TY - GEN
T1 - DYNAMIC CREDAL NETWORKS FOR RESILIENCE ASSESSMENT OF COMPLEX ENGINEERING SYSTEMS
AU - Estrada-Lugo, Hector Diego
AU - Santhosh, T. V.
AU - Patelli, Edoardo
N1 - Publisher Copyright:
© ESREL 2021. Published by Research Publishing, Singapore.
PY - 2021
Y1 - 2021
N2 - Complex engineering systems are of paramount importance for the correct operation of installations that allow functioning of the modern society and its economy. These systems are constantly under uncertain and potentially damaging conditions that may alter their operational performance. New system designs should consider safety aspects that maintain safe operating conditions while coping with disruptive events. In response to this need, the relatively new discipline of resilience engineering has been formulated to improve the safety of such complex systems. Resilience assessments must be carried out to study the system recovery after a disruptive event has occurred. Probabilistic models like fault tree or event tree analyses have been widely applied in safety-critical sectors such as process and/or nuclear industry due to their flexibility to model complex engineering systems and uncertainty quantification. However, such techniques moderate the modelling scope when representing the interdependencies of the components in the system and variations in time over a disruption event. Moreover, additional complications in the resilience assessment process arise when considering the epistemic uncertainty due to the lack of knowledge about the events and the operating conditions. Dynamic credal networks are proposed in this work to model complex systems whose performance evolves in time. The methodology aims to quantify resilience in terms of the availability of the components. The novelty of this work resides in the development of a resilience assessment framework that allows taking into account the epistemic uncertainty related to the sparse or defective data. The resilience assessment of the key safety systems of an Advanced Thermal Reactor is carried out to evaluate the system recovery after a mishap adopting the dynamic credal network approach. The application of the proposed approach to producing a resilience analysis is described and results presented to demonstrate the applicability of the method.
AB - Complex engineering systems are of paramount importance for the correct operation of installations that allow functioning of the modern society and its economy. These systems are constantly under uncertain and potentially damaging conditions that may alter their operational performance. New system designs should consider safety aspects that maintain safe operating conditions while coping with disruptive events. In response to this need, the relatively new discipline of resilience engineering has been formulated to improve the safety of such complex systems. Resilience assessments must be carried out to study the system recovery after a disruptive event has occurred. Probabilistic models like fault tree or event tree analyses have been widely applied in safety-critical sectors such as process and/or nuclear industry due to their flexibility to model complex engineering systems and uncertainty quantification. However, such techniques moderate the modelling scope when representing the interdependencies of the components in the system and variations in time over a disruption event. Moreover, additional complications in the resilience assessment process arise when considering the epistemic uncertainty due to the lack of knowledge about the events and the operating conditions. Dynamic credal networks are proposed in this work to model complex systems whose performance evolves in time. The methodology aims to quantify resilience in terms of the availability of the components. The novelty of this work resides in the development of a resilience assessment framework that allows taking into account the epistemic uncertainty related to the sparse or defective data. The resilience assessment of the key safety systems of an Advanced Thermal Reactor is carried out to evaluate the system recovery after a mishap adopting the dynamic credal network approach. The application of the proposed approach to producing a resilience analysis is described and results presented to demonstrate the applicability of the method.
KW - Dynamic Credal Networks
KW - Imprecise Data Sets
KW - Resilience Engineering
KW - Safety Critical Systems
UR - http://www.scopus.com/inward/record.url?scp=85135454220&partnerID=8YFLogxK
U2 - 10.3850/978-981-18-2016-8_771-cd
DO - 10.3850/978-981-18-2016-8_771-cd
M3 - Conference contribution
AN - SCOPUS:85135454220
SN - 9789811820168
T3 - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
SP - 613
BT - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
A2 - Castanier, Bruno
A2 - Cepin, Marko
A2 - Bigaud, David
A2 - Berenguer, Christophe
PB - Research Publishing, Singapore
T2 - 31st European Safety and Reliability Conference, ESREL 2021
Y2 - 19 September 2021 through 23 September 2021
ER -