Descripción del proyecto
Nuevos componentes con una mayor resistencia a la fractura
Los sectores europeos aeroespacial y del transporte cada vez utilizan más componentes de materiales compuestos reforzados con fibras y fabricados por adición (AMC, por sus siglas en inglés), producidos mediante modelado por deposición fundida. Esto no resulta sorprendente, teniendo en cuenta sus ventajas: unos costes de maquinaria, materiales y mano de obra inferiores, menos residuos de fabricación y el uso de materiales más eficientes. Sin embargo, hay un impedimento: los componentes de AMC presentan una geometría compleja y, en algunos casos, teselada que da lugar a mecanismos de daños cuasifrágiles y combinados. En este contexto, el proyecto financiado con fondos europeos AI2AM desarrollará componentes con una mayor resistencia a la fractura. En particular, formará a modelos sustitutos que se desplegarán dentro de un nuevo marco de optimización de la topología para alcanzar geometrías impresas en 3D óptimas.
Objetivo
"Additively Manufactured fibre reinforced composite (AMC) components manufactured via fused deposition modelling (FDM)
rapidly find applications within the European aerospace and transport industry , due to their well-known advantages mainly
relating to less machine, material and labour costs, less manufacturing waste, and usage of more efficient materials. A major
drawback of AMC components is their usually complex and in cases tessellated geometry; this gives rise to combined (e.g.
fibre pull-outs and matrix cracking) and quasi-brittle damage mechanisms that deviate from the usual “high strength and
ductile metal” design paradigm. Such a “complexity”, if controlled, can result in components of tailored mechanical
properties, e.g. of increased fracture toughness and pseudo-ductile post fracture response. Unfortunately, current analysis
and design methods lack the necessary level of refinement, or the underlying theoretical framework indeed, to efficiently
address this critical issue.
AI2AM aims to deliver a holistic approach to additively manufacture topologically optimum composite components of
increased fracture toughness. It will achieve this by developing a state-of-the-art fracture simulation framework for composite
structures harnessing the fidelity and computational advantages of phase field modelling for fracture and scaled boundary
finite element methods.
This high fidelity physics based ""continuum toolbox"" will be used to train surrogate models based on machine learning
methods. The surrogates will then be deployed within a novel topology optimisation framework to deliver optimal and 3D
printed geometries. The envisaged methodology crosses the boundaries of computational mechanics, optimisation, and
machine learning and brings together a talented academic with world-class experts in topology optimisation, composites,
and additive manufacturing."
Ámbito científico
- engineering and technologymaterials engineeringcomposites
- natural sciencesmathematicspure mathematicstopology
- natural sciencesmathematicspure mathematicsgeometry
- engineering and technologymechanical engineeringmanufacturing engineeringadditive manufacturing
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Palabras clave
Programa(s)
Régimen de financiación
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
157 80 ATHINA
Grecia