The aim of the project is to support the development of the R6 assessment procedure by improving the understanding of two failure mechanisms of thin shell components. These mechanisms are fracture and plastic collapse. It will add to knowledge of limits and conditions for the occurrence of fast fracture. To decide the conditions for testing, for example loading, Finite Element Analysis (FEA) will be used. This will ensure that the relevant region between stable and unstable fracture is investigated. The JR curve of the material will be generated along with a tabulation of stress-strain data. The data will establish relevance for the project to the nuclear industry. After this initial stage samples will be prepared with thickness between 0.5-1 mm. The relevant loading conditions for this type of material is a cylinder under pressure. This will be simulated at the University of Bristol using the biaxial testing rig that has been constructed. Defects to represent corrosion and puncturing can be introduced. The method of creating the defect in the sample is still being considered and could be extended to study a weld as well as the material itself. Digital Image Correlation (DIC) can be used to find surface stress field and output a value of K, the stress intensity factor. The method developed in part at the University of Bristol is novel, it involves autonomously measuring the displacement field using DIC and identifies cracks which have occurred. A Finite Element (FE) mesh is then automatically generated for the area in close proximity to the crack. The technique known as phase congruency is used to automatically segment the crack to give an intrinsic resolution less than a pixel. A number of tests will be performed under different conditions including a range of pressures and material properties. This will enable understanding of methods of failure, for example plastic collapse, fast fracture and mixed mode failure. The R6 assessment method that will be used at the start of the project, to perform an assessment for the thin shell samples, will develop skills and understanding of this assessment method as well as being a useful part of the project.