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. Lav C, Sandberg R, Philip J. A framework to develop data-driven turbulence models for flows with organised unsteadiness. JOURNAL OF COMPUTATIONAL PHYSICS. Academic Press. 2019, Vol. 383. DOI: 10.1016/j.jcp.2019.01.022
  2. Akolekar H, Weatheritt J, Hutchins N, Sandberg R, Laskowski G, Michelassi V. Development and Use of Machine-Learnt Algebraic Reynolds Stress Models for Enhanced Prediction of Wake Mixing in Low-Pressure Turbines. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME. ASME International. 2019, Vol. 141, Issue 4. DOI: 10.1115/1.4041753
  3. Wu H, Moreau S, Sandberg R. Effects of pressure gradient on the evolution of velocity-gradient tensor invariant dynamics on a controlled-diffusion aerofoil at Re-c=150 000. JOURNAL OF FLUID MECHANICS. Cambridge University Press. 2019, Vol. 868. DOI: 10.1017/jfm.2019.129
  4. Marconcini M, Pacciani R, Arnone A, Michelassi V, Pichler R, Zhao Y, Sandberg R. Large Eddy Simulation and RANS Analysis of the End-Wall Flow in a Linear Low-Pressure-Turbine Cascade-Part II: Loss Generation. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME. ASME International. 2019, Vol. 141, Issue 5. DOI: 10.1115/1.4042208
  5. Lengani D, Simoni D, Pichler R, Sandberg R, Michelassi V, Bertini F. On the Identification and Decomposition of the Unsteady Losses in a Turbine Cascade. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME. ASME International. 2019, Vol. 141, Issue 3. DOI: 10.1115/1.4042164
  6. Sandberg R, Michelassi V. The Current State of High-Fidelity Simulations for Main Gas Path Turbomachinery Components and Their Industrial Impact. FLOW TURBULENCE AND COMBUSTION. Springer. 2019, Vol. 102, Issue 4. DOI: 10.1007/s10494-019-00013-3
  7. Anupindi K, Sandberg R. An Embedded Flow Simulation Methodology for Flow over Fence Simulations. 10th ERCOFTAC Workshop on Direct and Large Eddy Simulation (DLES). Springer. 2018, Vol. 24. Editors: Grigoriadis DGE, Geurts BJ, Kuerten H, Frohlich J, Armenio V. DOI: 10.1007/978-3-319-63212-4_37
  8. Schoepplein M, Weatheritt J, Sandberg R, Talei M, Klein M. Application of an evolutionary algorithm to LES modelling of turbulent transport in premixed flames. JOURNAL OF COMPUTATIONAL PHYSICS. Academic Press. 2018, Vol. 374. DOI: 10.1016/j.jcp.2018.08.016
  9. Sandberg R, Tan R, Weatheritt J, Ooi A, Haghiri A, Michelassi V, Laskowski G. Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot. ASME Turbo Expo 2018. American Society of Mechanical Engineers. 2018, Vol. 5A-2018. DOI: 10.1115/GT2018-75444
  10. Sandberg R, Tan R, Weatheritt J, Ooi A, Haghiri A, Michelassi V, Laskowski G. Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME. ASME International. 2018, Vol. 140, Issue 10. DOI: 10.1115/1.4041268
  11. Schlanderer S, Sandberg R. Boundary Data Immersion Method for DNS of Aero-vibro-acoustic Systems. 10th ERCOFTAC Workshop on Direct and Large Eddy Simulation (DLES). Springer. 2018, Vol. 24. Editors: Grigoriadis DGE, Geurts BJ, Kuerten H, Frohlich J, Armenio V. DOI: 10.1007/978-3-319-63212-4_54
  12. Akolekar H, Weatheritt J, Hutchins N, Sandberg R, Laskowski G, Michelassi V. DEVELOPMENT AND USE OF MACHINE-LEARNT ALGEBRAIC REYNOLDS STRESS MODELS FOR ENHANCED PREDICTION OF WAKE MIXING IN LPTS. ASME Turbo Expo: Turbomachinery Technical Conference and Exposition. ASME International. 2018, Vol. 2C-2018. DOI: 10.1115/GT201875447
  13. Wu H, SanjosÉ M, Moreau S, Sandberg R. Direct numerical simulation of the self-noise radiated by installed controlled-diffusion airfoil at transitional reynolds number. 2018 AIAA/CEAS Aeroacoustics Conference. 2018. DOI: 10.2514/6.2018-3797
  14. Serrano-Galiano S, Sandham ND, Sandberg R. Fluid-structure coupling mechanism and its aerodynamic effect on membrane aerofoils. JOURNAL OF FLUID MECHANICS. Cambridge University Press. 2018, Vol. 848. DOI: 10.1017/jfm.2018.398
  15. Pichler R, Michelassi V, Sandberg R, Ong J. Highly Resolved Large Eddy Simulation Study of Gap Size Effect on Low-Pressure Turbine Stage. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME. ASME International. 2018, Vol. 140, Issue 2. DOI: 10.1115/1.4038178

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