Objective
The reduction of the environmental footprint of aviation relies on the development and fast deployment of lighter and more efficient polymer composite structures; however, the current configurations of composite aerospace structures result in a highly constrained design space. Additionally, the limitations of the state-of-the-art analysis methods result in overly conservative designs and in time-consuming certification methodologies. As a result, composite laminates have only contributed to modest weight savings in aircraft structures. Based on these observations, the main objective of the project is to unleash the full potential of composite systems to yield more efficient aerospace composite structures. The premise is that polymer composite laminates are far from being used to their full potential, and that significant performance improvements of composite aerospace structures can be obtained by developing a new systems-thinking methodology that will link the different scales of a composite system. The methodology relies on the combination of new experimental studies, conducted at the micro-scale of the composite material, that will guide the development of analysis methods at different spatial scales. The theoretical developments, guided by experiments and computations, will create the building blocks of a neural network that will unravel the currently hidden relations between manufacturing conditions, micro- and meso-structures of a composite material, and the performance of a composite structure. Overcoming this knowledge gap will enable the development of new, non-conventional micro-structures using different types of reinforcing fibres, and of new laminate configurations that will not be restrained by a limited set of fibre orientation angles. It is expected that, for the first time, the discontinuity between material design and structural design will be removed, opening new avenues for concurrent optimization of composite materials and structures.
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 technologymaterials engineeringcomposites
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
- natural scienceschemical sciencespolymer sciences
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
4200-465 Porto
Portugal