Artificial Intelligence driven topology optimisation of Additively Manufactured Composite Components

Project description

New components of improved fracture toughness

The European aerospace and transport industries are increasingly utilising additively manufactured fibre reinforced composite (AMC) components that have been made via fused deposition modelling. This is not a surprise, considering their advantages (fewer machine, material and labour costs, less manufacturing waste, and usage of more efficient materials). However, there is one drawback: AMC components have complex and, in some cases, tessellated geometry, which results in combined and quasi-brittle damage mechanisms. In this context, the EU-funded AI2AM project will develop components of increased fracture toughness. Specifically, it will train surrogate models that will be deployed within a new topology optimisation framework to deliver optimal 3D printed geometries.

Fields of science

• engineering and technology › materials engineering › composites
• natural sciences › mathematics › pure mathematics › topology
• natural sciences › mathematics › pure mathematics › geometry
• engineering and technology › mechanical engineering › manufacturing engineering › additive manufacturing
• natural sciences › computer and information sciences › artificial intelligence › machine learning

Programme(s)

• H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme
• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility

Topic(s)

• MSCA-IF-2020 - Individual Fellowships

Call for proposal

H2020-MSCA-IF-2020

See other projects for this call

Funding Scheme

MSCA-IF-EF-ST - Standard EF

Coordinator

ETHNICON METSOVION POLYTECHNION

Net EU contribution

€ 165 085,44

Address

Heroon Polytechniou 9 Zographou Campus
157 80 Athina
Greece

Region

Κεντρικός Τομέας Αθηνών › Aττική › Αττική

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 0,00