BibTeX

@inproceedings{GrothRAMS2008,
title = {Hybrid Methodology and Software Platform for Probabilistic Risk Assessment},
author = {Katrina Groth and Dongfeng Zhu and Ali Mosleh},
doi = {10.1109/RAMS.2008.4925831},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of the Annual Reliability and Maintainability Symposium (RAMS 2008)},
address = {Las Vegas, NV},
abstract = {This paper introduces the software implementation of a hybrid methodology for probabilistic risk assessment (PRA) of complex systems. The software, called IRIS (Integrated Risk Information System) combines a user-friendly graphical interface with a powerful computational engine. The framework includes a multi-layered modeling approach, combining Event Sequence Diagrams, Fault Trees, and Bayesian Belief Networks in a Hybrid Causal Logic (HCL) model. This allows the most appropriate modeling techniques to be applied in the different domains of the system. At its core IRIS brings related perspectives of system safety, hazard analysis, and risk analysis into a unifying framework.},
keywords = {Bayesian Networks, hazard identification, Probabilistic risk assessment (PRA), Quantitative risk assessment (QRA), software},
pubstate = {published},
tppubtype = {inproceedings}
}

Abstract

This paper introduces the software implementation of a hybrid methodology for probabilistic risk assessment (PRA) of complex systems. The software, called IRIS (Integrated Risk Information System) combines a user-friendly graphical interface with a powerful computational engine. The framework includes a multi-layered modeling approach, combining Event Sequence Diagrams, Fault Trees, and Bayesian Belief Networks in a Hybrid Causal Logic (HCL) model. This allows the most appropriate modeling techniques to be applied in the different domains of the system. At its core IRIS brings related perspectives of system safety, hazard analysis, and risk analysis into a unifying framework.