GC
G. Catalanotti
5 records found
1
This work represents the first step towards the application of machine learning techniques in the prediction of statistical design allowables of composite laminates. Building on data generated analytically, four machine algorithms (XGBoost, Random Forests, Gaussian Processes and
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A micromechanics framework for modelling the longitudinal failure of unidirectional fibre composites, in both tension and compression, is presented. Appropriate constitutive models are used for the different constituents (i.e., fibre and matrix) and interfaces. An algorithm for t
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The effect of through-thickness compressive stress on mode II interlaminar fracture toughness is investigated experimentally and replicated numerically. The modified Transverse Crack Tensile specimen recently proposed by the authors is used, together with an experimental device d
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The effect of through-thethickness compressive stress on the mode II interlaminar fracture toughness is investigated experimentally and replicated numerically. It is shown that the mode II interlaminar fracture toughness increases with the applied compressive through-the-thicknes
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The Transverse Crack Tension test revisited
An experimental and numerical study
Several problems arise when measuring the mode II interlaminar fracture toughness using a Transverse Crack Tension specimen; in particular, the fracture toughness depends on the geometry of the specimen and cannot be considered a material parameter. A preliminary experimental cam
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