Petroleum Science >2021,??lssue 6:??- DOI: https://doi.org/10.1016/j.petsci.2021.08.011
Parameter uncertainty modeling of safety instrumented systems Open?Access
文章信息
作者：Bao-Ping Cai, Wen-Chao Li, Yong-Hong Liu, Yan-Ping Zhang, Yi Zhao, Xiang-Di Kong, Zeng-Kai Liu, Ren-Jie Ji, Qiang Feng,
作者單位：
投稿時(shí)間：
引用方式：Bao-Ping Cai, Wen-Chao Li, Yong-Hong Liu, Yan-Ping Zhang, Yi Zhao, Xiang-Di Kong, Zeng-Kai Liu, Ren-Jie Ji, Qiang Feng, Parameter uncertainty modeling of safety instrumented systems, Petroleum Science, Volume 18, Issue 6, 2021, Pages 1813-1828, https://doi.org/10.1016/j.petsci.2021.08.011.
文章摘要
Abstract
In this study, a novel safety integrity level (SIL) determination methodology of safety instrumented systems (SISs) with parameter uncertainty is proposed by combining multistage dynamic Bayesian networks (DBNs) and Monte Carlo simulation. A multistage DBN model for SIL determination with multiple redundant cells is established. The models of function inspection test interval and function inspection test stages are alternately connected to form the multistage DBNs. The redundant cells can have different M out of N voting system architectures. An automatic modeling of conditional probability between nodes is developed. The SIL determination of SISs with parameter uncertainty is constructed by using the multistage DBNs and Monte Carlo simulation. A high-pressure SIS in the export of oil wellplatform is adopted to demonstrate the application of the proposed approach. The SIL and availability of the SIS and its subsystems are obtained. The influence of single subsystem on the SIL and availability of the SIS is studied. The influence of single redundant element on the SIL and availability of the subsystem is analyzed. A user-friendly SIL determination software with parameter uncertainty is developed on MATLAB graphical user interface.
In this study, a novel safety integrity level (SIL) determination methodology of safety instrumented systems (SISs) with parameter uncertainty is proposed by combining multistage dynamic Bayesian networks (DBNs) and Monte Carlo simulation. A multistage DBN model for SIL determination with multiple redundant cells is established. The models of function inspection test interval and function inspection test stages are alternately connected to form the multistage DBNs. The redundant cells can have different M out of N voting system architectures. An automatic modeling of conditional probability between nodes is developed. The SIL determination of SISs with parameter uncertainty is constructed by using the multistage DBNs and Monte Carlo simulation. A high-pressure SIS in the export of oil wellplatform is adopted to demonstrate the application of the proposed approach. The SIL and availability of the SIS and its subsystems are obtained. The influence of single subsystem on the SIL and availability of the SIS is studied. The influence of single redundant element on the SIL and availability of the subsystem is analyzed. A user-friendly SIL determination software with parameter uncertainty is developed on MATLAB graphical user interface.
關(guān)鍵詞
-
Safety integrity level; Dynamic Bayesian network; Monte Carlo; Parameter uncertainty