Modular Approach for Probabilistic Safety Assessment of Systems with Multiple Failure Modes

Probabilistic safety assessment (PSA) becomes quite difficult for the complex systems with different failure modes that are represented by Markov processes characterized by a large number of states and transitions. In order to overcome the complexity of this problem, we propose to build the Markov processes corresponding to each failure mode separately and to assess it's safety by the theory of p-languages. Further we can use the choice operator to model the system that incorporates multiple failure modes and to assess its safety performances.