The use of probabilistic design techniques in high-integrity applications in regulated industries

Brief Description

(from Mr Friebe's thesis)

Survivability is the ability of a naval vessel to survive a combat incident by avoiding (susceptibility), withstanding (vulnerability) or recovering (recoverability). Vulnerability assessment is often divided into the structural and system vulnerability assessment.
System vulnerability assessments are traditionally performed using manually built fault and success trees that model a simplified version of the functional failure relationships. This traditional approach has been very limiting, but more accurate and realistic methods were too computationally expensive to use.
Furthermore, traditional vulnerability assessments also assume that the onboard systems are perfectly reliable and fully functional, which is a further simplification that may have significant consequences on vulnerability assessments. System reliability has never been included in traditional vulnerability assessment methods mainly due to the limitation in available computational power. However, with increasing readily available computing power, such enhancements are now realisable.

Scope of the work

The following questions would need to be answered:

  • What is the state of the art in vulnerability assessment and how does one conduct a contemporary vulnerability assessment with the available tools?
  • Can the Bayesian machine learning algorithm be used to automatically investigate the vulnerability performance of a vessel during the detail design stage?
  • Can the developed framework and Bayesian Network be extended with system reliability values to model the aging effect of the vulnerability performance of the naval vessel?

Which SEA program would benefit and how?

Would benefit SEA1180.