Multi-physics reactor optimisation coupled with uncertainty quantification

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The modelling of nuclear reactor systems is one of the most challenging tasks in complex system modelling, due to the many different scales and coupled physical phenomena involved. The task is further complicated if efforts are also made to account for the unavoidable uncertainties in nuclear data, operating conditions, manufacturing tolerances, changes with age etc. With advances in the capabilities of codes and in the availability of high performance computing resources, it is now possible to undertake such analyses as one-off calculations, but the computational cost of performing such analyses many times within a design optimisation process remains prohibitive. To facilitate design optimisation computationally cheaper models must be employed. Such models can be surrogates built using a limited number of high-fidelity (computationally expensive) simulations or lower-fidelity models based on simplified physics. This project will explore ways in which state-of-the-art approaches to surrogate modelling and multifidelity analysis can be employed to facilitate multi-physics analysis and design optimisation of nuclear systems.