Deep learning accelerated prediction of the permeability of fibrous microstructures

Permeability of fibrous microstructures is a key material property for predicting the mold fill times and resin flow path during composite manufacturing. In this work, we report an efficient approach to predict the permeability of 3D microstructures from deep learning based permeability predictions of 2D cross-sections combined via a circuit...

A fully coupled thermo-mechanical analysis for the minimisation of spring-in and process time in ultra-thick components for wind turbine blades

The paper tackles the multi-objective optimisation of the cure stage of the Vacuum Assisted Resin Transfer Moulding (VARTM) process to manufacture the root insert of wind turbine blades. The aim of the study is to compare the Pareto front obtained from a pure heat transfer analysis, where temperature overshoot is an objective, with the one...

Effect of convection coefficient and thickness on optimal cure cycles for the manufacturing of wind turbine components using VARTM

The paper deals with the influence of the convection coefficient and laminate thickness on multi-objective optimisation of the vacuum assisted resin transfer moulding cure stage for the manufacturing of wind turbine components. An epoxy resin system widely used in the wind turbine industry has been chemically characterised and the...

Multi-objective optimisation of the cure of thick components

This paper addresses the multi-objective optimisation of the cure stage of composites manufacture. The optimisation aims to minimise the cure process duration and maximum temperature overshoot within the curing part by selecting an appropriate thermal profile. The methodology developed combines a finite element solution of the heat transfer...