For nuclear materials, it is important to understand how irradiation and high temperatures affect mechanical properties such as strength and toughness. Neutron irradiated materals can be extracted from operating reactors or obtained from Material Test Reactors that simulate the conditions of future fission and fusion systems. This imposes very significant contraints on specimen size (typically < 1 cm). The structural properties of engineering materials, such as the non-linear relationship between strain and stress as mechanical damage occurs, are usually measured using standard tests. These are not suitable for such small specimens, so new methods are needed to obtain data to evaluate novel materials, for new reactor designs and also to monitor material performance for the safety of operating reactors.
One approach to interpret small-specimen tests is to develop material models that relate experimental measurements of the full field deformations (total and elastic strains) to the applied boundary conditions (load and displacements). The total strain field can be measured using image correlation (applied to in situ 2D optical observations or 3D X-ray tomographs), and X-ray or neutron diffraction can map the elastic strain fields. Inverse modelling approaches of increasing levels of sophistication may then extract the materials stress/strain relationship and its evolution with mechanical damage. This approach has the potential to be applied under extreme conditions of temperature and irradiation. The developed material models can then be used to assess the structural integrity and safety of engineering components under realistic conditions.
The aim of this project is to develop and apply efficient numerical optimisation methods to extract material properties by inverse modelling from 2D and 3D displacement fields, measured in situ. The materials studied will include nuclear graphite, carbon-carbon composites and carbon-silicon carbide composites, with the objective of developing a better understanding of the relationships between microstructure, damage and mechanical properties. The experimental techniques will include digital image correlation, X-ray tomography and X-ray/neutron diffraction, which may be applied at high temperatures with irradiated materials. Modelling and optimisation approaches will include finite element methods, virtual fields and machine learning.
The project is suitable for graduates with an engineering, mathematical or physics/materials background.