  Simulation-based probabilistic risk assessment (SPRA) is a systematic and
comprehensive methodology that has been used and refined over the past few
decades to evaluate the risks associated with complex systems. SPRA models are
well established for cases with considerable data and system behavior
information available. In this regard, multiple statistical and probabilistic
tools can be used to provide a valuable assessment of dynamic probabilistic
risk levels in different applications. This tutorial presents a comprehensive
review of SPRA methodologies. Based on the reviewed literature, SPRA methods
can be classified into three categories of dynamic probabilistic logic methods,
dynamic stochastic analytical models, and hybrid discrete dynamic event and
system simulation models. In this tutorial, the key strengths and weaknesses,
and suggestions on ways to address real and perceived shortcomings of available
SPRA methods are presented and discussed.
