MOTIVATE Project in CS2 H2020

Simulation of structural behaviour is a key part of the design and operation of safety critical engineering infrastructure.  It is used to support design choices and to inform decisions about the servicing and operation of engineering structures and machines.  It is common practice to establish confidence in predictions from computer models used in simulation by comparing them to measurements obtained from physical tests on prototypes.  These physical tests are often expensive and time-consuming to conduct which can place them on the critical path in the development of new designs of aircraft.  Recent advances in measurement technology allow fields of measurements of the deformation of large-scale structures to be obtained during physical tests; however, the effective use of this ‘big data’ presents both challenges and opportunities in the context of validating predictions of structural behaviour.  The aim of the MOTIVATE project was to bring about a step change in the way simulations, or virtual tests, and physical tests are used together in an industrial environment to reduce the cost, risks and time associated with product development.  The specific objectives of the project were:

i.              to develop a robust and repeatable method for the quantification of uncertainties in measurements using digital image correlation in an industrial environment,

ii.             to produce advanced structural test protocols with an associated methodology for validation of simulation data, and

iii.            to deploy the validation methods and test protocols in a demonstration during a structural test case.

The project was a response to Innovation Action JTI-CS2-2016-CFP04-AIR-02-32 entitled 'Testing Matrix Optimisation by Interaction between Numerical Modelling & Innovative Non-Contact Measurement Technology' within Work Package B 3.3.2 of Technology Stream B3: Advanced Integrated Structures in the ITD Airframe of the Clean Sky Joint Technology Initiative (JTI).  Specifically, the intention was to improve and develop the existing methodologies for quantifying uncertainty in measurements of displacement and strain field, and in parallel, to progress and mature the current methodologies for correlating predicted and measured data fields in order to provide a simple-to-use and robust approach to validating computational models.  Enabling technologies, which had been demonstrated in laboratory conditions during a series of EU FP 5 and 7 projects, including SPOTS [No. G6RD-CT-2002-00856]; ADVISE [No. 218595] and VANESSA [No. NMP3-SA-2012-319116], have been refined, developed and transitioned into the industrial environment and demonstrated in a structural test on an aircraft subcomponent (a 1 sq.m fuselage panel) and in an aircraft-scale structural test on a cockpit at the Topic Manager’s site [Airbus in Toulouse].  The outcomes of the project are:

  • A methodology for the validation of simulation tools in structural mechanics;
  • A procedure for the quantification of measurement uncertainty in digital image correlation;
  • Protocols and best practice for validation methodology for subcomponents; and
  • A test case demonstrating 'double-blind' deployment of protocols and implementation of validation methodology.

In conclusion, the robust protocols for validation will enhance confidence and credibility in computational simulations of structures, and thus, enable light-weight, elegant designs to be brought to the marketplace faster and at lower costs by reducing the number of tests required to develop high fidelity models of new designs of aircraft structures.  Light-weight, elegant structures are essential in realising the Clean Sky goal of achieving major steps towards the ACARE (Advisory Council for Aeronautics Research in Europe) Environment Goals for 2020.

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MOTIVATE Project in CS2 H2020

MOTIVATE is an Innovation Action within the European Commission's Horizon 2020 Clean Sky 2 program under Grant Agreement No. 754660, supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 17.00064.

This Community Collection contains material from the significant progress on methods for DIC calibration and model validation, notably on measuring the quality of data comparison.

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September 25, 2020
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