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| 시뮬레이션 지원 고장 트리 분석× | 위험 기반 고장 트리 분석× | |
|---|---|---|
| 분야 | 실험설계 | 실험설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1970s–1980s (widespread adoption in nuclear and aerospace industries) | 1961 (FTA origin); risk-based integration formalised 1975–1981 |
| 창시자≠ | Fault tree analysis: H. A. Watson (Bell Labs, 1961); Monte Carlo integration in reliability: Herman Kahn / Stanislaw Ulam (RAND, late 1940s); combination formalized in reliability engineering literature from the 1970s onward | H.A. Watson (Bell Labs) and developed further by Boeing/U.S. Air Force; risk-based extension via NRC probabilistic risk assessment programs |
| 유형≠ | Quantitative reliability and risk analysis technique | Quantitative safety and reliability analysis |
| 원전≠ | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. US Nuclear Regulatory Commission, NUREG-0492. link ↗ | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. U.S. Nuclear Regulatory Commission, NUREG-0492. link ↗ |
| 별칭 | SA-FTA, Monte Carlo FTA, simulation-based FTA, stochastic fault tree analysis | RB-FTA, risk-informed FTA, quantitative fault tree analysis, probabilistic fault tree analysis |
| 관련 | 6 | 6 |
| 요약≠ | Simulation-assisted fault tree analysis (SA-FTA) combines the logical structure of classical fault tree analysis with Monte Carlo or discrete-event simulation to estimate the probability and timing of an undesired top event when component failures follow complex, non-exponential, or correlated probability distributions. The approach overcomes the analytical limitations of Boolean algebra-based FTA and is widely used in nuclear, aerospace, chemical process, and manufacturing reliability engineering. | Risk-based fault tree analysis (RB-FTA) combines classical fault tree analysis with explicit quantitative risk assessment. Starting from an undesired top event, the analyst decomposes it into contributing causes using AND/OR logic gates, assigns failure probabilities to basic events from reliability databases or historical data, and then propagates those probabilities through the tree to compute top-event likelihood. The result is expressed as risk — probability weighted by consequence severity — enabling prioritisation of safety interventions by their actual risk reduction impact. |
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