Minimal Cut Sets Research Articles

Preliminary Hazard Analysis dan Fault Tree Analysis untuk Identifikasi Penyebab Kegagalan Sistem Pelumas Mesin Induk Kapal Penangkap Ikan

Kapal penangkap ikan di Indonesia sebagian besar menggunakan mesin diesel sebagai tenaga penggeraknya. Mesin diesel merupakan mesin mekanis dimana singgungan komponen tidak dapat dihindari, sehingga sistem pelumas mutlak diperlukan untuk mengurangi tingkat kerusakan komponen yang bersinggungan. Penurunan kemampuan sisteem pelumas berdampak pada kerusakan mesin. Tujuan penelitian ini untuk mengidentifikasi penyebab kerusakan sistem pelumas mesin diesel kapal penangkap ikan sehingga memudahkan untuk membuat keputusan dalam melakukan tindakan perawatan dan perbaikan sistem pelumas. Metode untuk mengidentifikasi tiap kegagalan yang mungkin terjadi menggunakan Preliminary Hazard Analysis (PHA) dan Fault Tree Analysis (FTA). PHA merupakan perangkat untuk mengidentifikasi potensi bahaya yang mengakibatkan kegagalan sistem, FTA merupakan perangkat untuk mengidentifikasi penyebab kegagalan sistem. FTA bekerja dengan menentukan kegagalan yang disebut sebagai “top event”, selanjutnya top event diidentifikasi hubungan faktor penyebab berbagai peristiwa kegagalan dengan pohon kesalahan yang menggunakan gerbang logika sederhana “and” dan “or”. Terbentuknya FTA dapat menentukan faktor penyebab kegagalan dengan minimal cut set. Berdasarkan hasil analisis, terdapat tiga penyebab utama mesin diesel mengalami kegagalan karena sistem pelumas adalah gagalnya komponen sistem pelumas yaitu Kebocoran internal, (Screen pelumas + alarm tekanan + manometer + petugas), dan (Pompa pelumas + alarm tekanan + manometer + petugas).

Computing irreversible minimal cut sets in genome-scale metabolic networks via flux cone projection.

Minimal cut sets (MCSs) for metabolic networks are sets of reactions which, if they are removed from the network, prevent a target reaction from carrying flux. To compute MCSs different methods exist, which may fail to find sufficiently many MCSs for larger genome-scale networks. Here we introduce irreversible minimal cut sets (iMCSs). These are MCSs that consist of irreversible reactions only. The advantage of iMCSs is that they can be computed by projecting the flux cone of the metabolic network on the set of irreversible reactions, which usually leads to a smaller cone. Using oriented matroid theory, we show how the projected cone can be computed efficiently and how this can be applied to find iMCSs even in large genome-scale networks. Software is freely available at https://sourceforge.net/projects/irreversibleminimalcutsets/. Supplementary data are available at Bioinformatics online.

Reliability assessment of solar photovoltaic systems based on fuzzy fault tree analysis

Solar photovoltaic (SPV) systems are widely used as a renewable energy source to produce electricity to endusers. SPV system convert free and unlimited sunlight into electricity without carbon dioxide emission or any other air pollutants. The stochastic nature of SPV system may be responsible for degradation of performance in terms of availability, production, etc. Therefore, the assessment of the performance measures like reliability and quality of its components is vital concern that may open the new vista of research. There are various reliability assessment techniques used in conventional (thermal power plant, hydropower plant, nuclear power plant, etc.) and non-conventional power system (SPV power plant, wind power plant, etc.) like Fault Tree Analysis (FTA), Failure Mode and Effect Analysis (FMEA), etc. FTA is one of the powerful reliability assessment techniques, which gives modes of the failure and its consequences, that are demonstrated on SPV systems. FTA can further be broadly classified into two: qualitative and quantitative analysis. Qualitative FTA can be solved by determining a minimal cut set (MCS) and quantitative FTA can be solved by calculating the failure probability of each the basic event. In conventional FTA failure probability of each event must be known, to assess for quantitative FTA. However, to quantify probabilistic failure, data of all basic events seem to be inadequate. To overcome this problem, conventional FTA may be integrated with fuzzy linguistic scale method. In this research work, failure possibilities in terms of a linguistic variable of unknown failure data for all basic events, which lead the Top Events for SPV systems are assigned by the experts from academics, research, industries and practicing engineers. For Aggregated fuzzy number based on expert’s opinion, a consistency agreements method is used. Fussell-Vesely (F-V) importance measures is also implemented to rank the basic events and MCS to apportion the most critical event.

Investigation of extremely severe traffic crashes using fault tree analysis

ABSTRACTThis study aimed to use the fault tree analysis (FTA) to investigate the casual relationship among the event and causes contributing to extremely severe crash that leads to more than 10 deaths. The characteristics of extremely severe traffic crashes were compared with those of normal crashes in terms of gender, driving experience, road technical level, road alignment, time, and weather conditions. A fault tree was developed to provide an overview of the basic causes and their causal relationship. The minimal cut sets were derived to reveal the causal relationships among events and causes contributing to extremely severe crashes. Then, quantitative assessment was conducted to evaluate the importance of various events. The results can help to prioritize actions and resources for crash prevention. Finally, the minimal path set analysis was conducted to identify the minimal sets of basic events needed to be prevented so that extremely severe crash will not occur.

Sensor Fault Diagnosis Based on Fuzzy Neural Petri Net

This study aims to improve the operating stability of the resistance strain weighing sensor and eliminate fuzzy factors in fault diagnosis. Based on fuzzy techniques for fault diagnosis, the proposed fuzzy Petri net model uses the fault logical relationship between a sensor and an improved Petri net model. A formula for confidence-based reasoning is proposed using an algorithm, which combines neural network regulation algorithm with a transition-enabled ignition judgment matrix. This formula can yield an accurate assessment of the operating state of the sensor. Backward inference and the minimum cut set theory are also combined to obtain the priority of faults, which helps avoid blind and ambiguous maintenance. The sensor model was analyzed, and its accuracy and validity were verified through statistical analysis and comparison with other methods of fault diagnosis.

Sand casting safety assessment for foundry enterprises: fault tree analysis, Heinrich accident triangle, HAZOP-LOPA, bow tie model.

Sand casting operations, though commonplace, pose a significant threat of explosion accidents. This paper presents a novel sand casting safety assessment technique based on fault tree analysis, Heinrich accident triangle, hazard and operability–layer of protection analysis (HAZOP–LOPA) and bow tie model components. Minimal cut sets and minimal path sets are first determined based on fault tree analysis, then the frequency of sand casting explosion accidents is calculated based on the Heinrich accident triangle. Third, the risk level of venting quality can be reduced by adopting HAZOP–LOPA; the residual risk level of venting quality remains excessive even after adopting two independent protective layers. The bow tie model is then adopted to determine the causes and consequences of venting quality. Five preventative measures are imposed to enhance the venting quality of foundry sand accompanied by 16 mitigative safety measures. Our results indicate that the risk attributable to low foundry sand venting quality can be minimized via bow tie analysis.

ACTIVE REDUNDANCY ALLOCATION FOR COHERENT SYSTEMS WITH INDEPENDENT AND HETEROGENEOUS COMPONENTS

This paper studies the allocation of active redundancies to coherent systems on the context that the base and redundancy components have mutual independent lifetimes. For systems with two symmetric components and systems with one component's minimal cut sets (minimal path sets) covering those of another, we derive sufficient conditions to compare the resultant system lifetimes. Some numerical examples are also presented to illustrate the theoretical results.

Fault Tree Analysis of floating offshore wind turbines

Abstract With the development of offshore wind power, the reliability analysis of offshore wind turbines is increasingly significant due to the system complexity and negative impacts in harsh operating conditions. In this study, the Fault Tree Analysis method is adopted for both qualitative and quantitative evaluation of semi-submersible floating offshore wind turbine failure characteristics. The floating offshore wind turbine is divided into several assemblies, including support structures, pitch and hydraulic system, gearbox, generator and the other systems. Failure rates of relevant offshore structures are collected from previous studies, reports and reliability databases. On this basis, the quantitative assessment of Minimum Cut Sets and Importance Measures are achieved. The calculated results are generally in conformity with statistical data, indicating that most of the failures are caused by several basic factors. Marine conditions, especially the salt-spray and high wind speed, show the most significant impact on floating offshore wind turbine performance.

The Implementation of Importance Measure Approaches for Criticality Analysis in Fault Tree Analysis: A Review

THE IMPLEMENTATION OF IMPORTANCE MEASURE APPROACHES FOR CRITICALITY ANALYSIS IN FAULT TREE ANALYSIS: A REVIEW.Fault tree analysis (FTA) has been widely applied in nuclear power plant (NPP) probabilistic safety assessment to evaluate the reliability of a safety system. In FTA, criticality analysis is performed to identify the weakest paths in the system designs and components. For this purpose, an importance measure approach can be applied. Risk managers can apply information obtained from this analysis to improve safety by implementing risk reduction measure into the new design or build a more innovative design. Various importance measure approaches have been developed and proposed for criticality analysis in FTA. Each important measure approach offers specific purposes and advantages but has limitations. Therefore, it is necessary to understand characteristics of each approach in order to select the most appropriate approach to reach the purpose of the study. The objective of this study is to review the current implementations of importance measure approaches to rank individual basic events and/or minimal cut sets regarding their contributions to the unreliability or unavailability of NPP safety systems. This study classified importance measure approaches into two groups, i.e. probability–based importance measure approaches and fuzzy–based importance measure approaches. This study concluded that clear understanding of the purpose of the study, the type of reliability data at hands, and the uncertainty in the calculation need to be considered prior to the selection of the appropriate importance measure approach to the study of interest.

An Improved Hybrid Planning Model for Wind Power Transmission Channels

Based on the principles of deterministic planning and probabilistic planning, this paper proposes a multi-scenario hybrid planning model for wind power transmission channels. The model turns transmission channel planning into mixed-integer programming. The model uses the DC power flow model, the optimal power flow model and the minimal cut set to define and simulate multiple scenarios concerning future load growth in electric power system. The model uses the commercial optimization software CPLEX to find an optimal planning scheme for wind power transmission channels. In addition, through the assessment by a test system based on the actual grid and the comparison with traditional planning models, the model proves to be effective and usable.

A polynomial algorithm determining cyclic vertex connectivity of k-regular graphs with fixed k

For a connected graph G, a set S of vertices is a cyclic vertex cutset if $$G - S$$ is not connected and at least two components of $$G-S$$ contain a cycle respectively. The cyclic vertex connectivity $$c \kappa (G)$$ is the cardinality of a minimum cyclic vertex cutset. In this paper, for a k-regular graph G with fixed k value, we give a polynomial time algorithm to determine $$c \kappa (G)$$ and its time complexity is bounded by $$O(v^{15/2})$$.

Reliability Analysis of Aero-Engine Main Fuel System Based on GO Methodology

To improve the reliability of an aero-engine main fuel system, the quantitative and qualitative reliability analysis of the system is conducted based on goal oriented (GO) methodology. The quantitative reliability analysis results and the minimum cut sets of the fuel system are obtained, respectively. These results are compared with the results of the FTA (Fault Tree Analysis) method, and the comparison result shows GO method is rational and applicable. Therefore, it is feasible to apply the GO method in the reliability analysis of an aero-engine main fuel system.

Multicriteria reliability modeling and optimisation of a complex system with dual failure modes and high initial reliability

PurposeSystem reliability optimisation in today’s world is critical to ensuring customer satisfaction, businesses competitiveness, secure and uninterrupted delivery of services and safety of operations. Among many systems configurations, complex systems are the most difficult to model for reliability optimisation. The purpose of this paper is to assess the performance of a novel optimisation methodology of the authors, developed to address the difficulties in the context of a gas carrying system (GCS) exhibiting dual failure modes and high initial reliability.Design/methodology/approachThe minimum cut sets involving components of the system were obtained using the fault tree approach, and their reliability constituted into criteria which were maximised and the associated cost of improving their reliabilities minimised. Pareto optimal generic components and system reliabilities were subsequently obtained.FindingsThe results indicate that the optimisation methodology could improve the system’s reliability even from an initially high one, granted that the feasibility factor for improving a component’s reliability was very high. The results obtained, in spite of the size (41 objective functions and 18 decision variables), the complexity (dual failure modes) and the high initial reliability values provide confidence in the optimisation model and methodology and demonstrate their applicability to systems exhibiting multiple failure modes.Research limitations/implicationsThe GCS was assumed either failed or operational, its parameters precisely determined, and non-repairable. The components failure rates were exponentially distributed and failure modes independent. A single weight vector representing expression of preference in which components reliabilities were weighted higher than cost was used due to the stability of the optimisation model to weight variations.Practical implicationsThe high initial reliability values imply that reliability improvement interventions may not be a critical requirement for the GCS. The high levels could be sustained through planned and systematic inspection and maintenance activities. Even so, purely from an analytical stand point, the results nevertheless show that there was some room for reliability improvement however marginal that is. The improvement may be secured by: use of components with comparable levels of reliability to those achieved; use of redundancy techniques to achieve the desired levels of improvement in reliability; or redesigning of the components.Originality/valueThe novelty of this work is in the use of a reliability optimisation model and methodology that focuses on a system’s minimum cut sets as criteria to be optimised in order to optimise the system’s reliability, and the specific application to a complex system exhibiting dual failure modes and high component reliabilities.

Mine safety assessment based on basic event importance: grey relational analysis and bow tie model.

Safety assessments are a crucial first step in preventing coal and gas outburst accidents. The main purpose of this study was to create a new accident prevention technique using a novel safety assessment method based on fault tree basic event importance, grey relational analysis and the bow tie model. The innovation of the proposed method lies in generating the composite importance of a basic event from the fundamental importance via grey relational analysis; bow tie analysis serves to reveal the most critical basic event. First, the minimal cut sets and minimal path sets of a coal and gas outburst accident are determined by fault tree analysis. The role of minimal cut and path sets is determined and the coal and gas outburst occurrence frequency is calculated accordingly. Second, the structure, probability, critical and Fussell–Vesely importance ranked basic events differently due to different aspects of the basic events as investigated. We establish a composite importance to represent single basic events and achieved new ranking results by grey relational analysis. Third, the critical basic event low permeability coefficient is analysed via bow tie model and safety measures are defined which prevent the dangerous consequences of a low permeability coefficient. An actual coal and gas outburst accident is used as a case study to test the feasibility and effectiveness of the proposed method.

Fuzzy fault tree analysis for gas explosion of coal mining and heading faces in underground coal mines

During the past decade, gas explosions have been one of the most serious types of disasters in China, threatening the lives of miners and causing significant losses in terms of national property. This article, by constructing the fuzzy fault tree model of gas explosion on the coalface and heading face, deduces the minimum cut sets and minimum path of the fault tree, analyzes the importance of the fault tree structure, and obtains the ratio of gas explosion. The results show that the isolation of gas and heat sources is the most effective way to prevent gas explosion. In addition, a close detection of gas concentration and appropriate treatment can also avoid explosive accidents by reducing the ratio of explosion to below 0.059%, which is the critical value of explosion. The probability of gas explosion occurred in coal working face is about 0%–2.055%, and the most likely probability is 0.059%. However, the probability of gas explosion occurred in heading face is about 0%–8.543%, and the most probability likely to occur is 0.772% which is larger than that in coal working face. The fuzzy fault tree can not only be applied in the analysis of the coal mining gas explosion, but it also provides the theoretical basis for the precaution and prevention of coal mining accidents.

Performance and availability of a marine generator-solid oxide fuel cell-gas turbine hybrid system in a very large ethane carrier

This study investigates the proper configuration of an electric propulsion system for a very large ethane carrier. The system consists of a dual-fuel diesel electric generator and a solid oxide fuel cell-gas turbine hybrid system to replace the mechanical propulsion system based on a marine diesel engine. When the ship navigates the open sea, the dual-fuel diesel electric generator and hybrid system run in parallel at a power rating of 16 MW. However, the hybrid system only operates during the berthing state for ship hoteling. The system efficiency, energy efficiency design index, and availability are considered to identify the optimal system configuration. When the dual-fuel diesel electric generator produces 10 MW, the hybrid system generates 6 MW. Because the electric propulsion system complies with international environmental regulations, it may be broadly acceptable for gas carriers in terms of eco-efficiency. The system achieves high availability by using fault tree analysis and minimal cut sets.

GMCS: fast computation of genetic minimal cut sets in large networks.

The identification of minimal gene knockout strategies to engineer metabolic systems constitutes one of the most relevant applications of the COnstraint-Based Reconstruction and Analysis (COBRA) framework. In the last years, the minimal cut sets (MCSs) approach has emerged as a promising tool to carry out this task. However, MCSs define reaction knockout strategies, which are not necessarily transformed into feasible strategies at the gene level. We present a more general, easy-to-use and efficient computational implementation of a previously published algorithm to calculate MCSs to the gene level (gMCSs). Our tool was compared with existing methods in order to calculate essential genes and synthetic lethals in metabolic networks of different complexity, showing a significant reduction in model size and computation time. gMCS is publicly and freely available under GNU license in the COBRA toolbox (https://github.com/opencobra/cobratoolbox/tree/master/src/analysis/gMCS). Supplementary data are available at Bioinformatics online.

Process Pipeline Settlement Analysis of Gas Transmission Station in the Soft Soil Area

The fault tree analysis method is used herein to carry on the process pipeline settlement analysis of gas transmission station in the Pearl River Delta soft soil area. Firstly, establish the pipeline settlement fault tree with the help of CAFTA fault tree analysis software. Next, carry on the qualitative analysis to the fault tree with the method of minimum cut set, further do the quantitative evaluation by expert estimation and fuzzy mathematics analysis method. In this way, main factors to the pipeline settlement and weak points of the foundation treatment are disdinguished. Finally, we point out the basic events which should be pay attention to during the gas pipeline project of the soft soil area.

Advanced combinatorial method for solving complex fault trees

Combinatorial explosion is a common problem to both predominant methods for solving fault trees: Minimal Cut Set (MCS) approach and Binary Decision Diagram (BDD). High memory consumption impedes the complete solution of very complex fault trees. Only approximated non-conservative solutions are possible in these cases using truncation or other simplification techniques. The paper proposes a new method (CSolv+) for solving complex fault trees, without any possibility of combinatorial explosion. Each individual MCS is immediately discarded after its contribution to the basic events importance measures and the Top gate Upper Bound Probability (TUBP) has been accounted. An estimation of the Top gate Exact Probability (TEP) is also provided. Therefore, running in a computers cluster, CSolv+ will guarantee the complete solution of complex fault trees. It was successfully applied to 40 fault trees from the Aralia fault trees data base, performing the evaluation of the top gate probability, the 1.000 Significant MCSs (SMCS) and the Fussell-Vesely, RRW and RAW importance measures for all basic events. The high complexity fault tree nus9601 was solved with truncation probabilities from 10−21 to 10−27, just to limit the execution time. The solution corresponding to 10−27, evaluated 3.530.592.796 MCSs in 3 h and 15 min.

AIMS-MUPSA software package for multi-unit PSA

The need for a PSA (Probabilistic Safety Assessment) for a multi-unit at a site is growing after the Fukushima accident. Many countries have been studying issues regarding a multi-unit PSA. One of these issues is the problem of many combinations of accident sequences in a multi-unit PSA. This paper deals with the methodology and software to quantify a PSA scenarios for a multi-unit site. Two approaches are developed to quantify a multi-unit PSA. One is to use a minimal cut set approach, and the other is to use a Monte Carlo approach.