Multiscale Modelling of Aerospace Composites: Increasing Quality, Reducing Empiricism and Challenging Conservatism

Lead Research Organisation: University of Bath
Department Name: Mechanical Engineering


Whilst the basic advantages of composite laminates, such as carbon fibre-reinforced plastic, are well proven, they are often compromised by high cost, long development time and poor quality due to multiple defects, particularly in complex parts such as those found in aerospace applications. Within the aerospace industry, where safety is paramount, design changes require expensive programmes of empirical testing over a variety of length scales, the so-called "test pyramid". An important objective of this complex engineering system is to minimize the probability of failing the certification test. Modelling technologies and testing at various stages of development are all orchestrated toward this objective, which has been heuristically developed over the last decades without a clear understanding of how each player contributes to uncertainty reduction.

This project will engage a multidisciplinary team of engineers and mathematicians to develop novel mathematical modelling tools to address this issue. An embedded university-industry partnership will focus effort on creation of new capability with underlying fundamental research to reduce design-to-manufacture time and increase quality in airframe and aero-engine manufacture, critically important to the international standing of the UK aerospace sector. We will systematically develop stochastic models that integrate uncertainties from simulations and empirical testing (at different stages of the test pyramid) and quantify their propagation through the system to provide effective and reliable quality control for high-quality carbon fibre manufacture. New and fully-validated, laminate designs will be developed that challenge the inherent conservatism and the expensive industry standard which predominantly uses empirical testing for structural integrity certification.

A central theme to the project is the complex interaction of multiple scales within the structural hierarchy of an aircraft component. Interaction over all the scales strongly influences each of the three research areas addressed within this programme. Recently gained expertise in the modelling of folding in layered geological structures will be exploited to study the physically analogous formation of defects during automated manufacture of laminated parts. Multiscale structural performance models will draw upon novel numerical upscaling techniques to predict the strength of large aerospace components containing microscale internal defects. Novel probabilistic uncertainty quantification tools, such as multilevel Monte Carlo and multilevel Monte Carlo Markov Chain, will be brought to bear in performance analyses of entire sub-components. The data for these models will be inferred directly from images obtained using Computational X-ray Tomography (CT).

Manufacturing practices will be informed by seconding team members to GKN Aerospace, located at the National Composites Centre, to explore the interaction between the technical and business objectives of the industry, assisting researchers in the use of the new modelling tools, and in the selection of optimal manufacturing solutions. Target components will be wing spars, skin-stringer panels, and engine fan blades. The development and application of the novel stochastic methods for failure prediction will be undertaken with expert guidance of visiting researchers from the University of Florida and Lawrence Livermore National Laboratory, CA.

Our vision is to enable a greater than 50% reduction in design-to-manufacture time whilst ensuring predictable product improvement, amounting to significant (>10%) component weight saving.

Planned Impact

The development of multiscale models to increase quality, reduce empiricism and challenge conservatism in composites manufacturing has widespread impact over a number of beneficiaries. The following are identified along with the manner in which they will benefit.

Composite manufacturers (e.g. GKN Aerospace) and Original Equipment Manufacturers (e.g. Airbus, Rolls-Royce, Agusta-Westland, wind turbine manufacturers): Firstly, the ability to reduce or even rule out defect formation during manufacture will lead to improved performance and increased structural efficiency. This will enable reduced fuel burn or improved energy efficiency of composite components within complete products such as aircraft, aero-engines and wind turbines. Secondly, the use of multiscale performance models, alleviating the emphasis on empirical testing for certification, will significantly reduce development cost, cut time to market and provide greater opportunity for design optimisation of components (again leading to increased structural efficiency).

Composite material suppliers (e.g. Hexcel, Cytec): The improved use and understanding of composite material arising from the new modelling capability will mean that the material becomes more attractive to manufacturers, and that its key properties become better understood. This, in turn, will increase sales and lead to improved material performance.

Commercial FE software developers (e.g. ABAQUS): The new multiscale methods, including fibre-resin scale representation of defects, and the stochastic uncertainty quantification tools that are based on these multiscale methods, will be of interest in the development of new commercial modelling capability.

Airlines and the general public: Improved fuel efficiency of aircraft, as well as lower cost and reduced environmental impact of air travel.

Wider numerical modelling community (e.g. in mathematics, geoscience, biomechanics): New models for folding and buckling of layers, new multiscale modelling techniques, new uncertainty quantification capability.


10 25 50
Description Understanding and evaluation of the large influence of boundary conditions on testing of small representative parts to indicate strength of large component.
Development of novel multi-level Bayesian inference tools for efficient uncertainty quantification in large-scale FE problems, in particular with a view to combining experimental data with numerical simulations to reduce both physical testing & conservatism in aerospace composites design and manufacture.
Exploitation Route Completion of project plus take-up of new testing protocols by industry.
Sectors Aerospace, Defence and Marine,Manufacturing, including Industrial Biotechology,Transport

Description The A350 is the first Airbus airliner with composite wings, saving 25% in fuel, CO2 and operating cost compared with earlier metallic aircraft, with GKN supplying the rear spars, the backbone of the new wings. New multiscale modelling and testing methodologies created at Bath have allowed GKN to: (i) meet the Airbus ramp-up in production rates from 1/month in 2013 to 13/month (and revenues of GBP150,000,000/year) in 2018, and (ii) reduce spar scrappage, with direct savings of GBP11,000,000/year and over 1,200t/year in CO2 from reduced material wastage.
First Year Of Impact 2013
Sector Aerospace, Defence and Marine,Manufacturing, including Industrial Biotechology,Transport
Impact Types Economic

Description GKN
Amount £60,000 (GBP)
Funding ID GKN 
Organisation GKN 
Sector Private
Country United Kingdom
Start 10/2014 
End 09/2017
Description GKN & Royal Academy of Engineering Research Chair 
Organisation GKN
Department GKN Aerospace
Country United Kingdom 
Sector Private 
PI Contribution Bi-monthly research meetings; reports; papers; software support; data
Collaborator Contribution Bi-monthly research meetings; data; supply of material; industrial expertise
Impact Over 10 PhD studentships; 50 papers; over £5M third party funding
Start Year 2011
Title dune-composites module within DUNE (the Distributed and Unified Numerics Environment) 
Description A module to efficiently model and simulate composite materials within the high-performance parallel software platform DUNE. 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact Enables for the first time true large-scale simulation of small manufacturing defects in large component parts. Was used by GKN Aerospace, our industrial partner, to simulate some of their experimental tests and to discover improved certification option by using edge treatment of test "coupons". Interest also from the commercial software developers, such as ABAQUS.