Uncertainty Quantification in Fault Tree Analysis
Estimating Business Interruption due to Seismic Hazard
Bibliographic Data
| ID | 21738532 |
|---|---|
| Authors | Saurabh Prabhu (0000-0002-9799-4157, American International Group (United States)), Carl Ehrett (0000-0002-0711-0347, Clemson University), Mohammad Javanbarg (American International Group (United States)), D Andrew Brown (0000-0003-2715-7190, ORCID), Marc Lehmann (American International Group (United States)), Sez Atamturktur (0000-0003-3653-1260, Pennsylvania State University, corresponding author) |
| Year | 2020 |
| Volume | 21 |
| Issue | 2 |
| Publication date | 2020-05-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Natural Hazards Review (JOURNAL) |
| Journal identifiers | ISSN: 1527-6988 • E-ISSN: 1527-6996 |
| Publisher | American Society of Civil Engineers (ASCE) (PUBLISHER • US) |
| DOI | 10.1061/(asce)nh.1527-6996.0000360 |
| OpenAlex | W3008956430 |
| Language | EN |
| Citations received | 3 |
| References cited | 66 |
This paper presents an approach based on fault tree analysis and subset simulation for quantifying uncertainty in the risk assessment of complex industrial facilities. Downtime estimation of industrial facilities after an extreme event is critical for risk valuation, as business interruption contributes significantly to monetary losses. Industrial facilities are complex systems with many critical, interdependent components. Such facilities are thus amenable to modeling using fault trees. Fault tree analysis breaks down a facility’s layout into system components and links component failure probabilities through Boolean logic to estimate the larger system’s failure probability. In estimating system failure probability, the lack of knowledge about failure probabilities of individual components introduces uncertainty. Subset simulation offers an efficient approach for propagating these component-level uncertainties to the system level. However, when parameters are highly correlated, traditional algorithms used in subset simulation may suffer from low acceptance rates (ratio of new samples to total samples), resulting in repeated samples, thereby compromising efficiency. This paper demonstrates that the proposed treatment allows application of subset simulation to uncertainty quantification of large fault trees using a case study of a coal-fired power plant
Data mining · Downtime · Event tree · Fault tree analysis · Hazard · Reliability engineering · Computer Science · Engineering · Fault Detection and Control Systems · Probabilistic and Robust Engineering Design · Risk and Safety Analysis
A probabilistic approach for modeling the empirical economic loss impacts of data surveys on small and medium-sized enterprises; A case study of the November 2016 Sarpol-e Zahab earthquake
Risk Assessment of Urban Transportation Complex Hub from Resilience Perspective
Seismic Resilience Assessment and Improvement of a Containerized Edge Data Center
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2025 (2) |
| Highly cited | No |