Probabilistic Safety Analysis Methods for Applications in Nuclear Technologies

The ability to correctly make safety-related decisions and to demonstrate compliance with existing limits is of great importance in the nuclear safety analysis industry. For example, we may be interested to assess whether or not a physical component (such as the pressure tube which carries fuel) has undergone physical changes that have exceeded its allowable limits. The problem relies on the development of models that involve parameters describing such components and to use the models to predict and assess whether the parameter has become non-compliant. These predictive models are based on (imperfect) experimental data or complex computational codes. Thus, these physical parameters are considered as random variables that are subject to uncertainties (e.g., stochastic and epistemic uncertainties) that affect our ability to make safety-related decisions. The objective of this project will be to investigate the development of methods and tools required to demonstrate the statistical basis for reaching decisions that are consistent with the so-called 95/95 industry standard.

Faculty Supervisor:

Dr. Fred Hoppe

Student:

Dan Quach

Partner:

AMEC Nuclear Safety Solutions

Discipline:

Mathematics

Sector:

Energy

University:

McMaster University