Dr Nathaniel Read

Dr Nathaniel Read is now a research associate in the Nuclear Energy Group at the Department of Engineering.

Sponsor: EPSRC and National Nuclear Laboratory

Nuclear electric propulsion with low enriched uranium

The use of nuclear fission power systems in space is essentially unavoidable unless we accept a significant reduction in aspiration for space exploration. The availability of solar power diminishes with distance; in orbit around Jupiter the solar intensity is only around 4% of that around Earth. Deep space exploration is therefore very challenging without nuclear power. Even in the inner solar system, solar power does not provide the power levels or consistency required for many mission types, including the manned exploration of Mars or establishing a more permanent presence on the Moon.

My PhD research considered the implications for space nuclear power systems (intended principally for in-space propulsion) of using low-enriched uranium, in line with the internationally-agreed limit of 19.75% enrichment, rather than highly-enriched uranium which has historically been the fuel of choice for space power systems.

Since graduation

The focus of my postdoctoral work has been on nuclear safety and risk. My initial research focussed on the investigating safety claims made by designers of new ‘small modular reactors’. In particular, their probabilistic safety analyses arrive at accident frequencies which are several orders of magnitude lower than even the very latest large reactor designs such as the EPR currently being built at Hinkley Point C. They predict, for example, a frequency of releasing large amounts of radiation of once in ten billion years, which is comparable with the age of the universe. The research has considered several questions: Are such claims correct on their own terms? What assumptions underlie these analyses and are they reasonable? Are these probabilistic methods valid and meaningful at this level of frequency? Are they undermined by common-cause failure modes or human failure? What do more novel methods, such as system-theoretic approaches, have to contribute to this area? My experience as an actuary has been invaluable in this research, as I am comfortable with assessing and quantifying risk, whilst approaching the subject as something of an outsider who has fewer preconceptions.

My present work is concerned with detecting the early signs of nuclear power station decline, whether technical or organisational, that could lead to an accident. Following the Chernobyl accident, it was recognised that a single incident can have global consequences, leading to the establishment of the World Association of Nuclear Operators (WANO). This organisation conducts periodic reviews of the global nuclear power station fleet and collects data on operational incidents, including those that are relatively minor. My current postdoctoral work, funded by WANO, seeks to apply modern machine learning techniques to this dataset to attempt to detect early signs of station decline that could lead to an accident. This vein of thinking emerged after the Three Mile Island incident, after which it became clear that focussing on seemingly small operational details can greatly reduce the probability of large accidents as well improving plant reliability and economics. My research continues in the same philosophy but with the modern advantages of large datasets and the tools to understand them.

I am involved in several aspects of the Nuclear Energy MPhil course, leading the modules on Nuclear Safety and Advanced Fission and Fusion Systems and coordinating the MPhil project selection process. I supervise MPhil projects in the areas of reactor design, particularly for space systems, and nuclear safety.