Professor Richard Sandberg

  • Room: Level: 04 Room: 407
  • Building: Mechanical Engineering
  • Campus: Parkville

Research interests

  • Computational Fluid Dynamics (High-order accurate numerical methods, high-performance computing)
  • Numerical Modelling (High-performance computing for CFD, hybrid RANS/LES methods)
  • Turbomachinery (Low-pressure and high-pressure turbines, compressor flows)
  • Turbulent Flows (Aeroacoustics, Flow and Noise Control, Compressible Flows)

Biography

Richard is Chair of Computational Mechanics in the Department of Mechanical Engineering.  His main interest is in high-fidelity simulation of turbulent flows and the associated noise generation in order to gain physical understanding of flow and noise mechanisms and to help assess and improve low-order models that can be employed in an industrial context. 
He was awarded a veski innovation fellowship in July 2015 entitled: "Impacting Industry by enabling a step-change in simulation fidelity for flow and noise problems"

Prior to joining the University of Melbourne, he was a Professor of Fluid Dynamics and Aeroacoustics in the Aerodynamics and Flight Mechanics research group at the University of Southampton and headed the UK Turbulence Consortium (www.turbulence.ac.uk), coordinating the work packages for compressible flows and flow visualisations and databases. 

Career History
 

• 2015-present: Chair of Computational Mechanics in the Department of Mechanical Engineering at the University of Melbourne 
• 2012-2015: Professor of Fluid Dynamics and Aeroacoustics in the Aerodynamics and Flight Mechanics research group at the University of Southampton
• 2011-2012: Senior Lecturer of Aerospace Engineering in the Aerodynamics and Flight Mechanics Research
• 2008: Visiting Researcher at Karlsruhe Institute of Technology, Germany
• 2007-2012: Royal Academy of Engineering/EPSRC research fellowship
• 2007-2011: Lecturer of Aerospace Engineering in the Aerodynamics and Flight Mechanics Research
• 2005-2007: Research Fellow in Simulation of trailing-edge broadband noise in Aerodynamics and Flight Mechanics Research Group University of Southampton
• 1999-2004: PhD in Aerospace Engineering at the University of Arizona in ‘Numerical Investigation of Transitional and Turbulent Supersonic Axisymmetric Wakes’ (with Prof. Hermann Fasel)
• 1998-1999: M.S. in Aerospace Engineering at the University of Arizona in 1999 ‘Investigation of Turbulence Models for Turbulent Boundary Layer Flows using Temporal Numerical Simulations’
• 1994-1998: ‘Undergraduate’ at the University of Stuttgart

Recent publications

  1. Anupindi K, Sandberg R. An embedded flow simulation methodology for flow over fence simulations. ERCOFTAC Series. Springer. 2018, Vol. 24.
  2. Schlanderer S, Sandberg R. Boundary data immersion method for DNS of aero-vibro-acoustic systems. ERCOFTAC Series. Springer. 2018, Vol. 24.
  3. Sandberg R. Large-scale compressible-flow direct numerical simulations. ERCOFTAC Series. Springer. 2018, Vol. 24.
  4. Weatheritt J, Sandberg R, Ling J, Saez G, Bodart J. A COMPARATIVE STUDY OF CONTRASTING MACHINE LEARNING FRAMEWORKS APPLIED TO RANS MODELING OF JETS IN CROSSFLOW. ASME Turbo Expo: Turbine Technical Conference and Exposition. ASME International. 2017, Vol. 2B-2017.
  5. Wu H, Winkler J, Sandberg R, Moreau S. Direct numerical simulation of transitional airfoil noise. 23rd AIAA/CEAS Aeroacoustics Conference, 2017. 2017.
  6. Bechlars P, Sandberg R. Evolution of the velocity gradient tensor invariant dynamics in a turbulent boundary layer. JOURNAL OF FLUID MECHANICS. Cambridge University Press. 2017, Vol. 815.
  7. Pichler R, Sandberg R, Laskowski G, Michelassi V. HIGH-FIDELITY SIMULATIONS OF A LINEAR HPT VANE CASCADE SUBJECT TO VARYING INLET TURBULENCE. ASME Turbo Expo: Turbine Technical Conference and Exposition. ASME International. 2017, Vol. 2A-2017.
  8. Pichler R, Michelassi V, Sandberg R, Ong J. HIGHLY RESOLVED LES STUDY OF GAP SIZE EFFECT ON LOW-PRESSURE TURBINE STAGE. ASME Turbo Expo: Turbine Technical Conference and Exposition. ASME International. 2017, Vol. 2A-2017.
  9. Weatheritt J, Sandberg R. Hybrid reynolds-averaged/large-eddy simulation methodology from symbolic regression: Formulation and application. AIAA Journal. American Institute of Aeronautics and Astronautics . 2017, Vol. 55, Issue 11.
  10. Anupindi K, Sandberg R. Implementation and Evaluation of an Embedded LES-RANS Solver. FLOW TURBULENCE AND COMBUSTION. Springer. 2017, Vol. 98, Issue 3.
  11. Leggett J, Priebe S, Shabbir A, Sandberg R, Richardson E, Michelassi V. LES LOSS PREDICTION IN AN AXIAL COMPRESSOR CASCADE AT OFF-DESIGN INCIDENCES WITH FREE STREAM DISTURBANCES. ASME Turbo Expo: Turbine Technical Conference and Exposition. ASME International. 2017, Vol. 2A-2017.
  12. Zauner M, Sandham ND, Wheeler APS, Sandberg R. Linear stability prediction of vortex structures on high pressure turbine blades. 12th European Conference on Turbomachinery Fluid Dynamics and Thermodynamics, ETC 2017. 2017, Vol. 2, Issue 2.
  13. Weatheritt J, Pichler R, Sandberg R, Laskowski G, Michelassi V. MACHINE LEARNING FOR TURBULENCE MODEL DEVELOPMENT USING A HIGH-FIDELITY HPT CASCADE SIMULATION. ASME Turbo Expo: Turbine Technical Conference and Exposition. ASME International. 2017, Vol. 2B-2017.
  14. Shin D-H, Sandberg R, Richardson ES. Self-similarity of fluid residence time statistics in a turbulent round jet. JOURNAL OF FLUID MECHANICS. Cambridge University Press. 2017, Vol. 823.
  15. Schlanderer S, Weymouth GD, Sandberg R. The boundary data immersion method for compressible flows with application to aeroacoustics. JOURNAL OF COMPUTATIONAL PHYSICS. Academic Press. 2017, Vol. 333.

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile