BibTeX

@inproceedings{RoelenPSAM2008,
title = {Development and Validation of a Comprehensive Hybrid Causal Model for Safety Assessment and Management of Aviation Systems},
author = {Alfred Roelen and Rombout Wever and Ali Mosleh and Katrina Groth},
editor = {Enrico Zio and Vincent Ho and Tsu-Mu Kao},
year = {2008},
date = {2008-05-01},
booktitle = {Proceedings of the International Conference on Probabilistic Safety Assessment and Management (PSAM 9)},
address = {Hong Kong},
abstract = {The United States Federal Aviation Administration (FAA) has initiated the development of a causal risk model of commercial air transport in support of the System Approach for Safety Oversight (SASO) program. The model uses the so-called Hybrid Causal Logic (HCL) methodology which combines Event Sequence Diagrams (ESD), fault trees (FT) and Bayesian Belief Networks (BBN). The model is hierarchically structured: it includes 31 generic ESDs covering accident scenarios in various phases of flight at the top-level of the model, supported by numerous fault trees and BBNs to represent deeper causes of the ESD events. BBNs are used to extend the causal chain of events to potential human and organizational roots. Probabilities of the HCL models are obtained from extensive review and classification of commercial aviation accident/incident databases. A number of FAA operations research analysts, principal inspectors, and other experts actively participated in review and validation of the model development. A dedicated software prototype (IRIS) has been developed that simultaneously supports model development and model application.},
keywords = {aviation, Bayesian Networks, causal models, IRIS, Probabilistic risk assessment (PRA), Quantitative risk assessment (QRA), transportation safety},
pubstate = {published},
tppubtype = {inproceedings}
}

Abstract

The United States Federal Aviation Administration (FAA) has initiated the development of a causal risk model of commercial air transport in support of the System Approach for Safety Oversight (SASO) program. The model uses the so-called Hybrid Causal Logic (HCL) methodology which combines Event Sequence Diagrams (ESD), fault trees (FT) and Bayesian Belief Networks (BBN). The model is hierarchically structured: it includes 31 generic ESDs covering accident scenarios in various phases of flight at the top-level of the model, supported by numerous fault trees and BBNs to represent deeper causes of the ESD events. BBNs are used to extend the causal chain of events to potential human and organizational roots. Probabilities of the HCL models are obtained from extensive review and classification of commercial aviation accident/incident databases. A number of FAA operations research analysts, principal inspectors, and other experts actively participated in review and validation of the model development. A dedicated software prototype (IRIS) has been developed that simultaneously supports model development and model application.