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| リスクベースイベントツリー解析× | リスクベース故障木解析× | |
|---|---|---|
| 分野 | 実験計画法 | 実験計画法 |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | 1975 (WASH-1400); risk-based integration formalized through 1980s–1990s PRA practice | 1961 (FTA origin); risk-based integration formalised 1975–1981 |
| 提唱者≠ | Originated in nuclear industry (US Nuclear Regulatory Commission, WASH-1400 report); risk-based framing developed through probabilistic risk assessment practice | H.A. Watson (Bell Labs) and developed further by Boeing/U.S. Air Force; risk-based extension via NRC probabilistic risk assessment programs |
| 種類≠ | Risk and reliability analysis technique | Quantitative safety and reliability analysis |
| 原典≠ | Bedford, T., & Cooke, R. (2001). Probabilistic Risk Analysis: Foundations and Methods. Cambridge University Press. ISBN: 978-0521773201 | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. U.S. Nuclear Regulatory Commission, NUREG-0492. link ↗ |
| 別名 | Risk-based ETA, probabilistic event tree analysis, consequence-probability event tree, risk-informed ETA | RB-FTA, risk-informed FTA, quantitative fault tree analysis, probabilistic fault tree analysis |
| 関連≠ | 4 | 6 |
| 概要≠ | Risk-based event tree analysis is a forward-looking, inductive risk assessment technique that models the consequences of an initiating event by tracing binary success/failure branches through safety barriers, then weights each outcome path by its probability to produce quantified risk estimates. Widely applied in nuclear, chemical process, aviation, and infrastructure safety engineering, it sits at the heart of probabilistic risk assessment (PRA) and supports both design decisions and regulatory compliance. | 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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