کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7195095 | 1468192 | 2018 | 28 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Reliability-based sensitivity estimators of rare event probability in the presence of distribution parameter uncertainty
ترجمه فارسی عنوان
برآوردگرهای حساسیت مبتنی بر قابلیت اطمینان احتمال نادر بودن در حضور عدم قطعیت پارامتر توزیع
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کلمات کلیدی
عدم قطعیت پارامتر توزیع، شبیه سازی رویداد نادر، نمونه برداری اهمیت سازگار، تجزیه و تحلیل حساسیت قابلیت اطمینان، توابع امتیاز،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی مکانیک
چکیده انگلیسی
This paper aims at presenting sensitivity estimators of a rare event probability in the context of uncertain distribution parameters (which are often not known precisely or poorly estimated due to limited data). Since the distribution parameters are also affected by uncertainties, a possible solution consists in considering a second probabilistic uncertainty level. Then, by propagating this bi-level uncertainty, the failure probability becomes a random variable and one can use the mean estimator of the distribution of the failure probabilities (i.e. the “predictive failure probability”, PFP) as a new measure of safety. In this paper, the use of an augmented framework (composed of both basic variables and their probability distribution parameters) coupled with an Adaptive Importance Sampling strategy is proposed to get an efficient estimation strategy of the PFP. Consequently, double-loop procedure is avoided and the computational cost is decreased. Thus, sensitivity estimators of the PFP are derived with respect to some deterministic hyper-parameters parametrizing a priori modeling choice. Two cases are treated: either the uncertain distribution parameters follow an unbounded probability law, or a bounded one. The method efficiency is assessed on two different academic test-cases and a real space system computer code (launch vehicle stage fallback zone estimation).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Reliability Engineering & System Safety - Volume 178, October 2018, Pages 164-178
Journal: Reliability Engineering & System Safety - Volume 178, October 2018, Pages 164-178
نویسندگان
Vincent Chabridon, Mathieu Balesdent, Jean-Marc Bourinet, Jérôme Morio, Nicolas Gayton,