Probabilistic Safety Analysis Methods for Applications in NuclearTechnologies

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:

Fred Hoppe

Student:

Partner:

AMEC (St. John's, NL)

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

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