Research Programmes

Research Programmes

Aiding industry collaboration and dissemination of information through modelling and simulation and HPC, we actively participate in a number of advanced research programmes.

APROCONE

APROCONE is a £19.2 million project led by Airbus to develop new methods for aircraft wing design by embracing opportunities offered by developments in information systems technologies. The Advanced Product Concept Analysis Environment (APROCONE) project, of which CFMS is a collaborative partner, along with Cranfield University, GKN Aerospace, MSC Software, Rolls-Royce and University of Cambridge, will develop new methods for aircraft wing design by harnessing the power of the latest computing technology. The project aims to develop a highly productive, collaborative design environment and associated methodologies that will mean wings can be designed more innovatively and quickly to meet future market and environmental needs. The project has been made possible thanks to joint industry and UK government investment under the Aerospace Technology Institute (ATI). The project will be led by a team from Airbus in Filton, Bristol, which is a global centre of excellence for wing design, development and testing. 

Future Engineering System (FES)

FES brings together CFMS, aerospace prime Rolls-Royce, leading global engineering and technology services company Siemens, systems integrator Sysemia and digital quality specialist eQ-Technologic with academic specialists from the Sheffield Advanced Computing Research Centre and Leeds University Socio-Technical Centre. The consortium will develop and demonstrate a prototype future engineering system infrastructure to fully integrate engineering data sources within the process lifecycle management (PLM) tool chain. Within the FES, the project will demonstrate the integration of raw data from CFD and FEA analyses via JT Open to Siemens PLM, with Uncertainty Quantification and Management (UQ&M) functions and automated agent-based quality control. This will be exercised against real industrial use cases from Rolls Royce and demonstrated within a prototype system at CFMS. 

Hyperflux + +

Hyperflux + + builds on the successful Innovate UK project “Hyperflux” - developing next generation Computational Fluid Dynamics (CFD) technology for the civil, automotive, renewable and aerospace sectors using the cutting-edge high order flux reconstruction technique from Dr. Peter Vincent and his team at Imperial College. Hyperflux + + brings Bombardier, CFMS, Aircraft Research Association Ltd and Zenotech together to further develop the capability and address timely challenges in the aerodynamic modelling of undercarriages and nacelles. Included are localised transition modelling; better and more robust high order mesh generation and high fidelity acoustic source modelling. The capability will be available to all UK organisations via cloud access at the CFMS supercomputer, and will leverage the latest in many-core hardware for fast, efficient computation. Workflow integration to existing tool chains will be via support for most mesh formats, with automated upgrade to high-order elements.

Hyperflux

While Computational Fluid Dynamics (CFD) is used in a many engineering sectors, greater accuracy & efficiency are required before CFD can replace expensive physical prototypes for unsteady flows (including acoustics) and for resolving shed vortices and wakes. High-order flux reconstruction methods developed by Dr. Peter Vincent at Imperial College (IC) are a potential solution. IC will work with CFMS and Zenotech to create new software (using the latest in high-performance computing: conventional and many-core processors for speed and energy efficiency) for evaluation by Airbus, BAE Systems, EADS, Rolls-Royce, DSTL and the UK Aerodynamics Centre. Industrial primes will contribute benchmarking test cases. Via cloud access to its virtual engineering hub, CFMS will make the UK software available to other sectors (civil, automotive and renewable energy) and support its uptake with local specialists.

For Hyperflux test cases results and more information, visit Hyperflux page.

Simulated Wake Effects Platform for Turbines (SWEPT2)

The Offshore Wind Accelerator (OWA) identifies wind turbine wake interaction modelling as one of the top five technologies to improve the efficiency of offshore wind farms. The use of general purpose Computational Fluid Dynamics (CFD) software on normal hardware has been a limiting factor due to the computational effort and affordability of running simulations. The SWEPT2 project is focused on investigating the use of GPU-based CFD, a faster and more scalable alternative. This will provide the industry with an advanced toolset to design larger turbines and larger arrays of turbines and will improve the prediction of wind farm failure, which reduces financing cost and allows energy primes to cut carbon emissions, design better wind farm layouts and deliver cheaper environmentally friendly electricity.

Structural Enablers for Advanced Metallic Wing (STEAM)

The STEAM project is investigating technologies for both the short term and long term exploitation in advanced metallic wings. These include bi-metallic welded components, bonded metallic components, near-net shape fabrication of components and assembly technologies. This  project is a collaboration between industry and research organisations. Industrial partners include Airbus, Constellium, Magellan, BAe Systems, Testia and Airbus Group. Research organisations involved include CFMS, The Advanced Manufacturing Research Centre (AMRC), Cranfield University and Manchester University.

Enhanced Fidelity Transonic Wing (EFT)

Civil aircraft wing design faces a growing challenge to improve the fidelity of performance predictions. The drive towards high performance relies on a combination of small refinements. Even where step changes are sought, the success of a design can depend on the mitigation of complex aerodynamic risks. 1) Wing maximum lift (CLmax) is fundamental in determining aircraft low speed performance. An improvement of the CLmax estimation uncertainty to ±5 lift counts is targeted, requiring a step change in the physical understanding and the modelling approach. 2) The transonic drag rise characteristics of modern aircraft wings are becoming so carefully tuned, that highly precise predictions are vital to correctly capture fundamental design trades. An improvement in the confidence of exotic drag rise behaviour prediction to within 1% aircraft drag is targeted. 3) As wing designs move to more efficient and flexible structures an accurate knowledge of the wing shape in all conditions is a pre-requisite for the realisation of the above aims. The benefit of improved accuracy in wing aeroelastic assessment is expected to be of the order of 1% in aircraft drag. An increase in the use of theoretical methods for aerodynamic loads prediction throughout the aircraft envelope is sought to enable higher levels of structural and design optimisation. The overall objective is to significantly enhance the performance assessment fidelity of transonic wings, reducing risk and uncertainty in the aircraft design process, and thus enabling aircraft to be driven to higher performance standards.

Global Register for Energy Efficient Numerical Simulation (GREENS)

Engineering complex products (aircraft, buildings, wind turbines & motor vehicles) makes extensive use of high fidelity computer modelling. This requires power-hungry computer hardware and specialist software. A bewildering array of options is presented to the end user: hardware, software and algorithm selection – with their own measures of “performance”. Value chain stakeholders would benefit from a standard measure of energy efficiency (EE) – so that the devices, systems and software energy use can be measured and characterised. This informs user choices, and motivate component improvement with a specific value proposition. The GREENS project looked beyond the traditional focus of energy efficient computing – namely the power supply and hardware – to the algorithms being used and how they leveraged the hardware. By looking across different cases, and by using a variety of commercially available or open source solvers, the project participants identified the benefits that came with making adjustments to the algorithms and how those related to the hardware in question.

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