مقایسهٔ روش‌ها

	تحلیل درخت رویداد مبتنی بر ریسک	تحلیل درخت رویداد (ETA)
حوزه	طراحی آزمایش	قابلیت اطمینان
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	1975 (WASH-1400); risk-based integration formalized through 1980s–1990s PRA practice	2002
پدیدآور	Originated in nuclear industry (US Nuclear Regulatory Commission, WASH-1400 report); risk-based framing developed through probabilistic risk assessment practice	Andrews & Moss
نوع	Risk and reliability analysis technique	Forward inductive logic tree
منبع بنیادین	Bedford, T., & Cooke, R. (2001). Probabilistic Risk Analysis: Foundations and Methods. Cambridge University Press. ISBN: 978-0521773201	Andrews, J. D., & Moss, T. R. (2002). Reliability and Risk Assessment (2nd ed.). Professional Engineering Publishing. ISBN: 978-1-86058-290-5
نام‌های دیگر	Risk-based ETA, probabilistic event tree analysis, consequence-probability event tree, risk-informed ETA	ETA, Event Sequence Diagram Analysis, Initiating Event Analysis, Olay Ağacı Analizi
مرتبط	4	2
خلاصه	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.	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.