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Reliable digital simulation tools for improved resilience in Nuclear Power Plants

Project Description

The aim of the project is to develop fast and robust probabilistic risk assessment tools able to cope with lack of data and expert judgements. These tools will take advantages of the use of modern techniques such as generalized probabilistic methods, including fuzzy analysis, evidence theory, random set theory. Such models require in turn the availability of efficient uncertainty quantification tools required to estimate the probability of occurrence of the events and their consequences.

There is growing evidence that natural disasters from extreme large natural events such e.g. earthquakes, tsunami and flooding have the potential to simultaneous failures (cascading failures) in Nuclear Power Plants leading to severe accident and potential disasters. The Fukushima accident has shown the consequences of such events. Nuclear Power Plants are complex and highly interconnected system and during accident the exact status of the system is often unknown or identified based on few data, sometimes contradicting information and expert judgements.

Although based on vague and scarce data the most robust decision need to be taken in order to mitigate the consequences of nuclear accidents. This in turn requires the availability of robust supporting decision tools. In fact, in engineering practice, the evaluation of risk is often performed adopting over-simplified models which reduce considerably the credibility of the predictions in quantitative terms. Research is therefore required to develop more accurate models for risk assessment that are able to identify features, events and processes that influence the system integrity.

The project requires a sound mathematical background, curiosity, creativity and a strong interest to work with a multi-disciplinary research group. Applicants should have a background in relevant fields from Engineering. The student will join a multi-disciplinary research group in the Institute for Risk and Uncertainty at the University of Liverpool and Department of Engineering and System Science at National Tsing Hua University.

This project is part of a 4 year Dual PhD degree programme between the National Tsing Hua University (NTHU) in Taiwan and the University of Liverpool in England. As Part of the NTHU-UoL Dual PhD Award students are in the unique position of being able to gain 2 PhD awards at the end of their degree from two internationally recognised world leading Universities. As well as benefiting from a rich cultural experience, Students can draw on large scale national facilities of both countries and create a worldwide network of contacts across 2 continents.

All of the projects undertaken on the Dual PhD are aimed at working towards the UN’s Global Goals for Sustainable Development. In 2015 World leaders agreed to 17 goals for a better world by 2030. These goals are aimed at ending poverty, fighting inequality and stopping climate change. This project is specifically targeted at Goal 9 – to build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation.

When applying please ensure you Quote the supervisor & project title you wish to apply for and note ‘NTHU-UoL Dual Scholarship’ when asked for details of how plan to finance your studies.

Funding Notes

This project is a part of a 4-year dual PhD programme between National Tsing Hua University (NTHU) in Taiwan and the University of Liverpool in England. It is planned that students will spend the 2 years at the University of Liverpool, followed by 2 years at NTHU.
Both the University of Liverpool and NTHU have agreed to waive the tuition fees for the duration of the project and stipend of TWD 10,000/month will be provided as a contribution to living costs (the equivalent of £280 per month when in Liverpool).


For academic enquires please contact Dr Edoardo Patelli ([email protected]) or Dr Min Lee ([email protected])

For enquires on the application process or to find out more about the Dual programme please contact [email protected]

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