Projects at Liverpool

These projects are run by Liverpool University. Application information can be found in their how to apply section. Please contact the relevant person below before applying. Click on the titles below to see contact details and more information.

  • Crystallography and thermophysical properties of fission products with coherent domains

    Nuclear fission by its very nature induces change, i.e. transmutation of elements, how a structure accommodates this change is vital to the long-term stability of nuclear fuel. Current nuclear fuel is based on UO2, adopting the cubic fluorite structure, many fission products are soluble within this structure, and can give rise to new phases being formed. These new phases will impact fuel performance, through modification of thermophysical properties, thus potentially reducing the ability of the fuel to be used within the core longer term. The project examines the impact arising from the formation of phases which form as precipitates in the fuel, with a structure formed from ‘non-equilibrium’ synthesis.

    The formation of fission products within fuel, dramatically impacts both the thermophysical and structural response coupling in many cases with the induced radiation damage. For example, not only will fuel
    experience change in microstructure through formation of gas bubbles, but such change induces a reduction in thermal conductivity, which leads to heat being retained within the fuel. Fission product formation within the fuel can either be soluble, or insoluble, with each having differing impact on behaviour. For many fission products there is a miscibility gap in solubility. For example, in the systems U-Ln-O, the miscibility gap gives rise to the formation of new phases, forming coherent domains within the broader matrix. Domain behaviour, and formation is not fully understood and is ripe for further examination.


    Contact: Dr Maulik Patel

  • The role of virtual reality and social network analysis in delivering nuclear infrastructure projects

    Virtual reality, especially in the form digital twins[1],[2] is being used increasingly by designers to develop what is called “optimised design” of significant nuclear infrastructure projects.  Digital twins are computational representations of individual physical systems that can be used to inform all phases of a typical plant lifecycle.  Scientists and engineers recognise that the successful implementation of virtual reality will require new ways to gather process and share increasingly large volumes of data.  This is a particular challenge where projects are highly distributed and delivered in collaboration with multiple international partners as is typical of many next generation nuclear facilities[3].  The aim of this project will be to study the ways in which science and engineering can obtain maximum benefit from the adoption of virtual reality and the digital twin concept under such circumstances.  The research will include considering the role of the digital twins and the ways in which communication and collaboration can be enhanced through the creation of social networks within the design process.  The potential for applying social network analysis[4] will be examined within the nuclear context and how this might enhance both the effectiveness and efficiency of the “optimised design” process.  We intend to develop a methodology in this project that can be tested and demonstrated using case studies developed in collaboration with the nuclear energy industry.

    [1] De Lange, C., 2014, Meet your unborn child – before it’s conceived, New Scientist, 12 April 2014, p.8.

    [2] Glaessgen, E.H., & Stargel, D.S., 2012, The digital twin paradigm for future NASA and US Air Force vehicles, Proc 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, AIAA paper 2012-2018, NF1676L-13293

    [3] Patterson, E.A., Taylor, R.J. & Bankhead, M., A framework for an integrated nuclear digital environment, Progress in Nuclear Energy, 87:97-103, 2016

    [4] Wu D, Rosen DW, Panchal JH & Schaefer D, Understanding communication and collaboration in social product development through social network analysis, ASME J. Computing Information Science in Engineering, 16:01101, 2016.


    Contact: Prof Eann Patterson


  • Experimental characterisation of the development of plasticity in nuclear reactor steels

    Very recently, it has been demonstrated that metal fatigue in aerospace alloys can be detected using optical second harmonic generation. Second harmonic generation or frequency doubling occurs when photons interact with a non-linear material and are combined to produce new photons with twice the energy and hence twice the frequency and half the wavelength of the original photons. In this research, second harmonic generation was found to occur at material interfaces associated with dislocations in the material’s atomic structure that accumulate and coalesce into cracks. In particular, polarisation measurements were markedly different in the plastic zone ahead of a crack tip compared to virgin areas of the material, which implies that second harmonic polarisation analysis could be useful in non-invasive analysis of fatigue cracks. In this project, the technique will be extended to steels used in reactor pressure vessels with a view to elucidating our understanding of the development of the crack tip plastic zone during the load cycling. This will involve identifying the characteristics of polarisation second harmonic generation associated with fatigue damage in steels and establishing portable instrumentation that will allow in-situ measurements during fatigue tests. Comparison of the resultant measurements will be made with existing techniques, such as thermoelastic stress analysis and scanning electron microscopy.

    Contact: Dr Heike Arnolds

  • Robust Validation Methods for Computational Fluid Dynamics Models of Waste Flows

    Establishing credibility in engineering simulations through a process of model validation is an essential part of any engineering analysis. It is well-established that validation of computational models should include a comparison of predictions from the simulation with measurements from a physical experiment or prototype that closely resembles the conditions in service, i.e. real-world, everyday circumstances. Advances in digital sensor technology allow information-rich data fields to be acquire in real-time leading to large quantities of measured data, sometimes referred to as ‘big data’, which presents challenges in making quantitative and meaningful comparisons with predictions from simulations. In solid mechanics, Patterson and his co-workers have used orthogonal decomposition to reduce the dimensionality of both measured and predicted data to feature vectors that can readily be compared. This process is becoming routine for two-dimensional fields of data and is being developed for volumes of data. In both cases, feature vectors representing measurements and predictions can be compared to establish the probability that they belong to the same population. In this project these techniques will be extended to fluid dynamics, and in particular to fluid flows of interest in nuclear plant (i.e. slurry transport), based on current experimental work being pursued by Dennis and his co-workers in collaboration with the National Nuclear Laboratory. It is expected that the outcome will be a significant advance in the rigour with which simulations based on computational fluid dynamics models can be validated through detailed comparison to measurements and that this will enable updating of simulations to increase their fidelity.


    Contact: Dr David Dennis

  • Quantitative validation of a mechanistic model of nuclear graphite degradation

    Graphite acts as a moderator and a structural component in Advanced Gas-cooled Reactors (AGR). During operation, mechanical properties of polycrystalline graphite change due to irradiation and this can negatively affect the safety of the reactor. Empirical computational models are widely used to study and to extrapolate the changes in mechanical properties of the graphite subject to irradiation. The challenge is in combining mechanistic principles at different scales to define a realistic behaviour of the polycrystalline agglomerate. Further research on material modelling to understand the underpinning behaviour is necessary and will form part of the research project. In order to implement novel models, a certain degree of confidence in the predictions of the simulation has to be achieved through validation. There are different approaches to validation of computational mechanics models, but no methodology is commonly accepted. The need to quantify the quality of the model relative to reality, has stimulated initial research on Frequentist and Bayesian approaches but more in-depth research is required to account for data sparsity. In the current project, research on a novel validation metric will be performed and will support research on material modelling. The outcome is expected to provide evidence for the trustworthiness of improved predictions by incorporating uncertainty analysis and probabilistic statistics.


    Contact: Prof Eann Patterson


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