مقایسهٔ روش‌ها

	تحلیل حساسیت با تحلیل درخت رویداد	تحلیل درخت رویداد مبتنی بر ریسک
حوزه	طراحی آزمایش	طراحی آزمایش
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	Combination formalized in risk and reliability engineering from the 1990s onward	1975 (WASH-1400); risk-based integration formalized through 1980s–1990s PRA practice
پدیدآور	Sensitivity analysis: Saltelli et al. (1990s–2000s); Event tree analysis: Watson (1961, WASH-1400 formalization 1975)	Originated in nuclear industry (US Nuclear Regulatory Commission, WASH-1400 report); risk-based framing developed through probabilistic risk assessment practice
نوع	Hybrid quantitative risk analysis method	Risk and reliability analysis technique
منبع بنیادین	Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 978-0470059975	Bedford, T., & Cooke, R. (2001). Probabilistic Risk Analysis: Foundations and Methods. Cambridge University Press. ISBN: 978-0521773201
نام‌های دیگر	SA-ETA, ETA sensitivity analysis, event tree sensitivity analysis, probabilistic sensitivity analysis with ETA	Risk-based ETA, probabilistic event tree analysis, consequence-probability event tree, risk-informed ETA
مرتبط	6	4
خلاصه	Sensitivity analysis with event tree analysis (SA-ETA) is a quantitative risk assessment approach that systematically varies the input probabilities of an event tree model to determine which branch probabilities or initiating event frequencies most strongly influence the calculated probability of undesired outcomes. It extends classical event tree analysis by ranking the uncertainty contributions of individual inputs, thereby guiding risk-reduction efforts toward the parameters that matter most.	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.