Professor Paul Tucker

LES Modelling of Turbine Blade Trailing Edges (Rolls-Royce and EPSRC funded) In this project the LES modelling of the wall type jets issuing from the trailing edges of turbine blades will be explored using a range of LES techniques. Linear and non-linear LES models will be considered along with HYBRID implicit LES-RANS techniques.

Unsteady fan flow modelling on GPUs (Rolls-Royce) In this project fan simulations will be performed for flows with upstream distortion. The simulations will be large scale and performed on GPUs. The idea is to create a reliable predictive design capability. Also, the simulations will enable a greater physical understanding of the distortion transfer process to be gained.

Flow in Cavities and Shroud Leakage/Stator Well Paths (Rolls-Royce and TSB funded) In this project the flow in turbine cavities and shroud leakage/stator well paths will be studied. Boundary conditions will be developed to avoid the need for the explicit modelling of these zones. Also, RANS, URANS and LES simulations will be performed in these areas and deterministic stress modelling developed. These will enable faster design simulations to be made in the turbine cavities and shroud leakage/stator well paths.

Large Eddy Simulation for Jet and Exhaust Noise (Rolls-Royce and TSB funded) The objective of this project is to build improved jet noise prediction schemes through conducting jet LES calculations and validating these against the noise and turbulence experimental database from the NTF. The LES computations will cover: single stream and coaxial jets; jet velocity variation; jet temperature variation and coaxial jet area ratio variation. Further LES computations and validation will then cover effects of 3D nozzles, in particular the effect of the pylon. Collectively the LES and experimental results will feed the development of improved jet noise prediction methods.

Modelling of Transonic Flow and Transition on Curved Surfaces (Rolls-Royce and EPSRC) (Rolls-Royce and EPSRC Funded) The interaction of transonic flow with boundary layers is an important consideration for both aero engine intakes and exhaust systems. In the intake we see interaction of a transitional boundary layer with both transonic flow and shocks. When the shock structures are sufficiently strong it is straightforward to predict both the flow conditions inducing separation and the separation location with current RANS CFD methods. With weak shocks or in the case of transonic shock-free flow the prediction of separation from these curved surfaces is significantly more difficult, since it depends strongly on the state of the approaching boundary layer. In the intake this boundary layer is transitional; in the exhaust flow acceleration through the nozzle will suppress turbulence levels. The accurate prediction of separation from curved surfaces in transonic flow is therefore an important part of a total CFD capability and turbulence models for the reliable prediction of this will be explored.

High Efficiency Turbomachinery (EPSRC Funded) This project is part of a larger effort with the overall aim of reducing the environmental impact of gas turbines by improving the efficiency of turbomachinery. Large Eddy Simulation (and hybrids of it) will be used to study and hence understand flow around real turbine engine geometry. The development of simpler turbulence models to mimic these complex flow regimes will also be pursued along with the development of low order models for small scale features. A key output from the research will be the ability to design complex geometries with confidence in the design process within project time scales. The significant deliverable will be a validated computational modelling technique for effective design.

Cambridge UGTP Whole Engine Computational Aeroacoustics Consortium (EPSRC Funded) With the projected demand for air transport set to double the world aircraft fleet by 2020 it is becoming urgent to take steps to reduce the environmental impact of take off noise from aircraft. In worst case noise can be more than just annoying, potentially being a contributory factor towards illnesses such as hypertension. Hence, the Advisory Council for Aeronautics Research in Europe (ACRE) has set the target of reducing perceived noise levels by 50% by the 2020. A key noise source is caused by the powerfully turbulent flow field generated at the high Reynolds numbers associated with aerospace flows. Hence, the acoustician must be able to accurately predict the turbulent flow field, and its interaction, where necessary with combustion, and then manipulate it to reduce the acoustic signature. The only means of reliably predicting turbulence is through direct or near direct simulation of the Navier-Stokes equations. This, at realistic Reynolds numbers needs massive computational resources. Hence, access to the HECToR resource is being used to study various aeroengine flows/systems to produce noise reductions. The areas considered include the engine inlet rotor/fan zones, the combustor, turbine and exhaust.

Open Rotor Intake Aerodynamics (Rolls-Royce Funded) The ultimate aim of the program is to provide a design optimization tool for open rotor design. Although open rotors will yield substantial reductions in specific fuel consumption their design presents substantial coupled aerodynamic & aeroacoustic challenges. With regards to aerodynamics, to minimize engine size and hence weight for the tractor configuration the compressor inlet air must be passed down some form of complex geometry, sharply turned inlet duct. The duct entry flow will transmit the unsteady wake component from the upstream rotors. This sharply turned, local adverse pressure gradient, flow is likely to readily become separated and with bifurcated inlets exhibit an unsteady limit cycle behaviour. The interaction of the unsteady upstream flow with the compressor face presents a key CFD (Computational Fluid Dynamics) challenge. Hence, the project involves significant unsteady flow modelling. A key objective is to devise a design optimisation system for engine inlets. However, prior to this a greater flow physics understanding is required to help shape the design optimisation system. Also, it is necessary to develop the necessary CFD tools for Rolls-Royce in house use.

Differential Distance Function Computations for Mesh Generation (EPSRC Funded) - This project will explore the solution of differential distance function equations on unstructured moving and overset meshes. Flow solutions using such grids are increasingly common. However, robust mesh generation still presents a significant challenge. This is especially so if use is made of hexahedral cells and the higher numerical fidelity that they provide. The differential equations explored will include the hyperbolic Eikonal, Hamilton-Jacobi and elliptic Poisson. Especial attention will be paid to the economical and accurate solution of these equations on moving, unstructured over-set grids with mixed element topologies using finite element, finite volume & boundary element methods.

Advances in Mesh Generation (EPSRC Funded) - This project aims to pursue the use of unstructured mesh technology driven by applications. Applications provide the challenges that highlight deficiencies in a method that then leads to basic research and theoretical understanding that will then result in an enhanced capability. The proposed work will address many of the deficiencies that are currently restricting the wider use of computational simulation. In particular, problems associated with geometries will be emphasised and new and innovative techniques will be investigated for their solution. Furthermore, new methods of generating high quality meshes that can maximise the efficiency of solution algorithms will be explored. These developments will be made available through the use of recent developments in computer technology, such as the GRID and web services.

Development of Zonal LES and Wall Distance Approaches for the HYDRA CFD Code (Royal Society Funded) – This project transfers CFD technology (zonal LES, differential equation based turbulence distance functions and aeroacoustics) developed at Boeing Commerical Airplanes and NASA Langley to the Rolls Royce HYDRA CFD code.

Wall Distance and DES Computations for Flow with Time-Dependent Geometry (EPSRC Funded) – This project was carried out at NASA Langley working with the CFL3D CFD code. A novel zonal ILES approach was applied to a computational aeroelasticity problem. Also, the Eikonal wall distance equation was solved in an implicit/iterated form amenable to easy implementation in general geometry CFD solvers.

Aerodynamics and Aeroacoustics of co-flowing jets (EPSRC Funded, with Rolls-Royce Collaboration) – This project explores the dynamics of co-flowing jets in a jet-noise context. For the CFD, novel Zonal Large Eddy Simulation (ZLES) and non-linear LES approaches will be developed and then applied. Such approaches are probably better suited than pure LES to jets with co-flow.

DES Applied to Airplanes (Foresight and Boeing Funded, working with Boeing Commercial Airplanes) – This project mostly involves applying Detached Eddy Simulation and wall distance algorithms to various regions of an aircraft.

Prediction of Oscillatory Forced Convection Flows in Complex Geometries (EPSRC Funded) – This project mostly involves the use of CFD to predict heat transfer enhancements arising from oscillatory flows. Although focusing on electronics (where it is believed this research will make the greatest industrial impact) the proposed work is also relevant to the modelling of flows in buildings, other congested engineering systems and general engineering flows which are unsteady, turbulent and exhibit strong streamline curvature. Various novel turbulence-modelling strategies are being developed.

Computation of Internal Flows using Zonal Large Eddy Simulation: A Novel Approach (EPSRC Funded)– This project will explore the effectiveness of the Zonal Large Eddy Simulation Approach when modelling basic boundary layer flows and also separated flow behind a cylinder. The Zonal LES approach combines LES and RANS models.