Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza arborilor de evenimente asistată de simulare× | Analiza Arborelui de Evenimente (AAE)× | |
|---|---|---|
| Domeniu≠ | Design experimental | Fiabilitate |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1970s–1990s (formalized in probabilistic risk assessment practice) | 2002 |
| Autorul original≠ | H.A. Watson (Bell Telephone Laboratories, ETA origins ~1961); Monte Carlo integration of ETA developed in nuclear/aerospace PRA community 1970s–1990s | Andrews & Moss |
| Tip≠ | Probabilistic risk and reliability assessment method | Forward inductive logic tree |
| Sursa seminală≠ | Zio, E. (2009). Reliability engineering: Old problems and new challenges. Reliability Engineering and System Safety, 94(2), 125–141. DOI ↗ | Andrews, J. D., & Moss, T. R. (2002). Reliability and Risk Assessment (2nd ed.). Professional Engineering Publishing. ISBN: 978-1-86058-290-5 |
| Denumiri alternative | Monte Carlo ETA, stochastic event tree analysis, simulation-enhanced ETA, probabilistic event tree simulation | ETA, Event Sequence Diagram Analysis, Initiating Event Analysis, Olay Ağacı Analizi |
| Înrudite≠ | 6 | 2 |
| Rezumat≠ | Simulation-assisted event tree analysis (ETA) extends classical event tree analysis by replacing fixed point-estimate branch probabilities with Monte Carlo or discrete-event simulation. This allows analysts to propagate uncertainty through every branch of the tree and obtain full probability distributions over accident sequences and system outcomes, yielding far richer risk insights than deterministic ETA alone. | Event Tree Analysis (ETA) is a forward inductive technique used in reliability and risk engineering to model the possible outcomes that follow an initiating event. Starting from a single undesired event, ETA traces all subsequent event sequences through a binary branching tree representing the success or failure of safety barriers and protective systems. Introduced formally in reliability and risk literature by Andrews and Moss (2002), it is widely applied in nuclear, chemical, and aerospace industries to quantify accident sequence probabilities and guide safety decision-making. |
| ScholarGateSet de date ↗ |
|
|