GKN Aerospace will lead the ATI ISLAA (Implementation of Sustainable Large Additive for Aerospace) project. The project will bring together GKN's aerospace manufacturing expertise with the centre for modelling and simulation (CFMS), the University of Bristol and the University of Manchester in order to advance and implement large scale additive manufacturing in the aerospace structures domain. The project will build capability to exploit the technology for initial structures applications while focusing on the approaches necessary to realise large scale complex parts. This will result in the UK aerospace industry having technology that can reduce the cost and lead time associated with complex structural forgings and crucially produce the parts with lower emissions as part of GKN Aerospace's commitment to net zero. The project will build on GKN Aerospace's deep additive manufacturing expertise covering the entire manufacturing process. Innovation will come both in the deposition process itself and the critical supporting technologies that are necessary to maximise the value from the process and confirm the quality of the end product. CFMS will utilise their modelling and simulation expertise to develop novel approaches to predict process behaviour, linking this to the parameters and toolpaths that should be used to realise aerospace quality material. The University of Bristol will support with their capability in non-destructive testing to realise the methods that can reliably assess and confirm the quality of the material produced. Finally the University of Manchester will bring their material science pedigree to investigate methods to characterise additively manufactured material. The work will significantly stretch the current state of the art, utilising the control that can be exercised over the laser in GKN's large scale additive manufacturing process to drive towards parts that incorporate sections that can be used "as deposited" or with minimal finishing. This means that no subsequent machining is required in large areas of the part reducing cost, lead time and emissions. This will require simulation of the process both at the part distortion and melt pool level, along with a highly controlled deposition process incorporating novel hardware and finally an innovative approach to link surface characterisation and material performance. Through the work conducted in the project there will be a clear route to significant implementation of large scale additive manufacturing for aerospace structures helping the industry with lead time, rates, supply chain security and sustainability, all of which is required for the next generation of civil aircraft.

CFMS is proposing to deliver and demonstrate a unique tool for rapidly optimising train timetables during extreme weather events, delivering a step change in the way in which train operating companies respond to the increasing occurrence of extreme weather. The project will collaborate with GWR & Avanti West Coast to develop, evaluate and demonstrate the benefits of the tool. When extreme weather such as heat waves or heavy rain and flooding are forecast, temporary speed restrictions and line closures are imposed on parts of the network, typically with a few days' notice. This leaves planning teams only 24 to 48 hours to adjust timetables, putting a strain on resources leading to the creation of sub-optimal timetables, resulting in a reduction in service and financial penalty payments being incurred. CFMS proposes utilising parallel, distributed optimisation techniques coupled with high performance compute systems to perform automated timetable optimisation. This will use CFMS's robust timetable optimisation technology developed and validated on representative data on several projects including in the rail sector. The tool will run a very large number of possible timetables in parallel using high performance compute facilities allowing an optimal set of timetables prioritising different goals to be determined. An API will be developed to allow easy use of the tool and integration with other systems. The tool will be developed with close collaboration with train operating companies, including GWR & Avanti. Using real data it will evaluate and demonstrate to a wide reaching audience the transformational efficiency, performance improvements and large scale savings that the tool is capable of delivering for the rail sector.

Digital Assembly for Wing (DAWN) will develop and innovatively apply digital solutions and software tools to demonstrate end-to-end digitalisation for a high production rate aircraft wing assembly and systems installation manufacturing system utilising the Wing of Tomorrow demonstrator wingboxes. The aim is to improve process control, reduce the amount of concessions and inspections, and reduce cycle time by connecting the supply chain, operational workers and support functions to manufacturing assets and assembly processes. Airbus will utilise the results of DAWN to enable a Digital Smart Factory_._

Out-of-autoclave Resin-Infused composites provide a key opportunity for the Aerospace industry. Promising high manufacturing rates, lower manufacturing costs, and environmental sustainability through reduced weight of aerostructures. The CoSInC (Composite Smart Industrial Control) project partners have scoped an ambitious and innovative programme of work targeting key bottlenecks and challenges to achieve a robust, repeatable and rate-enabled industrial system. The project will deliver validated simulations for the various stages of manufacture as well as a next-generation digital manufacturing system. This is a collaborative project between Airbus, MSC, Planit Software, the National Composites Centre (NCC), and the Centre For Modelling and Simulation (CFMS).

The Smarter Testing project aims to develop a novel testing and certification process for aeronautical structures through the use of an optimised test campaign that will combine virtual and physical tests to provide a step reduction in development lead-time and costs. This will be achieved through the development of a continuous digital thread between virtual and physical tests to increase the use of simulations that supports the whole lifecycle of the product, from early design to type-certification. Simulations will be validated using advanced measurements, quantitative data correlation methods and exploited through data analytics in order to increase credibility and maturity.

The DAWS project will explore and evaluate a range of innovative wing concepts (including the use of folding wing tips to allow for greater wing span), needed to significantly improve the performance of future generations of commercial aircraft. With ever increasing awareness of environmental concerns, reducing environmental impact in a commercially sustainable way is now the priority challenge facing the aviation sector. However, such aircraft can only be delivered if the design tools and processes used to develop them are similarly transformed. DAWS will deliver a selection of innovative design and validation processes needed to support the wing development activities.

Designing products collaboratively and exploiting new technologies in the age of artificial intelligence (AI) and machine learning (ML) requires novel approaches to the ways engineering teams must work. In the COLIBRI project we will explore and develop new tools that exploit advances in AI/ML to improve and speed up the collaborative design environment for the UK's aerospace design community. This will include the use of advanced design process automation tools, voxel based geometry to augment the capabilities of conventional CAD tools and generative adversarial network and convolution neural methods to provide an AI/ML layer to these tools.

Awaiting Public Project Summary

CAVs and the infrastructure within which they operate form a highly complex super-system. In addition to operating reliably and safely, this system must be resilient in the face of cyber threats. International automotive cybersecurity standards (ISO/SAE 21434) and regulations (UNECE) are under development, which will specify requirements for cybersecurity throughout the vehicle lifecycle. However, while methods for cybersecurity engineering during development are maturing, rigorous methods to enable CAVs to be resilient in operation are at a much lower level of maturity. There is significant risk of catastrophic failure moving from CAV demonstrations to mass deployment if new methods are not developed to detect, understand and react to emerging threats. ResiCAV will respond to this challenge, building on the partners' preliminary groundwork to inform new operational requirements for resilience, assess their feasibility and identify further work to develop and operationalise them. ResiCAV will: explore the feasibility of the draft AESIN/UK Auto Council Cyber Resilience (CyRes) methodology by taking tools and techniques applied to static analysis of systems and applying them dynamically for real time monitoring/response and numerising and measuring the detect, monitor, act process so resilience will meet legal requirements expected of CAV systems; develop requirements for a cybersecurity operations centre and end-to-end monitoring/response processes and extending the application of AI and data visualisation techniques. These will be aligned with emerging requirements in international standards and will be specified to supplement elements of the new operating methodology as they mature; create specifications for new cybersecurity test facilities, including links, extensions and upgrades to existing UK CAV testbeds to support the development, verification and operationalisation of CyRes; specify requirements for a Cybersecurity Centre of Excellence and distributed ecosystem to leverage UK capabilities in CyRes and validate and deliver the operations methodology. This will build on work already supported by Innovate UK and will include recommendations for the adaptation of assurance and certification schemes such as 5StarS and UNECE regulations to operational CyRes. ResiCAV combines cross-sector expertise from automotive, cybersecurity, network operations, high performance computing, electronics hardware, and AI providing a solid intellectual foundation to address the technical and economic feasibility of achieving globally significant CyRes for CAVs throughout their operational lifetime.

Aerospace Cloud Services is a collaboration between high tech SME Zenotech and the Centre for Modelling and Simulation (CFMS), working with aerospace primes Rolls Royce, Airbus and Bombardier and the cloud computing suppliers Amazon AWS, Oracle & specialist HPC providers to further develop and deploy a web services architecture for engineering applications. The system leverages Internet standards for data exchange and will provide key services in security, support for cloud licensing and dynamic resource allocation. The project is aligned with the ATI Digital Strategy, the HMG Industrial Strategy and the High Value Design initiative and supports AI / Machine Learning.

The project addresses the vision of achieving a 1/3rd reduction in cost per hour of use for complex engineered products across a broad range of UK manufacturing sector output by 2025 (see recently published national strategy on through-life engineering services). The project led by OEM aerospace partners Rolls-Royce plc, BAE Systems and Bombardier Transportation, with a consortium of leading universities, software platform providers and market disseminators will provide accessible Through-life Engineering Services (TES) resources (tools, techniques, databases, best practise use cases and standards) to enable a significant reduction in the operational costs of long life, high value assets such as aero engines, aircraft and rail vehicles.

Aero Flux follows the successful Hyperflux++ (102366) project developing high order computational fluid dynamics (CFD) technology for aerospace. Original partners CFMS (Lead, CFD methods and advanced IT technology), Zenotech (solver technology and support for many-core computing), ARA (mesh generation and validation against wind tunnel data) and Bombardier (nacelle and thrust reverser design and development) will also address requirements for Airbus (surface effects for skin friction drag and undercarriage acoustics) by developing the capability for fluid-structure interaction, broadband acoustics, accelerated time-stepping, advanced high order mesh generation and multi-disciplinary coupling. The project supports international dissemination and export opportunities for UK aerospace technology.

AIRLIFT will mature AM (Additive Manufacturing) technology towards a ‘feed stock in – products out’ factory. State-of-art AM is based around machines developed for prototyping and not for serial production. The current available equipment is not scalable, nor fit to be positioned in an efficient factory where the complete process chain is linked. The AM technology is the core to build products but in the total chain it is just one process step of many.

Stiffer, lighter vehicle structures are required to enable mainstream electrification of common vehicle platforms, boosting adoption of electrified vehicles and improving their environmental performance. However, this requires a step-change in cost effective structural performance at a design, material and manufacturing-level which is currently unmet across the industry. In Project Tucana, Jaguar Land Rover leads a consortium of world-leading academic and industry partners spanning the entire supply chain to introduce large composite assemblies and realise world leading lightweight body structures. The consortium will leverage globally cutting edge industrialised materials, design and manufacturing concepts to integrate much higher quantities of affordable lightweight carbon-fibre composites into premium volume automotive applications, while also increasing the knowledge of these global businesses and the UK research base. As an enabler for a zero-emission electrified vehicle platform, Project Tucana has potential to reduce vehicle CO2 emissions and improve range and air quality. The project will deliver inward investment opportunities and strengthen UK capability by integrating existing automotive lightweight technologies and developing knowledge to deliver a new UK supply chain at a globally significant scale for cost competitive carbon-fibre-composites.

Forecasts indicate the need for over 30,000 new commercial aircraft by 2034. Securing market success depends on delivering products that meet customer demands and ensuring the long term viability of those engaged in developing and producing them. Innovative product architectures and novel technologies will be needed to achieve the demanding performance targets. The design environment used to develop and evaluate such products will also require transformation to meet the crucial development time and cost reduction ambitions. APROCONE, is a key step towards delivering the next generation aviation products and associated advanced design environment. It will deliver capabilities needed to transform the conceptual definition and evaluation of complex products thus providing the foundation on which to achieve significant improvements in development cost and product performance. The consortium of software specialists, industrial end users/suppliers and academic experts, will collaborate to investigate innovative aircraft wings & turbofan engines concepts, whilst developing and demonstrating the capability of the enhanced Design Environment.

Future Engineering System brings together SME 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 (FES) infrastructure to fully integrate engineering data sources within the process lifecycle management (PLM) tool chain. Within the FES, we 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. Dissemination to the wider community – including the aerospace, civil, automotive and renewable energy sectors – will be via a programme of open events.

Hyper Flux ++ builds on the successful Innovate UK project 101890 “Hyper Flux” - developing next generation CFD technology for the civil, automotive, renewable and aerospace sectors using the cutting-edge high order flux reconstruction technique from Peter Vincent and his team at ICL. Hyper Flux ++ 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. We will include localized 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. Hyper Flux is a UK-based software tool, underpinned by expertise within the UK. This is in line with government strategies for HVM and ICT, and forms a cornerstone for the UK aerodynamics ATI.

SWEPT2 follows the successful “Simulated Wake Effects Platform for Turbines” project to establish the viability of GPU-based fluid dynamics simulation of turbine array wake interaction effects. With a view to growing a UK-based technology supply chain, the original partners (DNV GL, Zenotech and the University of Bristol) will be joined by the Offshore Renewable Energy Catapult (providing access to LIDAR data for validation), STFC Daresbury (to apply the latest in big-data analytics to the challenge of comparing CFD & experimental data), CFMS (cloud computing integration and optimisation), and the universities of Surrey, Strathclyde and Imperial College – to provide expertise in wake turbulence and wind tunnel data. SSE has agreed to independently assess the functionality and value of the service during the project. SWEPT2 addresses the energy trilemma by (i) reducing costs, thus enabling a displacement of fossil fuels thereby (ii) cutting carbon emissions & (iii) reducing dependence on insecure imports.

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 the Centre for Modelling and Simulation (CFMS) and high-tech SME 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 - further establishing a center of expertise in the application of new models to on-ramp new users – particularly SMEs. This supports government strategies for HVM and ICT, and the new UK Aerospace Technology Institute.

The Structural Enablers for Advanced Metallic Wing project is a collaboration between industry and research organisation. 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. The 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

Independent review of IT infrastructure for continued cloud deployment of primary services of Pay as You Go, High Performance computing.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.