Exploiting the capabilities of bayesian networks for engineering risk assessment: Causal Reasoning through interventions
Author
dc.contributor.author
Ruiz-Tagle, Andrés
Author
dc.contributor.author
López Droguett, Enrique Andrés
Author
dc.contributor.author
Groth, Katrina M.
Admission date
dc.date.accessioned
2021-11-05T14:26:41Z
Available date
dc.date.available
2021-11-05T14:26:41Z
Publication date
dc.date.issued
2021
Cita de ítem
dc.identifier.citation
Risk Analysis, 2021
es_ES
Identifier
dc.identifier.other
10.1111/risa.13711
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/182615
Abstract
dc.description.abstract
In the last decade, Bayesian networks (BNs) have been widely used in engineering risk assessment
due to the benefits that they provide over other methods. Among these, the most
significant is the ability to model systems, causal factors, and their dependencies in a probabilistic
manner. This capability has enabled the community to do causal reasoning through
associations, which answers questions such as: “How does new evidence x about the occurrence
of event X change my belief about the occurrence of event Y?” Associative reasoning
has helped risk analysts to identify relevant risk-contributing factors and perform scenario
analysis by evidence propagation. However, engineering risk assessment has yet to explore
other features of BNs, such as the ability to reason through interventions, which enables the
BN model to support answering questions of the form “How does doing X = x change my
belief about the occurrence of eventY?” In this article, we propose to expand the scope of use
of BN models in engineering risk assessment to support intervention reasoning. This will provide
more robust risk-informed decision support by enabling the modeling of policies and actions
before being implemented. To do this, we provide the formal mathematical background
and tools to model interventions in BNs and propose a framework that enables its use in
engineering risk assessment. This is demonstrated in an illustrative case study on third-party
damage of natural gas pipelines, showing how BNs can be used to inform decision-makers
about the effect that new actions/policies can have on a system.
es_ES
Lenguage
dc.language.iso
en
es_ES
Publisher
dc.publisher
Wiley
es_ES
Type of license
dc.rights
Attribution-NonCommercial-NoDerivs 3.0 United States