Professor He L., FASME, FRAeS, CEng.

Education:

-BSc, MSc (1982, 1984, Beihang University)
-Ph.D (1990, Cambridge University)

Employment:

-Postdoctoral Research Associate (1990-91, Whittle Laboratory, Cambridge University)
-Senior Research Fellow (1991-93, Girton College, Cambridge University)
-Lecturer (1993-98, School of Engineering, Durham University)
-Reader (1998-2000, School of Engineering, Durham University)
-Chair of Thermo-fluids (2000-2007, School of Engineering, Durham University)
-Royal Academy of Engineering/Rolls-Royce Research Chair (2008-2013, Oxford University)
–Statutory Chair of Computational Aerothermal Engineering (2013-present, Oxford University)

Honours:

-Boyle Scholar (1988, University of Cambridge)
-Professorial Distinction Award (2014, University of Oxford)
-Rolls-Royce Inventor Awards (2013, 2014).         
-ASME Turbo Expo Best Papers in:
    Heat Transfer Best Paper Prizes (2009, 2016, 2020);
    Turbomachinery Best Paper Prizes (2015, 2020);
    Steam Turbine Best Paper Prize (2017).
-The 2017 Global Power and Propulsion Society (GPPS) Best Paper Prize.
-The 2020 ASME Gas Turbine Award.

Services:

-Head of Thermofluids (2001-07); Research Director of School of Engineering, Durham (2005-06).
-Head of Osney Laboratory (renamed as Oxford thermofluid inst ‘Oti’ in 2018), Oxford (2008-2011).
-Acting Director of the University Technology Centre in Aerodynamics and Heat, Oxford (2008-10).
-Oxford Director of EPSRC Centre for Doctoral Training (CDT) in Gas Turbine Aerodynamics (2014-23)
-ASME Turbo Expo Vanguard Chair in: Unsteady Flow (2001, 2007); Conjugate Heat Transfer (2017).  
-Review Chair, the Global Power and Propulsion Society (GPPS) Technical Conference (2017);
-Conference Chair, the 15th International Symposium on Unsteady Aerodynamics, Aero-elasticity and Aeroacoustics of Turbomachines (2018).
-International Scientific Committee, Unsteady Aerodynamics, Aeroelasticity and Aeroacoustics in Turbomachines (Member since 2011, Committee Chair 2015-2018).
-Technical consultant for several European gas turbine/aeroengine and steam turbine companies.
-Member of ASME/International Gas Turbine Institute (IGTI) Committees: Turbomachinery Committee (1998- ); Structural Dynamics Committee (1997- ); Heat Transfer Committee (2012- ).
-Member of Best Paper subcommittee, IGTI Heat Transfer Committee (2022-23).
-Member of Honours and Awards subcommittee, IGTI Heat Transfer Committee (2022-23).
-Guest Editor, International Journal of Computational Fluid Dynamics (2012-13).
-Guest Editor, Journal of Applied Thermal Engineering (2019-2021).
-Associate Editor, ASME Journal of Turbomachinery (2012-2019).
-Associate Editor, Journal of Global Power and Propulsion Society (2017-2019).
-Associate Editor, Aeronautical Journal (2013- ).
-Member of EU PRACE (European Advanced Computing) grant review panel (2013, 2016).
-Member of the ASME-IGTI Honours & Awards Committee (2023-24).
-Editor-in-Chief, Journal of Global Power and Propulsion Society (2020-).

Keynote: Some Machine-Assisted Physical-Learning – ‘Scales’ & ‘Conditions’ in Aero-Thermal-Dynamics Modelling

Abstract:

Many challenges of interest and relevance in Turbomachinery CFD in essence are about ‘Interactions’: those between disciplines, between components and between scales in properly-conditioned settings for engine performance, durability and structural integrity. How can we effectively identify,  predict and understand these interactions? In this talk, we will first take a look at some aero-thermal-dynamic interactions through the previous efforts of the speaker and his colleagues on: Multi-bladerow Interaction; Shape design – Flow control Interaction; Aerodynamics – Aeroelasticity Interaction; Aerodynamics – Heat transfer/Cooling Interaction.
Attention will then be directed to a problem setting of more general and fundamental interest: high Reynolds number turbulent flows over smooth as well as roughened walls with micro-structures. Can we leverage physically learnt turbulence scale-interaction in developing an efficient and accurate scale-resolving method? A two-scale method is developed to meet the two basic competing requirements by the mesh-resolution and the domain-conditioning. The method enables a distinctive on-the-fly correction on numerical errors arising from both the temporal under-resolution (akin to Reynolds-averaging) and the spatial one of under-resolved coarse-mesh in near-wall region. The latter presents a particular challenge to some machine-learning based methods for scale-resolving wall-bounded turbulence simulations.