Jack Edwards

Angel Family Professor, Assoc. Dept. Head, Dir. of Undergraduate. Programs

  • 919-515-5264
  • Engineering Building III (EB3) 3234

Dr. Edwards’ long-term goal is to develop efficient and accurate computational fluid dynamics (CFD) techniques for conducting large scale simulations of complex flows for important engineering problems.

At the graduate level, Dr. Edwards teaches Computation of Reacting Flows (MAE 770). This course is concerned with the general principles for formulating and solving the governing equations of reactive flows and multi-phase flows. He treats a wide range of problems in this course ranging from those in the atmospheric sciences to water flow in home faucets.

At the undergraduate level, he teaches Aerodynamics II (MAE 356) and Computational Aerodynamics (MAE 456). In Aerodynamics II, Dr. Edwards places a strong emphasis on developing good practices in computer coding. In his Computational Aerodynamics course, he brings in examples that he has encountered in his own work pertaining to the physics of high-speed flows. The students who work with Dr. Edwards are drawn to his area of research because of the versatility of the CFD tool in all areas of engineering leading to work opportunities in government/industry labs. His students tend to have strong skills in communication, math, and computer programming.

Outside of work, Dr. Edwards enjoys spending time with his family, playing guitar, and ice hockey (as a spectator).

Education

Ph.D. 1993

Aerospace Engineering

North Carolina State University

M.S. 1990

Aerospace Engineering

North Carolina State University

B.S. 1988

Aerospace Engineering

North Carolina State University

Research Description

Dr. Edwards is interested in computational fluid dynamics (CFD), 2D and 3D compressible flows, reactive and multi-phase flows, and turbulence modeling. Dr. Edwards is currently 1) developing large eddy simulation techniques for high speed internal flows in advanced engine concepts (ram jets, scram jets, etc.), 2) conducting simulations of entry/exit into collective protection systems designed to enable operation in contaminated environments, and 3) developing multi-phase flow simulation methods as applied to industrial/medical processes. He is Principal Investigator of the Aerospace Engineering Computational Fluid Dynamics Laboratory. In MAE, he collaborates with Dr. Dow, Dr. Eischen, Dr. Hassan, Dr. Luo, Dr. Fang, and Dr. Gopalarathnam.

Publications

Least Squares Minimization Closure Models for LES of Turbulent Combustion
Patton, C. H., & Edwards, J. R. (2019), FLOW TURBULENCE AND COMBUSTION, 102(3), 699–733. https://doi.org/10.1007/s10494-018-9968-5
Low-Order Model for Prediction of Trailing-Edge Separation in Unsteady Flow
Narsipur, S., Gopalarathnam, A., & Edwards, J. R. (2019), AIAA JOURNAL, 57(1), 191–207. https://doi.org/10.2514/1.J057132
Numerical Simulation of Two-Phase Flow Within Aerated-Liquid Injectors
Bornhoft, B. J., Edwards, J. R., & Lin, K.-C. (2019), JOURNAL OF PROPULSION AND POWER, 35(6), 1034–1047. https://doi.org/10.2514/1.B37284
Reflections on the early development of the "AUSM family" of Riemann solvers
Edwards, J. R. (2019, July), SHOCK WAVES. https://doi.org/10.1007/s00193-018-0863-8
Vortex-Sheet Representation of Leading-Edge Vortex Shedding from Finite Wings
Hirato, Y., Shen, M., Gopalarathnam, A., & Edwards, J. R. (2019), JOURNAL OF AIRCRAFT, 56(4), 1626–1640. https://doi.org/10.2514/1.C035124
Development of a premixed combustion capability for dual-mode scramjet experiments
Rockwell, R. D., Goyne, C. P., Chelliah, H., McDaniel, J. C., Rice, B. E., Edwards, J. R., … Danehy, P. M. (2018), Journal of Propulsion and Power, 34(2), 438–448. https://doi.org/10.2514/1.b36550
Leading-edge flow criticality as a governing factor in leading-edge vortex initiation in unsteady airfoil flows
Ramesh, K., Granlund, K., Ol, M. V., Gopalarathnam, A., & Edwards, J. R. (2018), Theoretical and Computational Fluid Dynamics, 32(2), 109–136. https://doi.org/10.1007/s00162-017-0442-0
Numerical simulation of aero-optical effects in a supersonic cavity flow
Zilberter, I. A., Edwards, J. R., & Wittich, D. J. (2017), AIAA Journal, 55(9), 3095–3108. https://doi.org/10.2514/1.j055402
Numerical simulations of turbulent flow over airfoils near and during static stall
Ke, J. H., & Edwards, J. R. (2017), Journal of Aircraft, 54(5), 1960–1978. https://doi.org/10.2514/1.c034186
Scramjet combustion efficiency measurement via tomographic absorption spectroscopy and particle image velocimetry
Busa, K. M., Rice, B. E., McDaniel, J. C., Goyne, C. P., Rockwell, R. D., Fulton, J. A., … Diskin, G. S. (2016), AIAA Journal, 54(8), 2463–2471. https://doi.org/10.2514/1.j054662

View all publications via NC State Libraries

Grants

2019-2020 AIAA Design-Build-Fly Team Space Grant Proposal
National Aeronautics & Space Administration (NASA)(11/15/19 - 5/15/20)
Development of Improved RANS and Hybrid LES/RANS Turbulence Models for Hypersonic Flow Applications
US Air Force Academy(7/08/19 - 7/07/22)
Scale-Resolving Numerical Simulation of Reactive, Two Phase Flows in Hypersonic Propulsion Designs
Air Force Research Laboratory (AFRL)(1/01/19 - 6/30/20)
NCSU American Institute for Aeronautics and Astronautics 2019 Design-Build-Fly Competition
National Aeronautics & Space Administration (NASA)(11/15/18 - 7/31/19)
NCSU American Institute of Aeronautics and Astronautics Design Build Fly Senior Design Team Space Grant Proposal
NCSU NC Space Grant Consortium(11/30/17 - 8/31/18)
NCSU American Institute of Aeronautics and Astronautics Design Build Fly Space Grant Proposal
NCSU NC Space Grant Consortium(11/30/17 - 7/30/18)
Modeling of Air, Surface, and Underwater burst Phenomena within Complex Environments after High Energy Explosion
Defense Agency of Technology and Quality (DTaQ)(7/05/17 - 5/31/20)
Improved Numerical Simulations of Barbotage Atomization
Air Force Research Laboratory (AFRL)(10/15/16 - 11/12/18)
Research Area 1, Section 1.4.1: Engines: Mesh-sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion (Short Term Innovative Research Program)
US Army - Army Research Office(1/17/17 - 12/31/17)
A Deep-Learning Approach Towards Auto-Tuning CFD Codes
US Air Force - Office of Scientific Research (AFOSR)(6/01/17 - 2/14/18)