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Giuseppe Catalanotti

Researcher at Queen's University Belfast

Publications -  104
Citations -  2760

Giuseppe Catalanotti is an academic researcher from Queen's University Belfast. The author has contributed to research in topics: Fracture toughness & Ultimate tensile strength. The author has an hindex of 24, co-authored 93 publications receiving 2023 citations. Previous affiliations of Giuseppe Catalanotti include Faculdade de Engenharia da Universidade do Porto & University of Évora.

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Numerical modelling of failure in advanced composite materials

TL;DR: Numerical modeling of failure in advanced composite materials comprehensively examines the most recent analysis techniques for advanced composite material as mentioned in this paper and presents new and emerging advanced numerical algorithms for modeling and simulation of failure.
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Simulation of failure in laminated polymer composites: Building-block validation

TL;DR: In this paper, a methodology to simulate elastic and inelastic deformation of composite laminates at the subcomponent level based on finite element analysis is proposed, which is validated for three aerospace-grade carbon fibre reinforced (epoxy) polymer composite material systems and coupon configurations with increasing level of complexity.
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On the importance of nesting considerations for accurate computational damage modelling in 2D woven composite materials

TL;DR: In this article, the mechanical behaviour and progressive damage of two-dimensional plain woven carbon-epoxy fabrics are modelled at different length scales, taking into account the geometric and material variability of the weave, by subjecting the dry preforms to compaction simulations.
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Effect of tow thickness on the structural response of aerospace-grade spread-tow fabrics

TL;DR: In this paper, an experimental test campaign was carried out to study the structural response of aerospace-grade plain weave spread-tow fabrics (STFs) of different areal weights.
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A methodology to generate design allowables of composite laminates using machine learning

TL;DR: This work serves as basis for the prediction of first-ply failure, ultimate strength and failure mode of composite specimens based on non-linear finite element simulations, providing further reduction of the computational time required to virtually obtain the design allowables for composite laminates.