Callum BarltropPhD student
Extreme Value Theory
Multivariate Extremes for Nuclear Regulation
I joined the STOR-i programme in 2018 straight after graduating from Lancaster University with a BSc Hons in Mathematics, for which I took a range of pure and statistics modules. I also completed the STOR-i internship in the summer of 2017, which motivated me to sign up for the CDT. I am now in the first year of my PhD, where I am supervised by Jenny Wadsworth from Lancaster University, and Aidan Parkes and Tanya MacLeod from the Office for Nuclear Regulation.
For my research, I am considering ways to apply multivariate extreme value theory in the context of nuclear regulation.
The Office for Nuclear Regulation (ONR) is responsible for the regulation of nuclear safety and security of GB nuclear licensed sites. ONR’s Safety Assessment Principles (SAPs, http://www.onr.org.uk/saps/saps2014.pdf) expect nuclear installations to be designed to withstand natural hazards with a return frequency of one in 10,000 years, conservatively defined with adequate margins to failure and avoiding ‘cliff-edge’ effects. This involves extrapolating beyond the observed range of data. A statistical framework is used to model and estimate such events.
For my PhD project, I am working with the ONR to investigate methods for applying multivariate extreme value theory. In particular, I am looking at techniques for estimating ‘hazard curves’ (graphs of frequency and magnitude) for combinations of natural hazards that could inform the design bases for nuclear installations. I am also considering new methods for incorporating factors such as climate change and seasonal variability into the analysis of environmental data.
- Extreme Value Statistics
- STOR-i Centre for Doctoral Training