A probabilistic relational model for risk assessment and spatial resources management

Abstract

Fault tree (FT) model is one of the most popular techniques for probabilistic risk analysis of large, safety critical systems. Probabilistic graphical models like Bayesian networks (BN) or Probabilistic Relational Models (PRM) provide a robust modeling solution for reasoning under uncertainty. In this paper, we define a general modeling approach using a PRM. This PRM can represent any FT with possible safety barriers, spatial information about localization of events, or resources management. In our proposed approach, we define a direct dependency between the resources allocated to one location and the strength of the barriers related to this same location. We will show how this problem can be fully represented with a PRM by defining its relational schema and its probabilistic dependencies. This model can be used to estimate the probability of some risk scenarios and to assess the presence of resources on each location through barrier’s efficiency on risk reduction.