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Predicting the effect of voids generated during RTM on the low-velocity impact behaviour by machine learning-based surrogate models
(Elsevier, 2023)
The main objective of the present paper is to demonstrate the feasibility of machine-learning-based surrogate models for predicting low-velocity impact behaviour considering void content and location generated during the ...
Definition of 3D Printing Parameters by the Design of Experiments to Characterise Carbon Fibre-Reinforced Polyamide
(Springer, 2024)
This paper presents the application of an advanced quality management tool, the design of experiments (DOE), in order to characterise a new material (carbon fibre-reinforced polyamide) used in the 3D printing process. The ...
An analytical model of through-thickness photopolymerisation of composites: Ultraviolet light transmission and curing kinetics
(Elsevier, 2020)
In this paper, a kinetic model able to predict the evolution of the through-thickness degree of cure of ultraviolet (UV) cured composites has been developed and validated. The kinetic model, which is based on the autocatalytic ...
Impact performance prediction of as-manufactured Resin Transfer Moulding composites using Machine Learning based Digital Twin
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2022)
The use of lightweight materials has demonstrated to be very energy efficient in the transport sector, reducing the consumption of fossil fuels and increasing the range of electric cars. Carbon fibre reinforced polymers ...
Paneles fabricados mediante curado UV de prepregs fuera de autoclave reforzados con perfiles de pultrusión UVPanels manufactured by UV curing of out-of-autoclave prepregs reinforced with UV pultrusion profiles
(Scipedia, 2023)
Los materiales compuestos, gracias a sus elevadas propiedades específicas, buena resistencia a la corrosión y libertad de diseño, están en la agenda estratégica de muchos sectores de gran valor añadido como la aeronáutica, ...