Objective
CompSTLar proposes a novel, holistic integrated-and-interoperable physical and digital-driven research ecosystem encompassing automated and scalable composite technologies, multiphysics-based and data-driven models, AI-powered tools, and sensorized processes and products, for the advanced design and cost-competitive manufacturing, intelligent maintenance and repair, and sustainable recycling of novel graphene-functionalized multifunctional and multimaterial (M&M) thermoplastic composite (TPC) aerostructures. Key developments to pave the way towards the CompSTLar ambition are: 1) an innovative, bespoke, laser-assisted ATL process with in-situ ultrasonic quality inspection boosted by off-line X-ray computed tomography characterization and AI-powered tools -to propel zero defect and high-volume ISC-ATL manufacturing; 2) advanced ML surrogates of high-fidelity multiphysics, and multiscale composite damage simulation coupled with on-the-fly optical fibre- and novel laser-induced graphene-based strain sensor data - for real-time structural health assessment and monitoring; 3) a modern induction-assisted conduction welding process enhanced with data-driven modelling grounded on parametric numerical simulations and real-world novel Fresnel-based sensor data - for smart repair of next-generation TP aerostructures, and 4) pioneering recycling process to facilitate complete undamaged recovery of TPC tapes suitable for reuse with ATL to confirm sustainable circular manufacturing. Digitalized methods, processes and tools will be physically tested and digitally integrated into an interoperable IIoT collaborative, modular and decentralized digital research infrastructure, i.e. CompSTLar end-to-end digital pipeline. CompSTLar digital ecosystem will support the optimized design, sustainable manufacturing, efficient maintenance, repair, and circularity of M&M composite aerostructures, allowing faster, more accurate, and more informed decision-making along the aircraft supply chain.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyenvironmental engineeringwaste managementwaste treatment processesrecycling
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencescomputational sciencemultiphysics
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Keywords
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
36410 Porrino
Spain