Master Assignment
Human bones are highly heterogeneous materials of an uncertain nature. Their properties are varying from one person to another, and are highly dependent on the persons age and their life habits. More importantly, the material properties of bone are not known, and cannot be obtained by using experimental data as such experiments do not yet exist, or are expensive. In order to model material characteristics, one has to introduce generalized constitutive material laws that account for all variations and uncertainties. In this project the crack propagation will be studied by including all variations. For this purpose, machine learning strategies will be combined with the finite element modelling, thus building digital twins.
The methods studied in this thesis are not only applicable on the bone problems but are general and can be used in many applications.
The thesis will include:
- Literature review
- Finite element model of femur
- Modelling of bone macroscopic properties
- Building of digital twin with the help of neural networks
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