Probabilistic Safety Analysis Methods for Application in Nuclear Technologies

The ability to make safety-related decisions and to demonstrate compliance with regulatory or safety limits is of great importance in the nuclear industry. For example, we may be interested to assess whether a component (such as the pressure tube which carries fuel) has undergone physical changes that have exceeded its allowable limits (e.g., the pressure tube has expanded in the radial direction due to irradiation effects). 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 built using (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) 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 95/95 industry standard.

The development of advanced mathematical and statistical applications are used in supporting and enhancing AMEC NSS’s wide range of services in the areas of thermal hydraulics analysis, reactor physics analysis and operational support. The products from AMEC NSS are directly related to supporting and ensuring the safe operation of the Nuclear Generations in Ontario (e.g., Ontario Power Generation, Bruce Power).

Faculty Supervisor:

Dr. Fred Hoppe

Student:

Dan Quach

Partner:

AMEC Nuclear Safety Solutions

Discipline:

Statistics / Actuarial sciences

Sector:

Energy

University:

McMaster University