Uncertainty Exploration in Material Modelling for Bird Strike Impacts

Master Thesis (2025)
Author(s)

D. Jonikaitė (TU Delft - Aerospace Engineering)

Contributor(s)

Saullo G.P. Castro – Mentor (TU Delft - Delft University of Technology)

Wydo van de Waerdt – Mentor (Fokker/GKN Aerospace)

Ines Uriol Balbin – Graduation committee member (TU Delft - Delft University of Technology)

A. Anisimov – Graduation committee member (TU Delft - Delft University of Technology)

Luc Hootsmans – Mentor (Fokker/GKN Aerospace)

Faculty
Aerospace Engineering
More Info
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Publication Year
2025
Language
English
Graduation Date
30-10-2025
Awarding Institution
Delft University of Technology
Programme
['Aerospace Engineering']
Faculty
Aerospace Engineering
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Abstract

Bird strikes pose a significant threat to aircraft safety, yet accurately predicting their impact behaviour remains challenging due to many uncertainties, such as variations in bird properties, high impact velocities, and limited experimental data. While much research has focused on modelling the bird itself, understanding the structural response of materials, particularly aluminium alloys commonly used in aircraft structures, is just as important. This thesis investigates how different material model definitions in the plasticity regime affect the predicted response of aluminium 2024-T3 under bird strike conditions.
Moreover, it investigates the uncertainties that arise from limited quasi-static testing or usage of inconsistent material properties that can be found in the literature. The work aims to highlight the influence of modelling choices and identify key sources of uncertainty related to material characterisation. Using a surrogate model implementation for two chosen plasticity models, Ramberg-Osgood and Johnson-Cook plasticity models, the uncertainties are being assessed through one-factor-at-a-time sensitivity analysis together with Monte Carlo analysis. The results of this work contribute to improving the reliability of bird strike simulations and provide guidance for future model development.

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