scholarly journals Choosing a heuristic for the "fault tree to binary decision diagram" conversion, using neural networks

2002 ◽  
Vol 51 (3) ◽  
pp. 344-349 ◽  
Author(s):  
L.M. Bartlett ◽  
J.D. Andrews
Keyword(s):  
Neural Networks ◽  
Fault Tree ◽  
Binary Decision Diagram ◽  
Binary Decision

Design and Development of DeRisk: A Fault Tree Analysis Program Package

2018 ◽  
Author(s):  
Zhenxu Zhou ◽  
Hao Nie ◽  
Qin Zhang
Keyword(s):  
Fault Tree ◽  
Fault Tree Analysis ◽  
Good Choice ◽  
Binary Decision Diagram ◽  
Program Package ◽  
Analysis Program ◽  
Binary Decision ◽  
Tree Analysis ◽  
Input Module ◽  
Low Efficiency

Fault tree analysis (FTA) has been proven to be a very important tool and has been successfully applied to safety/reliability studies in nuclear, chemical, military, space industries/systems. Hitherto, several useful and popular FTA software/program packages have been developed, like CAFTA+, FAUNET, RiskSpectrum, SAPHIRE, RiskA etc. Minimum Cut Set (MCS) method is the most commonly used traditional FTA method. However, it suffers from low efficiency when solving remarkably large fault trees (FTs). To overcome the shortcomings of the traditional method, several new techniques are proposed such as Binary Decision Diagram (BDD), Zero-suppressed Binary Decision Diagram, (ZBDD) Petri Net (PN), Bayesian Network (BN) and Dynamic Uncertain Causality Graph (DUCG). DUCG is a newly presented Probabilistic Graphic Model to deal with systems with dynamics, uncertainties and logic cycles. DUCG is a good choice to analyze large FTs, in our previous papers, we have proved that any FT can be mapped into a DUCG graph and additional modeling and analytical power can be achieved. DeRisk is a DUCG embedded risk analysis program package written in C# for FTA and is designed as a powerful tool to assist reliability engineers. In this paper, the design schema and the main algorithms of DeRisk are introduced. DeRisk contains five parts: (1) A Graphical User Interface (GUI) Module which interacts with users; (2) A Preprocessing Module which preprocesses FTs (3) An Input Module which allows user to input necessary data by file or by command line; (4) A Calculation Module which offers qualitative/quantitative analysis; (5) An Output Module which outputs the results required by users. Some illustrative examples are used to verify the correctness and effectiveness of DeRisk.

Variable ordering schemes to apply to the binary decision diagram methodology for event tree sequences assessment

2008 ◽  
Vol 222 (1) ◽  
pp. 7-16 ◽  
Author(s):  
C Ibáñez-Llano ◽  
E Meléndez ◽  
Nieto F
Keyword(s):  
Fault Tree ◽  
Binary Decision Diagram ◽  
Event Tree ◽  
Final Size ◽  
Binary Decision ◽  
Reliability Models ◽  
Variable Ordering ◽  
Recent Approach ◽  
Event Trees ◽  
Ordering Schemes

Binary decision diagram (BDD) methodology is the most recent approach to improve Boolean reliability models assessment. The final size of the BDD, and therefore the ultimate benefits of this technique, are very sensitive to the initial variable ordering that has to be fixed prior to conversion. Several variable ordering strategies have been proposed in the literature, all of them focused on the treatment of single fault tree models. This paper proposes some extensions of existing variable ordering schemes for the case of combinations of non-disjoint fault trees, as is the case in quantifying sequences of event trees. These extensions work by combining ordering schemes applied to each fault tree, and exploring the cases where variables within the domains intersection are kept together or not. They have been specifically designed to be applied together with an incremental procedure to compute the BDD of the sequence accumulatively and to be used to quantify sequences of dynamic event trees. Preliminary results show the potential of this approach.

Efficient Ordering Heuristics in Binary Decision Diagram-based Fault Tree Analysis

2012 ◽  
Vol 29 (3) ◽  
pp. 307-315 ◽  
Author(s):  
Yuchang Mo ◽  
Farong Zhong ◽  
Huawen Liu ◽  
Quansheng Yang ◽  
Gang Cui
Keyword(s):  
Fault Tree ◽  
Fault Tree Analysis ◽  
Binary Decision Diagram ◽  
Binary Decision ◽  
Tree Analysis

A method for transformation from dynamic fault tree to binary decision diagram

2020 ◽  
pp. 1748006X2097418
Author(s):  
Haiyue Yu ◽  
Xiaoyue Wu
Keyword(s):  
Quantitative Analysis ◽  
Fault Tree ◽  
Binary Decision Diagram ◽  
Tree Structure ◽  
Binary Decision ◽  
Dynamic Fault Tree ◽  
Sequential Event ◽  
High Level ◽  
Topological Sorting ◽  
Generation Procedure

Dynamic fault tree (DFT) is a powerful modeling approach for reliability analysis of complex system with dynamic failure behaviors. In reality, the tree structure may be highly coupled either by shared basic events or by the high-level dynamic gates. Currently, the application of sequential binary decision diagram (SBDD)-based method for quantitative analysis of such highly coupled DFTs is mainly limited to DFTs whose dynamic gates locate in the bottom of the tree. Moreover, there is no efficient way dealing with the dependencies among different nodes of a SBDD 1-path. This paper makes an improvement to the SBDD-based approach. A generation procedure is proposed to directly construct the binary decision diagram (BDD) model for a DFT with arbitrary tree structure. During the construction, the sequential-dependent information of the tree is derived as several BDD nodes, each indicates a binary-sequential event representing the sequence of two occurred basic events. A topological sorting is applied on each 1-path of the resultant BDD to obtain its contained disjoint cut sequences. Based on this, both qualitative and quantitative analysis can be performed on the DFT with no limitations on tree structure, and its minimal cut sequence set (CSS) is obtained as disjoint. Examples are provided for verification and comparison, and the results illustrate the merits of the proposed approach.

Characterizing wafer stage transmission errors via binary decision diagram and dynamic fault tree

2018 ◽  
Vol 32 (11) ◽  
pp. 5111-5119 ◽  
Author(s):  
Junyu Guo ◽  
Guo-Zhong Fu ◽  
Hong-Zhong Huang ◽  
Yu Liu ◽  
Yan-Feng Li
Keyword(s):  
Fault Tree ◽  
Binary Decision Diagram ◽  
Binary Decision ◽  
Transmission Errors ◽  
Dynamic Fault Tree
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