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Optimización del proceso de Compression Resin Transfer Moulding (CRTM) mediante técnicas experimentales y simulación
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2017)
The environmental protection, with special emphasis on CO2 emissions reduction, is a growing demand that the transport industry has to fulfill. Carbon fibre reinforced polymers (CFRP) are interesting candidates as they can ...
Optimization of the CRTM process by means of monitoring techniquesOptimización del CRTM mediante técnicas de monitorizado de procesos
(Scipedia, 2018)
In this work the feasability of the monitoring system, composed of flow-rate and injection pressure sensors, in addition to the pressure sensors integrated in the mold, is demonstrated to determine the optimal process ...
Impregnation quality diagnosis in Resin Transfer Moulding by machine learning
(Elsevier Ltd., 2021)
In recent years, several optimization strategies have been developed which reduce the overall defectiveness of the RTM manufactured part. RTM filling simulations showed that, even using optimized injection strategies, local ...
Efecto de la separación fibra-matriz sobre las propiedades mecánicas de una viga forjada en poliamida reforzada con fibra de vidrioEffect of the fiber-matrix separation on the mechanical properties of a fiberglass reinforced polyamide forged beam
(Scipedia, 2022)
In the present work, ribbed beams have been manufactured by forging fiberglassreinforced polyamide using two different temperatures. The higher processing temperature studied (300 ºC) ensures the filling of the mold in the ...
Effect of voids on the impact properties of Non-Crimp fabric carbon/epoxy laminates manufactured by liquid composite Moulding
(Elsevier, 2022)
A great effort has been made to quantify the detrimental effect of voids on CFRP, nevertheless, the effect on impact properties has been barely studied and when it has been considered, it has always been for prepeg materials ...
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 ...
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 ...