Bidirectional implementation of Markov/CCMT for dynamic reliability analysis with application to digital I&amp;C systems

Yang, Jun; Zou, Bowen; Yang, Ming

doi:10.1016/j.ress.2018.12.024

Cited by 11 publications

(4 citation statements)

References 20 publications

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“…As shown in Figure 3, a synchronous learning framework for securing the model‐data assimilation of multiple phenological observations to constrain and predict dynamic risks in system operations is proposed based on our previous studies of Markov/CCMT 51–53 . The Markov/CCMT models formulated by matrix‐coded probabilistic mapping scheme can assimilate multi‐source observational data including simulation data and real‐time field data from real operating environment.…”

Section: Markov/ccmt Solver For Process Dynamics Analysismentioning

confidence: 99%

“…Similar to all graph‐based search, i.e., the aforementioned DDET algorithm in Figure 2, the Markov/CCMT analysis can be started from either system initial state, end state or even the in‐between risk point of system state respectively implemented for inductive searching mode, deductive searching mode and bidirectional searching mode. The concept of ‘risk point’ is also newly introduced in our previous study 53 to contribute in a more efficient system state space searching and spot the key points that may lead to system failures. In the practical applications of Markov/CCMT compute engine, the risk points will be screened out by taking both the probability of occurrence and degradation rate into account with proactive analytics.…”

Section: Markov/ccmt Solver For Process Dynamics Analysismentioning

confidence: 99%

“…As shown in Figure 3, a synchronous learning framework for securing the model-data assimilation of multiple phenological observations to constrain and predict dynamic risks in system operations is proposed based on our previous studies of Markov/CCMT. [51][52][53] The Markov/CCMT models formulated by matrix-coded probabilistic mapping scheme can assimilate multi-source observational data including simulation data and real-time field data from real operating environment. The assimilated matrix-coded probabilistic mapping scheme of system state space is updated based on the dynamical synchronization of observational data and models and calculated by Markov/CCMT compute engine.…”

Section: Markov/ccmt Solver For Process Dynamics Analysismentioning

confidence: 99%

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A hybrid computing framework for risk‐oriented reliability analysis in dynamic PSA context: A case study

Jiang

et al. 2022

Quality & Reliability Eng

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Nowadays, the emerging digital technologies and digitalization trend in safety‐critical industrial process systems are bringing great opportunities for system performance improvements. However, new big challenges are also encountered in the reliability and safety evaluation of large complex industrial process systems due to its multi‐state, multi‐phase dynamic interactions, resilience on software and inter‐dependencies among digital components. The objectives of this study are i) to present an introductory overview of a hybrid computing framework as a supplementary to conventional fault tree analysis toolkit for risk‐oriented reliability analysis in dynamic probabilistic safety assessment context; ii) to illustrate how to combine the three methods of DDET, Markov/CCMT, and GO‐FLOW for integrated risk solutions by a case study of small‐break LOCA in nuclear power plants. Within the hybrid computing framework, the DDET model is implemented based on graph‐based search and sequence diagram refactoring by linking with Markov/CCMT and GO‐FLOW solver for branch probability estimation. The dynamic event tree model is adopted to represent the accident sequence of small‐break LOCA, where the heading events of system failure of digital RPS and phased‐mission ECCS in realization of safety‐critical functions of reactivity control and emergency core cooling are respectively modeled and analyzed by Markov chain and GO‐FLOW method. The demonstration results show that the failure analysis of complex dynamic process interactions together with time‐dependent mission reliability analysis of safety systems involved in accident prevention and mitigation can be easily implemented with accurate modeling and fast evaluation within the hybrid integration platform. The core algorithms and principles implemented for dynamic risk scenarios development by DDET, modeling, and analysis of dynamic process interactions by Markov/CCMT, time‐dependent and multi‐phase mission reliability analysis by GO‐FLOW as well as their integration to provide comprehensive solutions for the application of dynamic reliability in risk assessment are also discussed as open problems for future research.

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Section: Markov/ccmt Solver For Process Dynamics Analysismentioning

confidence: 99%

Section: Markov/ccmt Solver For Process Dynamics Analysismentioning

confidence: 99%

Section: Markov/ccmt Solver For Process Dynamics Analysismentioning

confidence: 99%

See 1 more Smart Citation

A hybrid computing framework for risk‐oriented reliability analysis in dynamic PSA context: A case study

Jiang

et al. 2022

Quality & Reliability Eng

Self Cite

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“…Among the methods that can be used to quantitatively compute a fault tree, the authors want to highlight bottom-up analysis, binary-decision diagrams [23] [20], rare event approximation [3] [21] (usually, based on MCS) or Bayesian network analysis [15] [24]. Although other ones, like Petri Nets, Pivotal Decomposition [25] or Markov methods [26], are also relevant, but out of the scope of the present work. Two of the quantitative analyses of a fault tree are specially used in the aviation sector, the main aim of the present communication: Minimal Cut Sets (MCS) [27] and Direct numerical Evaluation (DE) without computing the cut sets.…”

Section: Introductionmentioning

confidence: 99%

Development and Implementation of a Direct Evaluation Solution for Fault Tree Analyses Competing With Traditional Minimal Cut Sets Methods

Cortes¹,

Martino²,

Duran³

et al. 2023

IEEE Trans. Rel.

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Fault Tree Analysis (FTA) is a wellestablished technique to analyze the safety risks of a system. Two specific prominent FTA methods, largely applied in the aerospace field, are the socalled Minimal Cut Sets (MCS), which uses an approximate evaluation of the problem, and the Direct Evaluation (DE) of the fault tree, which uses a top-down recursive algorithm. The first approach is only valid for small values of basic event probabilities and has historically yielded faster results than exact solutions for complex fault trees. The second one means exact solutions at a higher computational cost. The paper presents several improvements applied to both approaches in order to upgrade the computing performance. Firstly, improvements to the MCS approach have been performed, where the main idea has been to optimize the number of required permutations and to take advantage of the available information from previous solved subsets. Secondly, improvements to the DE approach have been applied, which deal with a reduction of the number of recursive calls through a deep search for independent events in the fault tree. This could dramatically reduce the computation time for industrial fault trees with a high number of repeated events.

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Study for Reliability Analysis of Operator Response Process Under IBLOCA Accident in Nuclear Power Plant

Zhang

et al. 2021

Lecture Notes in Electrical Engineering

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Bidirectional implementation of Markov/CCMT for dynamic reliability analysis with application to digital I&C systems

Cited by 11 publications

References 20 publications

A hybrid computing framework for risk‐oriented reliability analysis in dynamic PSA context: A case study

A hybrid computing framework for risk‐oriented reliability analysis in dynamic PSA context: A case study

Development and Implementation of a Direct Evaluation Solution for Fault Tree Analyses Competing With Traditional Minimal Cut Sets Methods

Study for Reliability Analysis of Operator Response Process Under IBLOCA Accident in Nuclear Power Plant

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