Review of Application on Dynamic Fault Tree Method in Nuclear Power Plants

2020 ◽  
Author(s):  
Wu Guohua ◽  
Yuan Diping ◽  
Xiao Yiqing ◽  
Wang Jiaxin
Keyword(s):  
Markov Chain ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Fault Trees ◽  
Tree Analysis ◽  
Dynamic Fault Tree ◽  
Fault State

Abstract Fault tree analysis (FTA) is one of the most important methods of probabilistic risk assessment (PRA). The fault state of the system is taken. While traditional FTA is based on static failure model. FTA is not applicable for systems that include redundant, sequence-related systems. At the same time, nuclear power plants (NPPs) contains a large number of redundant equipment, and FTA is difficult to solve these dynamic problems. Therefore, it is necessary to use dynamic fault tree analysis (DFTA) for PRA. In DFTA research, the modular analysis method was first proposed. The modular method divides the dynamic fault tree into a dynamic fault tree and a static fault tree. Among them, the dynamic fault tree is analyzed using a Markov chain, and the static fault tree is studied using a binary decision diagrams method. However, the shortcomings are that when the system is complicated, the information explosion in the Markov chain is appeared. To solve this problem, a dynamic fault tree is transformed into a Bayesian network. At the same time, to verify the feasibility of the method, Monte Carlo random sampling was used to evaluate the method. Other methods are relatively infrequently studied. In this paper, firstly, status of dynamic fault trees has been investigated. Secondly, each method is analyzed and the problems of dynamic fault tree are described. Finally, a survey and analysis on the dynamic fault tree is finished, and the main problems of the dynamic fault tree are: information explosion; the lack of commercial software to apply to engineering. Through this review, we hope to play a certain guiding role in the subsequent research on dynamic fault trees.

Dynamic fault tree analysis of auxiliary feedwater system in a pressurized water reactor

Kerntechnik ◽  
2021 ◽  
Vol 86 (2) ◽  
pp. 164-172
Author(s):  
R. A. Fahmy ◽  
R. I. Gomaa
Keyword(s):  
Power Plant ◽  
System Reliability ◽  
Nuclear Power ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Cost Effective ◽  
Pressurized Water Reactor ◽  
Pressurized Water ◽  
Tree Analysis ◽  
Dynamic Fault Tree

Abstract The safe and secure designs of any nuclear power plant together with its cost-effective operation without accidents are leading the future of nuclear energy. As a result, the Reliability, Availability, Maintainability, and Safety analysis of NPP systems is the main concern for the nuclear industry. But the ability to assure that the safety-related system, structure, and components could meet the safety functions in different events to prevent the reactor core damage requires new reliability analysis methods and techniques. The Fault Tree Analysis (FTA) is one of the most widely used logic and probabilistic techniques in system reliability assessment nowadays. The Dynamic fault tree technique extends the conventional static fault tree (SFT) by considering the time requirements to model and evaluate the nuclear power plant safety systems. Thus this paper focuses on developing a new Dynamic Fault Tree for the Auxiliary Feed-water System (AFWS) in a pressurized water reactor. The proposed dynamic model achieves a more realistic and accurate representation of the AFWS safety analysis by illustrating the complex failure mechanisms including interrelated dependencies and Common Cause Failure (CCF). A Simulation tool is used to simulate the proposed dynamic fault tree model of the AFWS for the quantitative analysis. The more realistic results are useful to establish reliability cantered maintenance program in which the maintenance requirements are determined based on the achievement of system reliability goals in the most cost-effective manner.

Fault Tree Analysis Based on Dynamic Uncertain Causality Graph

2017 ◽  
Author(s):  
Zhenxu Zhou ◽  
Qin Zhang
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis ◽  
Industrial Systems ◽  
Weapon Systems ◽  
Chemical Systems ◽  
Binary State ◽  
Dynamic Uncertain Causality Graph

Fault Tree Analysis (FTA) has been widely applied to large, complex industrial systems like nuclear power plants, chemical systems, and weapon systems. Events in classical FTA are assumed binary-state and s-independent but multi-state, dependencies and logic cycles may exist within FTs. Moreover, causalities in FTA are assumed deterministic, while sometimes they may be uncertain. This paper applies Dynamic Uncertain Causality Graph (DUCG) in FTA to overcome aforementioned issues. This paper shows that any FT can be mapped into a DUCG graph. And with DUCG representation model and algorithm, additional modeling and analytical power are obtained. Multi-value, dependencies, logic cycles, and non-deterministic causalities in FTA are solved. This paper also depicts how to calculate the importance measurement, predict failure, and diagnose fault. The results reveal the effectiveness and feasibility of this methodology.

scholarly journals A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2150
Author(s):  
Woo Sik Jung
Keyword(s):  
Exact Solutions ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Fault Tree ◽  
Ground Acceleration ◽  
Special Operations ◽  
Core Damage ◽  
Full Power ◽  
Conditional Events

Seismic probabilistic safety assessment (PSA) models for nuclear power plants (NPPs) have many non-rare events whose failure probabilities are proportional to the seismic ground acceleration. It has been widely accepted that minimal cut sets (MCSs) that are calculated from the seismic PSA fault tree should be converted into exact solutions, such as binary decision diagrams (BDDs), and that the accurate seismic core damage frequency (CDF) should be calculated from the exact solutions. If the seismic CDF is calculated directly from seismic MCSs, it is drastically overestimated. Seismic single-unit PSA (SUPSA) models have random failures of alternating operation systems that are combined with seismic failures of components and structures. Similarly, seismic multi-unit PSA (MUPSA) models have failures of NPPs that undergo alternating operations between full power and low power and shutdown (LPSD). Their failures for alternating operations are modeled using fraction or partitioning events in seismic SUPSA and MUPSA fault trees. Since partitioning events for one system are mutually exclusive, their combinations should be excluded in exact solutions. However, it is difficult to eliminate the combinations of mutually exclusive events without modifying PSA tools for generating MCSs from a fault tree and converting MCSs into exact solutions. If the combinations of mutually exclusive events are not deleted, seismic CDF is underestimated. To avoid CDF underestimation in seismic SUPSAs and MUPSAs, this paper introduces a process of converting partitioning events into conditional events, and conditional events are then inserted explicitly inside a fault tree. With this conversion, accurate CDF can be calculated without modifying PSA tools. That is, this process does not require any other special operations or tools. It is strongly recommended that the method in this paper be employed for avoiding CDF underestimation in seismic SUPSAs and MUPSAs.

Dynamic Fault Tree Analysis

2020 ◽  
pp. 73-112
Author(s):  
Koorosh Aslansefat ◽  
Sohag Kabir ◽  
Youcef Gheraibia ◽  
Yiannis Papadopoulos
Keyword(s):  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis ◽  
Dynamic Fault Tree
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