layer Control on Lifting Surfaces, Advances in Mechanical Engineering (2022)

Compressible Velocity Transformations for Various Non-Canonical Wall-Bounded Flows, AIAA Journal (2022)

Velocity Transformation for Compressible Wall-Bounded Turbulent Flows With and Without Heat Transfer, Proceedings of the National Academy of Sciences (2021)

General Method for Determining the Boundary Layer Thickness in Nonequilibrium Flows, Physical Review Fluids (2021)

Grid-Point and Time-Step Requirements for Direct Numerical Simulation and Large-Eddy Simulation, Physics of Fluids (2021)

Correlated Forcing with an Active Grid, Experiments in Fluids (2019)

Near-Wall Model for Large-Eddy Simulation That Incorporates Resolved Non-Equilibrium and Reynolds-Number Effects, 12th International Symposium on Turbulence and Shear Flow Phenomena (2022)

Awards and Honors

Gerald J. Lieberman Fellowship (2022)

National Defense Science and Engineering Graduate Fellowship (2017–2021)

Stanford Graduate Fellowship (2017–2022)

National Science Foundation Graduate Research Fellowship Honorable Mention (2017)

1st Place Donald Janssen Dike Award for Excellence in Undergraduate Research, Princeton University (2017)