This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

Braiding is a direct tow to net-shape preform technology enabling to tailor performance with braid angle variation, different interlacing patterns and possibility of triaxial structures. This design flexibility also comes with high production rate and repeatability, making braiding extremely suitable to fully automated processes. With ever stricter environmental regulations, the demand for composites parts has been increasing significantly over the last decade. As a result, finalising the transition to highly automated processes has never been more pressing for the composite manufacturing industry.

The scarcity of reliable process modelling leads to costly and time-consuming physical trials, slowing down the adoption of the technology. Accurately predicting the preform fibre architecture allows to understand the mechanical properties of the finished part, but also to anticipate defects arising during the braiding process and at the resin infusion stage. Hence, this work is focused on producing a model that predicts accurately the fibre architecture of a braided preform. A previous study conducted by the National Composites Centre (NCC) compared the kinematic and Finite Element (FE) output for a given shape and confirmed that considering the yarn-to-yarn and yarn-to-mandrel friction produces a more accurate representation of the braid architecture. This was achieved by using an in- house developed FE model in Abaqus, and follow-up activity has focused on increasing the capacity and quality of such model. This paper aims to outline the advances made in the modelling of the braiding process using the finite element approach and discuss some of the most challenging aspects.

By developing more in-depth verification and automation methods, the following areas of improvement were identified: contact modelling between the yarns, the yarn tensioning system, and braid pattern irregularity. These issues were addressed in the model and validated against an experimental trial using an in-process monitoring of braid angles. The outcome was an improved prediction of the braid angle, an even pattern and a more lightweight and efficient model. The resulting model can now be the starting point for further simulation, to predict the permeability and structural integrity of the future manufactured part.