Dynamic Probabilistic Risk Assessment

Tarannom Parhizkar (), Ingrid B. Utne () and Jan-Erik Vinnem ()
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Tarannom Parhizkar: Norwegian University of Science and Technology
Ingrid B. Utne: Norwegian University of Science and Technology
Jan-Erik Vinnem: Norwegian University of Science and Technology

Chapter Chapter 2 in Online Probabilistic Risk Assessment of Complex Marine Systems, 2022, pp 17-39 from Springer

Abstract: Abstract In this chapter, definitions of important terms related to online probabilistic risk assessmentOnline probabilistic risk assessment are clarified (Sect. 2.1). In Sect. 2.2, dynamic, real-time, and online risk assessmentsOnline risk assessment are defined. In Sect. 2.3, methods for online risk assessmentOnline risk assessment such as hazard identificationHazard identification, event sequence diagramsEvent sequence diagram (ESDs), fault tree analysisFault tree analysis (FTA), and hybrid methodsHybrid method are presented. In addition, in this subsection, the online risk assessmentOnline risk assessment methodology for autonomousAutonomous systems is more clarified by applying the method in a case studyCase study. In Sect. 2.4, methods for dynamic probabilistic risk assessmentDynamic probabilistic risk assessment of complex systemsComplex systems including dynamic event sequence diagramsDynamic event sequence diagrams (DESDs), Markov chainsMarkov chain, dynamic fault treesDynamic fault tree, and dynamic Bayesian networksDynamic bayesian network are presented and discussed. Finally, in Sect. 2.5, the challengesChallenges of available methods are discussed; and possible solutions to overcome these challengesChallenges are proposed. Integrating predictive and optimizationOptimization algorithmsAlgorithm, as well as simulation, with risk assessmentRisk assessment may result in more powerful risk assessmentRisk assessment methods for complex systemsComplex systems.

Date: 2022
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DOI: 10.1007/978-3-030-88098-9_2

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