Ander Gray graduated from Queen's University Belfast in 2017 in Physics, and has been a student at the Institute for risk and uncertainty since October of 2017.
Ander's work mainly revolves around Monte Carlo methods for particle transport, uncertainty propagation, and Bayesian analysis. His background in Physics was in atomic simulation, computation of the electronic structure of matter using Density Functional Theory.
Monte Carlo Simulation, Bayesian Analysis, Validation, Neutron Transport
Research project title: Quantification of Nuclear Data Uncertainy in Fusion Neutronics
Project description: Neutronics is the study of how neutrons propagate through matter: how they interact, what with, and their manipulation. It is a basic branch of fusion research. Fusion neutrons must be used in tritium breeding and will be an energy production mechanism through energy deposition blankets. Neutronics will also bring control over hazards like radiation exposure and waste production, key to the success of experimental reactors and future power stations. The Nuclear Data governing how neutrons interact with matter is the main ingredient in any neutronics calculation, yet is very uncertain. A lacking of experimental data for the vast majority of nuclear reactions has resulted in nuclear data being produced with an inherent uncertainty value. The impact of Nuclear Data uncertainty is exaggerated in fusion since the number of nuclides and materials used is more diverse than fission. This projects primary aim is to study the impact this uncertainty has on ITER scale neutronics problems. To reach this goal, efficient methods for uncertainty propagation in neutron transport codes will be developed, as current methods are too computationally intractable for ITER scale simulations in the majority of situations.
Supervisory team: Edoardo Patelli (Risk Insititute), Andrew Davis (CCFE)