Education

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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Publications

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. https://doi.org/10.2514/1.J057172

A robust and efficient finite volume method for compressible inviscid and viscous two-phase flows

Pandare, A. K., & Luo, H. (2018), JOURNAL OF COMPUTATIONAL PHYSICS, 371, 67–91. https://doi.org/10.1016/j.jcp.2018.05.018

Application of nonlinear Krylov acceleration to a reconstructed discontinuous Galerkin method for compressible flows

Wang, C. J., Cheng, J., Berndt, M., Carlson, N. N., & Luo, H. (2018), Computers & Fluids, 163, 32–49. https://doi.org/10.1016/j.compfluid.2017.12.015

Cell-centered high-order hyperbolic finite volume method for diffusion equation on unstructured grids

Lee, E., Ahn, H. T., & Luo, H. (2018), Journal of Computational Physics, 355, 464–491. https://doi.org/10.1016/j.jcp.2017.10.051

Reconstructed discontinuous Galerkin methods for linear advection-diffusion equations based on first-order hyperbolic system

Lou, J. L., Li, L. Q., Luo, H., & Nishikawa, H. (2018), Journal of Computational Physics, 369, 103–124. https://doi.org/10.1016/j.jcp.2018.04.058

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

Sensitivity analysis of interfacial momentum closure terms in two phase flow and boiling simulations using MCFD solver

Liu, Y., Rollins, C., Dinh, N., & Luo, H. (2017), In Proceedings of the ASME Summer Heat Transfer Conference, 2017, vol 2. https://doi.org/10.1115/ht2017-4963

A parallel, high-order direct discontinuous Galerkin methods for the Navier-Stokes equations on 3D hybrid grids

Cheng, J., Liu, X. D., Liu, T. G., & Luo, H. (2017), Communications in Computational Physics, 21(5), 1231–1257. https://doi.org/10.4208/cicp.oa-2016-0090

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Grants

Development of a Moving Discontinuous Galerkin Methods for Compressible Flows

US Dept. of Energy (DOE)(2/28/19 - 9/30/19)

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Development of a Moving Discontinuous Galerkin Methods for Compressible Flows

Sponsor: US Dept. of Energy (DOE)

Start Date: 2/28/19

End Date: 9/30/19

Abstract

We will explore and develop a moving discontinuous Galerkin method for compressible flows.

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Enabling Highly Scalable Multiphysics Simulation of Particulate Systems on Exascale Computing Architectures

US Dept. of Energy (DOE)(3/28/18 - 9/30/18)

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Enabling Highly Scalable Multiphysics Simulation of Particulate Systems on Exascale Computing Architectures

Sponsor: US Dept. of Energy (DOE)

Start Date: 3/28/18

End Date: 9/30/18

Abstract

The main objective of this LDRD-NUC project is to explore the use of Charm++ in Dr. Xia’s LDRD project in order to achieve a high parallel efficiency for the coupling of mesh-based structure mechanics and particle-based fluid dynamics.

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Development of hp Reconstructed Discontinuous Galerkin Methods for Compressible Flows Using CHARM++

US Dept. of Energy (DOE)(12/20/17 - 9/30/19)

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Development of hp Reconstructed Discontinuous Galerkin Methods for Compressible Flows Using CHARM++

Sponsor: US Dept. of Energy (DOE)

Start Date: 12/20/17

End Date: 9/30/19

Abstract

The main objective of this research effort is to develop and implement adaptive hp discontinuous Galerkin (DG) methods into Quinoa for compressible flows on unstructured grids.

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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)

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Development and Assessment of a Reconstructed Discontinuous Galerkin Method for Compressible Flows in Lagrangian Formulation

Sponsor: US Dept. of Energy (DOE)

Start Date: 4/20/17

End Date: 9/30/18

Abstract

Develop and assess a reconstructed discontinuous Galerkin (rDG) method for compressible flows in a Lagrangian formulation.

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A Deep-Learning Approach Towards Auto-Tuning CFD Codes

US Air Force - Office of Scientific Research (AFOSR)(6/01/17 - 2/14/18)

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A Deep-Learning Approach Towards Auto-Tuning CFD Codes

Sponsor: US Air Force - Office of Scientific Research (AFOSR)

Start Date: 6/01/17

End Date: 2/14/18

Abstract

Heterogeneous computing systems are increasingly becoming the norm in high-performance computing (HPC) norm. For instance, as of the November 2015 TOP500 List, more than 35% of the computational power on the TOP500 now comes from systems containing heterogeneous computing devices, e.g., CPUs, GPUs, APUs, Xeon Phis, and even FPGAs. However, significant hurdles impede a domain scientist ability to extract high performance out of such heterogeneous devices, including (1) selecting the appropriate algorithm(s) for the target heterogeneous device, (2) setting the runtime parameters, and (3) configuring the hardware relative to some evaluation metric, e.g., performance, power, or energy efficiency. Unfortunately, exploring hardware and software design choices often requires time-consuming simulations, and while some brute-force auto-tuning support has been proposed, the results are heuristic that are often narrow in scope, i.e., only applicable to a particular problem. This proposal seeks to study, analyze, and synthesis deep-learning approaches that expose the various parameters as "knobs" that can be tuned via deep learning to optimize for the metric of interest, whether it be performance, power, or energy efficiency.

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Hyperbolic Reconstructed-Discontinuous-Galerkin Method for High-Order Unsteady Viscous Simulations on Unstructured Grids

US Army - Army Research Office(5/01/16 - 4/30/19)

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Hyperbolic Reconstructed-Discontinuous-Galerkin Method for High-Order Unsteady Viscous Simulations on Unstructured Grids

Sponsor: US Army - Army Research Office

Start Date: 5/01/16

End Date: 4/30/19

Abstract

The objective of the proposed project is to develop a third- and higher-order unsteady viscous solver for 3D unstructured arbitrary grids by combining the FOHS method and the rDG method.

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High-Fidelity Numerical Simulation of Energy Recovery from Oil Shale

NCSU Research and Innovation Seed Funding Program(1/01/14 - 12/31/14)

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High-Fidelity Numerical Simulation of Energy Recovery from Oil Shale

Sponsor: NCSU Research and Innovation Seed Funding Program

Start Date: 1/01/14

End Date: 12/31/14

Abstract

The objective of the effort discussed in this project is to develop an innovative interdisciplinary program on high-fidelity simulation of energy recovery from oil shale and other unconventional energy resources using advanced computational fluid dynamics methodology. A primary focus of this project is to establish a research center that will provide our expertise and capability in numerical simulation and modeling to address some challenging problems in different INL (Idaho national laboratory)research project and eventually be funded by INL.

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High Performance Computing for NASA's Applications

National Aeronautics & Space Administration (NASA)(8/16/13 - 8/15/16)

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High Performance Computing for NASA's Applications

Sponsor: National Aeronautics & Space Administration (NASA)

Start Date: 8/16/13

End Date: 8/15/16

Abstract

Computational simulations are now playing an increasingly important role in science and engineering, which are routinely used by engineers and scientists for the development, design, analysis, and optimization of modern airplanes, high speed trains, advanced ships/submarines, high performance cars, new weapon systems, and nuclear reactors. High performance computing is essential to virtually all of NASA's major programs; it supports all phases of NASA activity from formulation of hypotheses to conceptual design to analysis to mission operations. In aeronautics, it is vital not only to NASA's own technology, but to NASA's mission of supporting and enhancing the competitiveness of the U.S. civil aircraft manufacturing industry. Although NASA has achieved a supercomputing capability of several billion FLOPS (floating points per second), even that tremendous capability will not be adequate for the computational demands of tomorrow, because complex future flight vehicles will be more difficult to simulate.

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Co-Design of Hardware / Software for Predicting MAV Aerodynamics

US Air Force - Office of Scientific Research (AFOSR)(9/01/12 - 10/31/15)

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Co-Design of Hardware / Software for Predicting MAV Aerodynamics

Sponsor: US Air Force - Office of Scientific Research (AFOSR)

Start Date: 9/01/12

End Date: 10/31/15

Abstract

This proposal provides subcontractor support to Virginia Tech for a proposal submitted under the Air Force's Basic Research Initiative. The proposal will focus on development of reconfigurable mapping strategies for porting multi-block structured and unstructured-mesh CFD codes to computing clusters containing CPU/GPU processing units.

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Development and Assessment of a Reconstructed Discontinuous Galerkin Method for Compressible Flows at All Speeds

US Dept. of Energy (DOE)(4/16/12 - 12/31/12)

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Development and Assessment of a Reconstructed Discontinuous Galerkin Method for Compressible Flows at All Speeds

Sponsor: US Dept. of Energy (DOE)

Start Date: 4/16/12

End Date: 12/31/12

Abstract

NCSU is pleased to offer the following statement of work in support of Idaho National Laboratory¡¯s effort on the development of a modern reactor safety code. The main objective of the research effort is to develop and assess a reconstructed discontinuous Galerkin method for compressible flows at all speeds. In reconstructed DG methods, termed RDG(PnPm), Pn indicates that a piecewise polynomial of degree of n is used to represent a DG solution, and Pm represents a reconstructed polynomial solution of degree of m (m¡Ýn) that is used to compute the fluxes. The RDG(PnPm) schemes are designed to enhance the accuracy of the discontinuous Galerkin method by increasing the order of the underlying polynomial solution. The beauty of the RDG(PnPm) schemes is that they provide a unified formulation for both finite volume and DG methods, and contain both classical finite volume and standard DG methods as two special cases of RDG(PnPm) schemes, and thus allow for a direct efficiency comparison. When n=0, i.e. a piecewise constant polynomial is used to represent a numerical solution, RDG(P0Pm) is nothing but classical high order finite volume schemes, where a polynomial solution of degree m (m ¡Ý1) is reconstructed from a piecewise constant solution. When m=n, the reconstruction reduces to the identity operator, and RDG(PnPn) scheme yields a standard DG method. Our lately developed Hermit WENO reconstruction-based discontinuous Galerkin method is designed not only to reduce the high computing costs for the DG methods, but also to avoid spurious oscillations in the vicinity of strong discontinuities, thus effectively overcoming the two shortcomings of the DG methods and ensuring the stability of the reconstructed DG method. In this work, the developed RDG method will be used to compute the compressible flows at all speeds. In particular, the ability of this RDG method for 1) low Mac number speed flows and 2) flows with stiffened equations of state will be assessed, tested, and validated.

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