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MACADAMIA SIGNED

Machine learning Augmented Computational Analysis of composite panels: new insights into DAmage Mechanisms In Aerospace structures with nanoparticles

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 MACADAMIA project word cloud

Explore the words cloud of the MACADAMIA project. It provides you a very rough idea of what is the project "MACADAMIA" about.

fuel    cycle    classification    computational    until    estimation    competitiveness    regulations    added    carefully    pound    machine    weight    critical    difficult    14000    commercial    conjunction    life    arrest    prone    mechanics    durability    structural    mechanical    safe    strategy    certification    plan    nanotechnology    experiments    hot    structures    classify    tolerance    vital    nanoparticles    damage    stiffened    optimise    environmental    longer    predictive    aerospace    count    integration    technologies    panels    aircraft    realized    fleet    nanoparticle    seamless    composite    learning    evolution    leveraged    strengthen    multidisciplinary    gallons    strength    load    mitigates    predict    fasteners    macadamia    smartly    physics    reducing    delay    models    compliance    fastener    innovative    bearing    serve    savings    spots    envisions    prediction    ambitiously    mechanisms    certified    accelerated    retain    data    inclusion    coupled    free    alternatives    flight    evaluation    primary    efficacy    popular    designed   

Project "MACADAMIA" data sheet

The following table provides information about the project.

Coordinator
TECHNISCHE UNIVERSITEIT DELFT 

Organization address
address: STEVINWEG 1
city: DELFT
postcode: 2628 CN
website: www.tudelft.nl

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Total cost 175˙572 €
 EC max contribution 175˙572 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2020
 Duration (year-month-day) from 2020-04-01   to  2022-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TECHNISCHE UNIVERSITEIT DELFT NL (DELFT) coordinator 175˙572.00

Map

 Project objective

MACADAMIA ambitiously seeks a seamless integration of machine learning concepts with physics-based models to optimise aerospace stiffened panels for damage tolerance. As an innovative strategy to delay damage, nanoparticles will be added in failure-prone hot-spots of composite stiffened panels to serve as damage arrest features. The efficacy of machine learning when used in conjunction with advanced computational methods for data classification and prediction will be smartly leveraged to classify and predict damage mechanisms in aircraft structures, the understanding of which is critical to their safe implementation. In aircraft, stiffened composite panels are popular alternatives to structures with mechanical fasteners because they retain strength while reducing weight and part count; but cost and weight savings cannot be fully realized until stiffened panels are certified without fasteners in primary load-bearing structures. It is estimated that a one-pound weight reduction on each aircraft in a commercial fleet would result in fuel savings of 14000 gallons/year, which also mitigates the environmental impact of flight. To strengthen the competitiveness of European aerospace technologies in compliance with evolving environmental regulations, it is vital to work towards accelerated certification of fastener-free composite panels. Major challenges to this goal are: i) damage mechanisms in stiffened panels are complex and coupled, making the evaluation of strength and durability difficult; ii) predictive models for life-cycle estimation have large uncertainty. MACADAMIA envisions an approach with carefully designed experiments for nanoparticle inclusion along with physics-based models to investigate strength and damage evolution in stiffened panels, and machine learning to further optimise them for longer useful life. Multidisciplinary concepts of structural mechanics, computational physics, nanotechnology and machine learning will be used to accomplish research plan.

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The information about "MACADAMIA" are provided by the European Opendata Portal: CORDIS opendata.

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