Hong Luo


  • 919-513-3898
  • Engineering Building III (EB3) 3236
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Dr. Luo is interested in computational fluid dynamics, computational magnetohydrodynamics, computational aeroacoustics, fluid-structure interaction, high-performance computing, and unstructured grid generation.

At the graduate level, Dr. Luo teaches Computation Fluid Dynamics (MAE 766). This course is concerned with the finite difference, finite volume, and finite element methods for solving the governing equations in fluid dynamics. Dr. Luo guides his students toward an expertise in numerical methods and strong capabilities in programming.

At the undergraduate level, he teaches Aerodynamics I (MAE 355) and Heat transfer fundamentals (MAE 310). In Aerodynamics I, he brings in examples over the wide range of flow speeds he has encountered in his own work, like low speed flow past an Indy-racing car, transonic flow around a Boeing 747, supersonic flow past a missile, and hypersonic flow past a space shuttle.

The students who work with Dr. Luo are drawn to his area of research because they find the numerical simulations and modeling, both technically interesting and intellectually challenging, and appreciate the increasingly important role that they play in science and engineering. These students appreciate its major impact on the development, design, and analysis of modern airplanes, high speed trains, advanced ships/submarines, high performance cars, new weapon systems, and nuclear reactors, leading to work opportunities in government/industry/national labs. Dr. Luo looks for students who are self-motivated, hard-working, and strong in mathematics and computer programming.

See also Dr. Luo’s ResearcherID site and his Google Scholar link below.

Outside of work, Dr. Luo enjoys spending time with his family, exercising, and traveling.



Applied Mathematics

Pierre et Marie Curie University


Applied Mathematics

Pierre et Marie Curie University



Nanjing University of Aeronautics and Astronautics

Research Description

Dr. Luo's long-term goal is to impact engineering and science through the development of innovative numerical methods and advanced computational techniques in the areas of computational fluid dynamics, computational aeroacoustics, and computational magnetohydrodynamics. Dr. Luo is currently developing 1) high-order spatial/temporal discretization methods based on reconstructed discontinuous Galerkin schemes for the next generation of CFD codes in aerospace and nuclear engineering, 2) a hybrid structured-unstructured grid methodology for the analysis of advanced propulsion systems, and 3) advanced unstructured grid methods in magnetohydrodynamics for the understanding and modeling of solar physics phenomena. In MAE, he collaborates with Dr. Edwards.

Honors and Awards

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A moving discontinuous Galerkin finite element method with interface condition enforcement for compressible flows
Luo, H., Absillis, G., & Nourgaliev, R. (2021), JOURNAL OF COMPUTATIONAL PHYSICS. https://doi.org/10.1016/j.jcp.2021.110618
A reconstructed discontinuous Galerkin method for compressible flows on moving curved grids
Wang, C., & Luo, H. (2021), ADVANCES IN AERODYNAMICS. https://doi.org/10.1186/s42774-020-00055-6
Reconstructed discontinuous Galerkin methods for compressible flows based on a new hyperbolic Navier-Stokes system
Li, L., Lou, J., Nishikawa, H., & Luo, H. (2021), JOURNAL OF COMPUTATIONAL PHYSICS, 427. https://doi.org/10.1016/j.jcp.2020.110058
An enhanced AUSM(+)-up scheme for high-speed compressible two-phase flows on hybrid grids
Pandare, A. K., Luo, H., & Bakosi, J. (2019), SHOCK WAVES, 29(5), 629–649. https://doi.org/10.1007/s00193-018-0861-x
An updated Lagrangian discontinuous Galerkin hydrodynamic method for gas dynamics
Wu, T., Shashkov, M., Morgan, N., Kuzmin, D., & Luo, H. (2019), COMPUTERS & MATHEMATICS WITH APPLICATIONS, 78(2), 258–273. https://doi.org/10.1016/j.camwa.2018.03.040
Reconstructed Discontinuous Galerkin Methods for Hyperbolic Diffusion Equations on Unstructured Grids
Lou, J., Liu, X., Luo, H., & Nishikawa, H. (2019), COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 25(5), 1302–1327. https://doi.org/10.4208/cicp.OA-2017-0186
Robust Implicit Direct Discontinuous Galerkin Method for Simulating the Compressible Turbulent Flows
Xiaoquan, Y., Cheng, J., Luo, H., & Zhao, Q. (2019, March), AIAA JOURNAL, Vol. 57, pp. 1113–1132. https://doi.org/10.2514/1.J057172
Second memorial issue in honor of Dr. Meng-Sing Liou
Chang, C.-H., & Luo, H. (2019), SHOCK WAVES. https://doi.org/10.1007/s00193-019-00932-0
A reconstructed direct discontinuous Galerkin method for simulating the compressible laminar and turbulent flows on hybrid grids
Yang, X. Q., Cheng, J., Luo, H., & Zhao, Q. J. (2018), Computers & Fluids, 168, 216–231. https://doi.org/10.1016/j.compfluid.2018.04.011
A reconstructed discontinuous Galerkin method for compressible turbulent flows on 3D curved grids
Liu, X. D., Xia, Y. D., & Luo, H. (2018), Computers & Fluids, 160, 26–41. https://doi.org/10.1016/j.compfluid.2017.10.014

View all publications via NC State Libraries

View publications on Google Scholar


Development of Moving Discontinuous Galerkin Methods for Hypersonic Reacting Flows
National Aeronautics & Space Administration (NASA)(5/19/21 - 6/19/22)
Development of Moving Discontinuous Galerkin Methods for Compressible Flows
US Dept. of Energy (DOE)(2/08/21 - 9/30/21)
Development of p-adaptive Reconstructed Discontinuous Galerkin Methods for Compressible Multi-Material Flows
US Dept. of Energy (DOE)(7/02/20 - 9/30/22)
Development of a Moving Discontinuous Galerkin Methods for Compressible Flows
US Dept. of Energy (DOE)(2/28/19 - 9/30/20)
Enabling Highly Scalable Multiphysics Simulation of Particulate Systems on Exascale Computing Architectures
US Dept. of Energy (DOE)(3/28/18 - 9/30/18)
Development of hp Reconstructed Discontinuous Galerkin Methods for Compressible Flows Using CHARM++
US Dept. of Energy (DOE)(12/20/17 - 9/30/19)
Development and Assessment of a Reconstructed Discontinuous Galerkin Method for Compressible Flows in Lagrangian Formulation
US Dept. of Energy (DOE)(4/20/17 - 9/30/18)
A Deep-Learning Approach Towards Auto-Tuning CFD Codes
US Air Force - Office of Scientific Research (AFOSR)(6/01/17 - 2/14/18)
Hyperbolic Reconstructed-Discontinuous-Galerkin Method for High-Order Unsteady Viscous Simulations on Unstructured Grids
US Army - Army Research Office(5/01/16 - 9/30/19)
High-Fidelity Numerical Simulation of Energy Recovery from Oil Shale
NCSU Research and Innovation Seed Funding Program(1/01/14 - 12/31/14)