High Fidelity Computational Nuclear Engineering

Lead Research Organisation: University of Leeds
Department Name: Chemical and Process Engineering

Abstract

The project will focus on combining computational multi-disciplinary approaches to obtain solutions to a range of generic nuclear systems such as fuel fluid flow reprocessing, mixer settler and liquid-liquid extraction columns encountered in the industry for decommissioning and waste management. Given the fundamental nature of such numerical solutions, the information derived from them will also be analysed to provide improved understanding of a range of practically relevant systems, of value in the design of improved treatment methods.

The key aim is to extend a predictive model, based on multi-disciplinary simulations, to include optimisation approaches such design of experiment and surrogate modelling techniques, capable of predicting the types of thermal fluid flow systems encountered in nuclear.

The outcomes of the project will be a series of surrogate models which are useful in providing fundamental understanding of such systems, as well as being available for use in the validation of the predictive approaches used within the industry. The latter, in particular, gives those using simplified predictive techniques the opportunity to reinforce their quality assurance and technical excellence credentials by getting involved in an initiative that removes the potential for error due to the necessary approximations applied in modelling.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509681/1 01/10/2016 30/09/2021
1787184 Studentship EP/N509681/1 01/10/2016 28/02/2020 Daniel Wesley Theobald