High-resolution numerical models for damage assessment in composite materials

Abstract

This thesis was conducted as part of an Innovative Training Network (ITN) (“ICONIC” - Improving the crashworthiness of composite transportation structures), funded by the European Union’s Horizon 2020 research and innovation programme, under the Marie Sklodowska-Curie grant agreement No 721256. The reported work was undertaken within Work Package 3 (WP3) - “Numerical modelling of impact and crush behaviour of composite structures”, where the focus was on the high-fidelity modelling of energy absorbing mechanisms of carbon fibre-reinforced polymer (CFRP) composite structures, under a variety of quasi-static and dynamic loading conditions. This contribution presents several numerical strategies to evaluate the mechanical performance of these materials at their different length scales. The developed tools enable a proper and detailed evaluation of the damage mechanisms which arise in both unidirectional and two-dimensional woven textile composites.

It is well established that a methodology which can be considered reliable in predicting the structural response of heterogeneous materials depends on the scale at which damage is explicitly modelled, making low-scale models ideal subjects to assess the behaviour of composites. Here, it is shown that computational micro- and mesomechanics can be regarded as a reliable numerical tool to analyse different types of phenomena whose contribution is often neglected in laminate-level analysis. The effect of certain material parameters on the mechanical performance of the material, which are difficult to characterise experimentally, can now be studied, and consequently, this work makes a vital contribution towards the proper exploitation of high-resolution numerical frameworks.

Date of Award	Dec 2020
Original language	English
Awarding Institution	Queen's University Belfast
Sponsors	EC/Horizon 2020 Marie Skłodowska-Curie actions
Supervisor	Brian Falzon (Supervisor) & Giuseppe Catalanotti (Supervisor)