Fault Tree Research Articles

Assessing the reliability of natural gas pipeline system in the presence of corrosion using fuzzy fault tree

The corrosion encountered within natural gas pipelines can precipitate significant ramifications. Numerous internal and external factors contribute to incidents of gas leakage. A multitude of factors influencing pipeline failure underscore the imperative need for a safety system intricately linked to the operation process. The absence of this systematic process for detecting factors contributing to failure detrimentally impacts the efficiency of pipelines. In this context, this paper has devised a risk assessment and warning model utilizing multi-factor monitoring data, employing the fuzzy fault tree analysis (FFTA). The fuzzy fault tree is constructed to assess the impact of individual factors and parameters influencing corrosion on the reliability of the grid. Moreover, a performance diagram illustrating this mechanism is crafted, elucidating the system's reliability relationship based on each component's reliability. The findings showed that 14 basic and 10 intermediate events play a role in the corrosion of natural gas pipelines. The failure probability of the top event was identified to be 22%. Employing the proposed method, the system's reliability was estimated with lower and upper limits of [0.6825, 0.8859]. The obtained results demonstrate the effectiveness and efficiency of the proposed method in addressing the uncertainty inherent in the input data.

Safety System Study of Gas Stations Based on Preliminary Hazard Analysis and Fault Tree Analysis

Safety System Study of Gas Stations Based on Preliminary Hazard Analysis and Fault Tree Analysis

Comparing the safety of bunkering LH2 and LNG using quantitative risk assessment with a focus on ignition hazards

Liquid hydrogen represents a potential candidate for a climate neutral fuel for shipping. The utilization of this fuel necessitates the implementation of safe and reliable bunkering operations. This paper employs a quantitative risk assessment to compare the safety of bunkering liquid hydrogen with the safety of bunkering LNG. Initially, a frequency analysis is conducted using an event tree. It can be demonstrated, that the occurrence of the hazardous events, pool fire, flash fire and explosion, is more frequent with liquid hydrogen than with LNG. In the second step, the consequence analysis determines necessary safety distances for the hazardous events under consideration. For the events of pool fire and explosion, LNG-bunkering requires higher safety distances. Liquid hydrogen-bunkering requires higher distances for flash fire event. Since the safety distances for flash fire events are largest, they define the distances for the system. However, the consequences of flash fire events are subject to greater uncertainties and require further investigation. Overall, hazardous events occur more often with liquid hydrogen-bunkering, but LNG-bunkering requires in two out of three cases larger safety distances.

Small data-based maintenance planning for a Tainter gate using component and system reliability

This paper presents a method using small data to enhance maintenance efficiency, addressing the limitations of solely qualitative maintenance records. It involves the use of a model based on the Bayesian–Weibull first-order reliability method (BW-FORM) for component analysis and a stochastic analytic hierarchy process for system-level assessment, including fault-tree analysis and reliability-centered maintenance for prioritizing tasks. Key components such as “gate body” and “wire rope” significantly affect system reliability, whereas “rusted crane base” and “bolt on base falling” are the top maintenance priorities. The Mudan Reservoir case study validates this approach, with the life expectation estimated using the BW-FORM aligning well with expert predictions.

A dynamic decision-making approach for cabin unlawful interference emergency disposal using dynamic Bayesian network

Disposal of unlawful interference incidents is essential for is crucial for the advancement of aviation security. Effective emergency disposal requires a comprehensive approach that includes the perspectives of airlines, airports, and passengers. In this context, each component of the disposal process can fail randomly. The objective of this research is to optimize emergency disposal decisions to enhance the efficiency of civil aviation operations, reduce accidents, and lower costs. Given the dynamic complexity of unlawful interference incidents, a dynamic fault tree consisting of 26 nodes was constructed to analyze the emergency disposal process. To explore the relationships and priorities of each event, the Dynamic Fault Tree is converted into a dynamic Bayesian network. Based on historical statistical data, simulation analysis is conducted in three aspects: posterior probability, sensitivity, and importance. Simulation results reveal that the top three critical nodes in cabin unlawful interference incidents are “structural damage to the cabin,” “inadequate training by airlines,” and “untimely airport police takeover of disruptive passengers.” Further analysis shows that (1) most of the critical nodes are associated with airlines. (2) The decision-making rationale and pathways of the critical nodes can be clearly observed and prioritized. (3) Besides airlines, other entities such as airports can implement targeted emergency disposal measures. Through quantitative analysis and simulation, this study provides decision-making guidance for participating groups on dynamic emergency disposal, thereby enhancing civil aviation security.

Transformer Fault Diagnosis and Location Method Based on Fault Tree Analysis

Transformer Fault Diagnosis and Location Method Based on Fault Tree Analysis

Research on low-speed unmanned vehicle diagnosis system based on fault tree

Abstract To reduce the safety risks of low-speed unmanned vehicles losing control and colliding with pedestrians or vehicles due to malfunctions during autonomous task execution, Fault Tree Analysis (FTA) is used to analyze the safety of low-speed unmanned vehicles. A low-speed unmanned vehicle fault diagnosis system is designed to take corresponding measures in case of vehicle faults and improve vehicle driving safety.

Failure analysis of air-conditioning system of domestic rolling stock based on fuzzy fault tree

Failure analysis of air-conditioning system of domestic rolling stock based on fuzzy fault tree

Dynamic Fault Tree Model of Civil Aircraft Avionics Network Transmission Failure Based on Optimized Extended Fuzzy Algorithm

Dynamic Fault Tree Model of Civil Aircraft Avionics Network Transmission Failure Based on Optimized Extended Fuzzy Algorithm

LOGICAL-PROBABLIC MODELING OF FAILURES OF GEODESIC NETWORKS

The credibility and reliability of the results of geodetic and cadastral works depends mainly on the accuracy of the instruments, the qualification of the observer, his professionalism and the reliability of the points of the geodetic network (GN). As a rule, in most cases, there is a well-founded choice of geodetic tools suitable for accuracy and the involvement of a highly qualified geodetic engineer to perform certain types of geodetic work. However, certain questions may arise regarding the determination of starting points for the creation of a reliable geodetic survey justification. The issue of selecting reliable geodetic points for performing engineering and geodetic works based on the application of reliability assessment methods is an urgent scientific problem today. The purpose of the work is to establish the optimal reliability assessment method based on the analysis of existing ones. Adapt this method to solve the problem of assessing the reliability of geodetic networks as one of the most important parameters characterizing its condition. Assess the reliability of the Dnipro geodetic network by constructing a fault tree. Calculate the dynamics of the intensity of GN failures during the 100-year period of its existence. Calculate the appropriate periodicity of surveys (monitoring) of GN depending on the intensity of failures of elements (geodetic points). Methodology. Analysis of international and national standards for reliability assessment, Standards of Ukraine, where the methods of system reliability assessment are given. Review of methods for assessing GN reliability. The deductive method with the construction of a geodetic network failure tree has been applied. This method is based on a logic-probabilistic model of cause-and-effect relationships of system failures with failures of its elements and other events. Scientific novelty. The optimal method of assessing the reliability of GN has been established. A GN failure tree has been built in the TopEvent FTA software tool. The reliability of the geodetic network has been evaluated, the intensity of failures at various stages of its operation has been calculated. Mathematical expressions of the failure functions of the geodetic network have been described by applying Boolean functions. Practical value. International and national regulatory documents and Standards of Ukraine of reliability assessment have been analyzed. In Standarts the methods of system reliability assessment have been given. The performed assessment of the reliability of the state of the geodetic network of the city of Dnipro helps to choose stable geodetic points for the creation of local geodetic networks and survey justification. Reasonable periodicity of monitoring for the survey of geodetic points has been substantiated. The use of reliable points of geodetic networks will allow obtaining reliable observation data, which will significantly increase the quality of engineering and geodetic works. Results. The functioning of the geodetic network of the city of Dnipro on the constructed sequential tree of failures has been considered. Boolean functions to describe the mathematical expressions of the failure functions of the geodetic network, which includes 5 and 10 elements have been used.

Reliability model and emergency maintenance strategies for smart home systems

After the smart home system is impacted by malicious attacks or other factors, the system reliability drops drastically, so the user's living environment is greatly disturbed. To determine the emergency maintenance strategy, firstly, we study the failure mechanism of the smart home system by the fault tree theory, and distinguish the components into two types: critical components and non-critical components. Secondly, a recovery prioritization is proposed to measure the extent to which changes in the reliability of each component affect the reliability of the system. Then, three scenarios of smart home system failure are proposed. Under the constraints of time and cost, the maintenance strategies for the three scenarios are determined to achieve emergency recovery. Finally, through the multi-objective particle swarm optimization algorithm, the system reliability is maximized, the maintenance cost is minimized, and the optimal reliability recovery level of each component is obtained, so that the reliability of the smart home system is further improved. The effectiveness and practicality of the emergency maintenance strategies proposed in this paper are demonstrated by a smart home system example.

Dynamic Seismic Probabilistic Risk Assessment of Nuclear Power Plants Using Advanced Structural Methodologies

The conditional core damage probability (CCDP) of a representative nuclear power plant is estimated for a beyond design basis earthquake (BDBE) using state-of-the-art structural models within a dynamic probabilistic risk assessment (DPRA) framework. Randomness of seismic excitation and uncertainty of structural parameters are considered using a simulation-based approach. Finite element models are developed for the structure and a liquid container (hydro-accumulator), and fluid–structure interaction is considered with the arbitrary Lagrangian-Eulerian method. The CCDP is evaluated through a time-dependent event tree. Also, correlation among multiple hydro-accumulators is investigated. The results show that operator action and implementation time of mobile safety equipment are critical under BDBE in case of loss of offsite power following an earthquake. It was also found necessary to adopt a DPRA approach to determine the available time for action and core damage timing probabilistically.

Analysis Of Defects In Laminated Doors Using Failure Mode And Effect Analysis (FMEA) And Fault Tree Analysis (FTA)

Quality control is an crucial part of the production process because product quality must meet established standards. Based on drawback that happen in the laminating door production process, prioritizing different failure types is essential to reduce the occurrence of defects in the same production process. To enhance product quality and minimize defects, consider implementing by using Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA). The purpose of this study is to identify the types of factors causing product defects in the laminating door production process and provide recommended actions in the improve phase to minimize the number of defects. This study analyzes six types of defects in laminating door products. The results show that operator errors are the dominant cause, influenced by environmental conditions and an unsupportive work system. Based on the Risk Priority Number (RPN) values, the defects with the highest values are glue not sticking (RPN 294) caused by machine factors, cracks (RPN 252) by method factors, groove size not meeting specifications (RPN 245) by man factors, peeling paint (RPN 180) by method factors, scratches on the laminate surface (RPN 175) by man factors, and imprecise joints (RPN 120) by man factors. Improvement suggestions include operator training, machine maintenance, replacement of inadequate equipment, selection of appropriate raw materials, and implementation of clear Standard Operating Procedures.

Integrating reliability analysis into MBSE for FPGA-based safety critical I&C system design in nuclear power plants

Abstract With the widespread application of Field Programmable Gate Array (FPGA) technology in the instrumentation and control (I&C) systems of nuclear power plants (NPPs), its design reliability has become the key to ensuring the subsequent safe operation of NPPs. However, the traditional document-based design method is no longer sufficient to meet the current design needs of complex systems, and there is a lack of research related to the reliability and security analysis of FPGA-based systems. Therefore, the overall goal of this study is to integrate reliability analysis into the model-based systems engineering (MBSE)-based design of FPGA-based I&C systems. Based on the typical application characteristics of the FPGA, a digital design framework for FPGA-based systems is proposed to realize a traceable design process from requirements to implementation. Subsequently, a model-based forward comprehensive reliability analysis method is proposed, which uses a SysML-based mapping mechanism to integrate Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) methods into the design process, so as to comprehensively identify and analyze failure modes from systems to components and optimize and improve system design. Finally, the proposed method is applied to the analog output design of FPGA-based systems. The proposed method can provide guidance for improving the reliability of FPGA-based DI&C systems and provide theoretical basis for the further engineering application.

Real-Time rejuvenation scheduling for cloud systems with virtualized software spares

With the increasing popularity of cloud services, there is a growing demand for high reliability and availability of cloud computing. As viable solutions, virtualized software spares and rejuvenation scheduling have been used to maintain highly reliable software platforms and combat Mandelbugs in cloud systems. However, developing real-time rejuvenation schedules for software components with dynamic reliability models has been a challenging task. In this paper, we propose a hybrid approach that integrates preventive and automatic failover strategies to mitigate the harmful effects of Mandelbugs. The approach allows selecting reliability models based on the state of virtualized software components, performing reliability calculations for Software SPare (SSP) gates with up to two virtual hot spares, and scheduling software rejuvenation in real time for cloud systems. Furthermore, the use of Dynamic Fault Tree (DFT) analysis supports the compositional modeling of complex and interconnected systems, alleviating the problem of state-space explosion. Finally, we present a case study of a cloud system with virtualized software spares to demonstrate how rejuvenation schedules can be generated and updated in real time.

Reliability evaluation of a medical oxygen supply system by FTA based on intuitionistic fuzzy sets

The main objective of healthcare centers is to ensure a consistent and high-purity oxygen supply for the safety of patients. Pressure Swing Adsorption (PSA) is a commonly used technique for supplying medical oxygen by eliminating nitrogen from the ambient air. Due to the increased fire risk associated with oxygen, any malfunctions in the oxygen supply system can lead to serious hospital fires. This study aimed to assess the reliability of the oxygen supply system using Fault Tree Analysis (FTA) based on both the traditional method and Intuitionistic Fuzzy Analysis. FTA is a logical analysis method used to identify events that could result in an undesirable top event and calculate the probability of its occurrence. The FTA of the PSA system outlined the logical sequence of events that could lead to the release of oxygen as a top event. The study revealed that the failure of the pressure switch in the concentrator, inadequate sealing, and the use of inappropriate materials for the seals were the primary basic events that led to the release of oxygen. Additionally, this study utilized the Intuitionistic Fuzzy System to quantify experts' opinions, providing more flexibility in handling ambiguous situations and considering both membership and non-membership functions simultaneously.

Fuzzy reliability algorithm for the shutdown system of research reactor

Abstract Probabilistic safety assessment (PSA) has been applied to evaluate the safety of nuclear reactor systems. The results of PSA are used by designers, utilities and regulatory body to confirm the reactor design, to change operation procedures, to enhance the reliability of safety systems, or to modify regulation. Fault tree analysis (FTA) has been used as a deductive means for PSA. System components are assumed to always have defined failure probabilities; however, in reality this assumption is questionable and sometimes there is insufficient data about the failure probability of some components. To solve this problem, fuzzy approaches have been proposed and implemented. The aim of this study is to apply a fuzzy reliability algorithm to estimate basic events failure probabilities for the shutdown system of a research reactor. The reactor is a 22 MW light water open pool type material test reactor and the shutdown system is responsible for the fast shutdown of the reactor whenever safety limits are exceeded. Then, to illustrate the ability of the algorithm, the results are compared with real basic event failure probabilities. The results verify the competence of the algorithm and confirm that it can be applied as an alternative method when quantitative data are not available. Also, a risk importance measure is done on the fault tree of the shutdown system to illustrate which components need to be focused for improvements to achieve the safe operation of shutdown system.

Multilevel assessment method for post-earthquake functionality of medical buildings considering component–department–floor interdependencies

The assessment of the post-earthquake functionality of medical buildings (PEFMB) is critical for the post-earthquake emergency response, recovery, and resilience-based seismic design of medical buildings. Hospitals are complex functional systems that exhibit multilevel functional coupling from components to departments to floors. Existing methods have challenges, including the difficulty of considering the impact of different departments located on different floors on medical functions, and a lack of multilevel performance improvement strategies for enhancing post-earthquake medical functionality. A multilevel assessment method for the PEFMB that considers component–department–floor interdependencies (CDFI) was developed in this study. This method establishes a functional logical relationship between components and departments using fault tree models of typical departments. A multilevel functional coupling relationship among the components, departments, and floors was established by incorporating floor nodes to reflect the impact of departments located on different floors. This enabled the assessment of the PEFMB considering the CDFI. Furthermore, methods for identifying critical failure paths in the PEFMB were developed, and multilevel performance improvement strategies by adjusting medical equipment and departments along the critical failure path were recommended. The proposed method is demonstrated using an outpatient building. The main conclusions are as follows. (1) The proposed multilevel assessment method enables quantitative assessment of the PEFMB and exhibits good scalability. (2) This method provides a clear and intuitive visualization of the critical failure path in healthcare functionality under seismic conditions. The proposed multilevel improvement strategies can enhance the post-earthquake functionality of medical buildings at multiple levels, which provides a valuable reference for the seismic design of medical buildings.

Risk Analysis of Jet A-1 Tank Filling and Storage Processes at the Shorebase

Coastal Logistics Centers (CLS) provide logistics support to deep-sea drilling operations. Jet A-1 (helifuel), required for helicopters that transfer personnel to drilling ships, is filled into tanks from the tanker arriving at CLS and stored in open areas. Jet A-1 is a hazardous chemical with flammable and toxic effects and can also explode when exposed to flame. Risk analysis of this hazardous chemical is essential for CLS. This study aimed to determine the process hazards and risk analysis in the filling and storage operation of Jet A-1 from tankers to tanks. For this purpose, the Preliminary Hazard List (PHL) and Preliminary Hazard Analysis (PHA) were performed. Then, a Hazard and Operability (HAZOP) study was carried out based on these analysis results. The HAZOP study identified Jet A-1 overflow from the tank as a high-risk event. Afterward, Event Tree Analysis (ETA) was performed on the initial event of Jet A-1 spilling due to tank overflow. In ETA analysis, immediate ignition, delayed ignition, and explosion probabilities resulting from delayed ignition were calculated with the CCPS (Center for Chemical Process Safety) Module. The probability and frequency values of accident scenarios were calculated as P=0.0028, f=1.736 x10-4 year-1 for jet fire, P=0.0225, f=1.395x10-3 year-1 for vapor cloud explosion, P=0.127, f=7.874x10-3 year-1 for flash fire, P=0.847, f = 0.0525 year-1 for toxic release, respectively. It was determined that all accident scenario frequency values were above the legislation threshold value (10-4 year-1). Design solutions and preventive measures have been proposed to reduce risks. The combination of risk analysis methods is effective in risk assessment studies.

Risk assessment of aflatoxin in Iowa corn post-harvest using an event tree analysis: A case study.

Mycotoxins are secondary metabolites produced by fungi found in corn and are anticipated to increase globally due to enhanced weather extremes and climate change. Aflatoxin (AFL) is of concern due to its harmful effects on human and animal health. AFL can move through complex grain supply chains in the United States, including multiple stakeholders from farms, grain elevators, grain and ethanol processors, and feed mills, before reaching end users, putting numerous entities at risk. Since corn is an essential food and feed product, risk management of AFL must be considered. This case study aimed to (1) calculate the probabilities of pivotal events with AFL in corn at Food Safety Modernization Act-regulated entities using an event tree analysis (ETA) and (2) propose recommendations based on factors identified through the ETA for AFL risk management. The ETA was based on historical AFL prevalence data in Iowa above a 20-part per billion (ppb) threshold (2.30%). Results showed four single-point failures in feed safety systems, where countermeasures did not function as designed. Failure is defined as the type 2 error of corn being infected with AFL<20 ppb, when it is>20 ppb, and the overall system fails to detect this with contaminated corn reaching end users. The success rate is defined as detecting the corn samples correctly>20 ppb. The average success rate was 50.14%, and the failure rate was 49.86%. It was concluded that risk-informed decisions are a critical component of effective AFL monitoring in corn, with timely intervention strategies needed to minimize the overall effects on end users.