Basic Events Research Articles

Importance-Based Key Basic Event Identification and Evolution Mechanism Investigation of Hydraulic Support Failure to Protect Employee Health.

Background: Although hydraulic support can help enterprises in their production activities, it can also cause fatal accidents. Methods: This study established a composite risk-assessment method for hydraulic support failure in the mining industry. The key basic event of hydraulic support failure was identified based on fault tree analysis and gray relational analysis, and the evolution mechanism of hydraulic support failure was investigated based on chaos theory, a synthetic theory model, and cause-and-effect-layer-of-protection analysis (LOPA). Results: After the basic events of hydraulic support failure are identified based on fault tree analysis, structure importance (SI), probability importance (PI), critical importance (CI), and Fussell–Vesely importance (FVI) can be calculated. In this study, we proposed the Fussell–Vesely–Xu importance (FVXI) to reflect the comprehensive impact of basic event occurrence and nonoccurrence on the occurrence probability of the top event. Gray relational analysis was introduced to determine the integrated importance (II) of basic events and identify the key basic events. According to chaos theory, hydraulic support failure is the result of cross-coupling and infinite amplification of faults in the employee, object, environment, and management subsystems, and the evolutionary process has an obvious butterfly effect and inherent randomness. With the help of the synthetic theory model, we investigated the social and organizational factors that may lead to hydraulic support failure. The key basic event, jack leakage, was analyzed in depth based on cause-and-effect-LOPA, and corresponding independent protection layers (IPLs) were identified to prevent jack leakage. Implications: The implications of these findings with respect to hydraulic support failure can be regarded as the foundation for accident prevention in practice.

Comprehensive Risk Management in Passive Buildings Projects

Nowadays, we can observe a growing interest in passive buildings due to global climate change, environmental concerns, and growing energy costs. However, developing a passive building is associated with meeting many Passive House requirements, which results in their increased complexity as well as many challenges and risks which could threaten the successful completion of the project. Risk management is a key tool enabling meeting today’s challenging passive house project’s demands connected with quality, costs, deadlines, and legal issues. In this paper, a new model of risk management dedicated for passive buildings based is proposed, in which a novel Fuzzy Fault Tree integrated with risk response matrix was developed. We proposed 171 risk remediation strategies for all 16 recognized risks in passive buildings projects. We show how to apply the proposed model in practice on one passive building example. Thanks to applying the proposed risk management model an effective reduction of the risks of the basic event is enabled, leading to a significant reduction of the top event risk. The proposed model is useful for architects, installation designers, contractors, and owners who are willing to develop attainable and successful passive buildings projects that benefit all stakeholders.

The Risk Assessment of Genset Installation Project Using Fault Tree Analysis In Indonesia

The XYZ company had a project to install the generator set (genset) in several island in Indonesia. The project was estimated to finish in 10 months, but it delayed up to 20 months. This delayment made the company experience cost overruns. In the other hand, according to Indonesian Ministry of Energy and Mineral Resource (MSDM) in 2016, the electrification in this project area has not reached 100%. The area are including Kalimantan, West Nusa Tenggara (WTB), Papua, Sulawesi and Maluku. The tardiness was caused by the company can't mitigate the project risk optimally. Therefore this research aims to evaluate this genset installation project to assess the risk, thus in the next project the company can avoid project delay and the overruns cost. The research uses Fault Tree Analysis (FTA) in risk assessment to identify the basic event of the project’s problem. First, this research collect the report of the project. Second, this project collect the problems that caused project delay. There are 154 problems found in this research. The FTA method divides the problems found into 13 basic event. The highest risk that triggers problem for this project are from two basic events, which are user error with the probability rate 0,2013 and installation error with the probability rate 0,1494.

Risk Analysis and Reliability Assessment of Overhead Cranes Using Fault Tree Analysis Integrated with Markov Chain and Fuzzy Bayesian Networks

Establishing an adequate level of reliability in the overhead crane operations is an important and vital principle to avoid undesirable consequences. To do this, it is appropriate to have a comprehensive approach for risk and reliability assessment of the most probable failure scenarios during overhead crane operations. In this study, fault tree analysis (FTA) in combination with fuzzy set theory, Bayesian network (BN), and Markov chain was used to evaluate the probability of top event and reliability of overhead cranes. A total of 47 basic events were identified for ladle fall in overhead cranes. The results showed that the probability of the ladle fall in the FT approach is equal to 0.0523035 and in the BN approach in the prior event is equal to 0.0273394 which is less than the FT method. Based on the values predicted by Markov chain, the reliability of the system decreases over time by 67.9% after 60 months. This study showed that the plan for ladle fall prevention should consider all influencing parameters identified by proper risk assessment methodologies.

Fuzzy fault tree reliability analysis based on improved T-S model with application to NC turret

In Takagi and Sugeno (T-S) fuzzy fault tree analysis (FFTA), the construction of T-S fuzzy gates relies too much on expert experience, which will result in inevitable subjective errors. In order to overcome this disadvantage, a new method was proposed in which the construction of T-S gates no longer relies solely on historical data and expert experience but is also determined by the importance of the basic events to the top event. In the proposed method, fault degrees were described as fuzzy numbers; fault probabilities were described as fuzzy possibilities. The importance index of basic events can be solved through the analysis of the fuzzy fault tree model by Monte Carlo (MC) simulation. The proposed method is suitable for systems where exact information on the fault probabilities of the components and the magnitude of failure and effect on the system are not available. The concept and calculation method of T-S probability importance was presented. Finally, the proposed method is applied to analyze the reliability of the NC turret seal subsystem, the accuracy of the method is verified by comparing with the methods based on traditional FFTA and T-S FFTA, and the weak points of the system are obtained by importance analysis, which will provide data for system fault diagnosis and preventive maintenance.

Applications of FFTA–HFACS for Analyzing Human and Organization Factors in Electric Misoperation Accidents

Human and organizational factors (HOFs) play an important role in electric misoperation accidents (EMAs), but research into the reliability of human factors is still in its infancy in the field of EMAs, and further investment in research is urgently required. To analyze the HOFs in EMAs, a hybrid method including the Human Factors Analysis and Classification System (HFACS) and fuzzy fault tree analysis (FFTA) was applied to EMAs for the first time in the paper. HFACS is used to identify and classify the HOFs with 135 accidents, reorganized as basic events (BEs), intermediate events (IEs), and top event (TE), and develop the architecture of fault tree (FT). Fuzzy aggregation is employed to address experts’ expressions and obtain the failure probabilities of the BEs and the minimal cut sets (MCSs) of the FT. The approach generates BEs failure probabilities without reliance on quantitative historical failure statistics of EMAs via qualitative records processing. The FFTA–HFACS model is applied for quantitative analysis of the probability of failure of electrical mishaps and the interaction between accident risk factors. It can assist professionals in deciding whether and where to take preventive or corrective actions and assist in knowledgeable decision-making around the electric operation and maintenance process. Finally, applying this hybrid method to EMAs, the results show that the probability of an EMAs is 1.0410 × 10−2, which is a risk level that is likely to occur and must be controlled. Two of the most important risk factors are habitual violations and supervisory violation; a combination of risk factors of inadequate work preparation and paralysis, and irresponsibility on the part of employees are also frequent errors.

Risks of water and wastewater PPP projects: an investors’ perspective

PurposeWater and wastewater (WW) projects are gaining attention in Iran because of shortages of water resources. However, these projects are lengthy and they are accompanied by numerous risks, such as lack of sufficient financial resources. Public–private partnerships (PPPs) are taken into account as a constructive approach to deal with the problem of insufficient government funds and they are increasingly being implemented to construct the required infrastructures in different countries. Although WW projects in PPPs can reduce the government’s debt, investors are still uncertain about this approach. Hence, this study aims to identify and evaluate the risk of all parties involved in WW-PPP projects, from the viewpoint of investor.Design/methodology/approachFirst, the risk factors which are involved in WW projects are identified by interviewing experts and reviewing the literature by means of fault tree analysis (FTA) tool. Second, the probability and effects of the risky factors which are related to specific event are evaluated and analyzed by hybridization of interval fuzzy Type-2 sets (IT2FS) and risk score formulation. Finally, some solutions are proposed to deal with the most challenging risks.FindingsSix gate events, namely, risks which are related to investors such as investor’s consultant-related risks, risky conditions from engineering, procurement, and construction (EPC) contractors’ point of view, risk factors which public sector takes into account, public sector’s consultant-related risks which public sector’s consultant consider challenging and external factors were defined according to the literature. From FTA tool and by interviewing the experts, 94 basic events were identified. Finally, from hybridization of IT2FSs and risk score formulation, top five risks are determined as “Difficulty of injecting financial resources into the project,” “Fluctuation in inflation rate,” “Poor decision-making process” in public sector, “Difficulty of importing the equipment which are required for the project (such as pumps, grain catchers, garbage collectors, etc.) from other countries” and “Impact of risky conditions in other projects on operation of PPP project.”Originality/valueIn the absence of a constructive approach for risk identification and a reliable model for evaluating the identified risks in PPP projects, this research project is one of the first research studies which used FTA for identifying risks and hybridization of IT2FSs and risk score formulation for evaluating the risks.

Study on explosion risk assessment of low‐concentration gas safe combustion system based on FAHP‐fuzzy fault tree

AbstractExplosion is the most dangerous accident during direct combustion of low‐concentration gas. Few investigations have focused on explosion risk assessment of low‐concentration gas safe combustion system. This study aims to analyze explosion risk of above system. Due to insufficient accident data for calculating the failure probability of explosion, expert evaluation method and fuzzy algorithm were adopted to obtain the failure probability of basic events (BEs) and Fuzzy Analytic Hierarchy (FAHP) Process method used to improve the calculation of expert weights. Then qualitative and quantitative analysis was carried out using fault tree analysis. Results show that the failure probability of system explosion is 0.085%. Events with high‐risk probability are mainly on equipment management and personnel behavior norms. Safe combustion system has excellent performance on tempering prevention, explosion resistance and explosion relief. The outcomes of this study are expected to help the safety professionals while formulating safety management measures for low‐concentration gas safety combustion system.

Risk assessment of floating offshore wind turbines based on fuzzy fault tree analysis

Risk assessment of Floating Offshore Wind Turbines (FOWTs) relies on failure statistics, which are usually collected from various source. In order to quantify the information uncertainties, this paper introduces the Fuzzy Fault Tree Analysis (FFTA) to assess the risk of semi-submersible FOWTs. A Fault Tree (FT) model is adopted to analyze the risk evolution mechanism of the FOWT and the fuzzy set theory is employed to process the failure statistics. As the results of quantitative analysis, the failure intervals of the FOWT and critical assemblies are calculated. The risk measure named Fuzzy Critical Importance (FCI) is utilized to compute the sequence of the basic fault events and identify critical components. A comparison analysis is performed and the results indicate that the present FFTA method is more in line with practical and has the merit in error reduction of failure rate figured out.

A fault tree-based approach for aviation risk analysis considering mental workload overload

Many lives and aircrafts have been lost due to human errors associated with mental workload overload (MWLOL). Human errors are successfully considered in existing Fault Tree Analysis (FTA) methods. However, MWLOL is considered through Performance Shaping Factors indirectly and its information is hidden in FT construction, which is not conducive to analyze the root causes of human errors and risks. To overcome this difficulty, we develop a risk analysis method where Multiple Resources Model (MRM) is incorporated into FTA methods. MRM analyzes mental workload by estimating the resources used during performing concurrent tasks, probably including abnormal situation handling tasks introduced by basic events in FT. Such basic events may cause MWLOL and then trigger corresponding human error events. A MWLOL gate is proposed to describe MWLOL explicitly and add these new relationships to traditional FT. This new method extends previous FTA methods and provides a more in-depth risk analysis. An accident, a helicopter crash in Maryland, is analyzed by the proposed method.

Probabilistic analysis of aluminium production explosion accidents based on a fuzzy Bayesian network

Explosion accidents of molten aluminium in contact with water during aluminium production often occur and may cause injury and death. In this paper, a fuzzy Bayesian network (BN) was employed to probabilistically analyse the explosion accident of molten aluminium in contact with water. A fault tree-Bayesian network (FT-BN) model was established in the cause-effect analysis of the explosion accident, including three processes: electrolysis, molten aluminium transportation and aluminium casting. Fifty-three nodes were proposed in the model to represent the evolution process of the explosion accident from failure causes to consequences. Furthermore, the occurrence probabilities of basic events (BEs) were determined by expert judgement with weighted treatments based on fuzzy theory. By giving certain occurrence probabilities of each BE, the probability of an explosion accident was estimated. Subsequently, importance measures were assessed for each BE, which could reflect the impact on the occurrence of the top event (TE), and the final ranks were provided. The results indicate that using wet ladles and tools, water on the ground, breakage of the tap hole, damage to the casting mould, and leakage of circulating water are five main problems that cause explosion accidents. Safety advice was provided based on the analysis results. This study can help decision makers improve the safety management of aluminium production.

Entropic Explanation of Power Set

A power set of a set S is defined as the set of all subsets of S, including set S itself and empty set, denoted as P(S) or 2S. Given a finite set S with |S|=n hypothesis, one property of power set is that the amount of subsets of S is |P(S)| = 2n. However, the physica meaning of power set needs exploration. To address this issue, a possible explanation of power set is proposed in this paper. A power set of n events can be seen as all possible k-combination, where k ranges from 0 to n. It means the power set extends the event space in probability theory into all possible combination of the single basic event. From the view of power set, all subsets or all combination of basic events, are created equal. These subsets are assigned with the mass function, whose uncertainty can be measured by Deng entropy. The relationship between combinatorial number, Pascal's triangle and power set is revealed by Deng entropy quantitively from the view of information measure.

Safety risk assessment intelligent system for on-foot construction worker using fuzzy fault tree

A risk assessment model is developed to estimate the potential combined influence of concurrent safety risks facing on-foot construction worker at a certain point in space or instant of time. The model is based on a holistic approach that comprehensively systemizes principal types and subjective values of possible safety risk events. Fuzzy fault tree is built using a deductive approach to identify possible concurrent basic and conditional risk events, not risk symptoms, from the major subgroups of triggering, enabling and environment-related risks. The inclusive risk breakdown structure helps in combating assessment underestimation related to overlooking influential risks. Adequate logic gates are suggested at tree junctions to overcome assessment overestimation related to accumulating the effect of dependent, redundant, and non-concurrent risks, and ignoring the effectiveness of safety precautions and measures that may reduce or eliminate risks. Operational logic gates are applied to properly combine the residual risk of static (non-moving) events and dynamic (moving) events that can concurrently influence safety. The model is programmed into an interactive interfaced intelligent system to simulate cases of risk assessment input, computations, and output. The system shows the advantages of using the model as a prognostic or diagnostic tool to estimate top risk event. Subjective linguistic risk values can be induced for basic risk events at the bottom of the tree, and conditional risk events controlling residual risk values can be induced at different levels of the tree. Fuzzy logic plays a key role in hosting subjective risk evaluation into computational truth values to generate realistic and meaningful assessment values that are helpful for risk control.

The Importance of Studying Human Brain

Abstract Due to its numerous distinctive functions and unique pathology, the human brain, or rather forebrain has been difficult to study in common animal models. Although many basic molecular and cellular events are conserved across species, human brain connectivity, pertinent especially to the cerebral cortex circuitry, is unique and demands extensive research. Despite a great advancement in functional imaging methods accomplished over the last two decades, many basic features of healthy and diseased human forebrain remain elusive. Here we address difficulties in anatomical studies of developing and adult human brain and indicate the new directions and challenges to be addressed in the future. We pay special attention to possibilities of translating animal brain research to human cases. We consider that, although animal experiments play a vital role in understanding fundamental molecular and cellular mechanisms behind brain function, understanding of higher brain functions (language, intelligence, memory) has to be based on understanding uniqueness of human circuitries. Furthermore, brain is the site of many human-specific diseases, such as multiple sclerosis, schizophrenia, and Alzheimer’s disease, for which only partial animal models exist. To study human brain, thus, remains irreplaceable in the quest for new therapeutic tools, as well as in understanding the essence of our being.

Application of FTA Analysis for Calculation of the Probability of the Failure of the Pressure Leaching Process

European Union legislation requires organizations to assess their processes in the context of risk management. The main task of risk management is to manage all risks that can significantly affect the outcome of processes. The article is focused on risk evaluation in pressure leaching at elevated temperature using the method Fault Tree Analysis (FTA). The effectivity of pyrite and arsenic pyrite decomposition by oxidative pressure leaching is influenced by the duration of the process, by the temperature, concentration of the leaching solution and by a density of the slurry. It was found that, under equitable conditions, the arsenic pyrite decomposes more intensely than pyrite. Under laboratory conditions, leaching is performed in an autoclave. Due to the aggressive environment, increased pressure and temperature, process failure is possible. Its probability was calculated by FTA. It has been found that the probability of the top event in the examined process was disproportionately high (0.057) and represents an invitation to take corrective actions. The Monte Carlo method was used for the simulation of the effect the probability of basic events on the probability of the top event—the failure of the leaching process.

Regulation of metabolic homeostasis by the TGF-β superfamily receptor ALK7.

ALK7 (Activin receptor-like kinase 7) is a member of the TGF-β receptor superfamily predominantly expressed by cells and tissues involved in endocrine functions, such as neurons of the hypothalamus and pituitary, pancreatic β-cells and adipocytes. Recent studies have begun to delineate the processes regulated by ALK7 in these tissues and how these become integrated with the homeostatic regulation of mammalian metabolism. The picture emerging indicates that ALK7's primary function in metabolic regulation is to limit catabolic activities and preserve energy. Aside of the hypothalamic arcuate nucleus, the function of ALK7 elsewhere in the brain, particularly in the cerebellum, where it is abundantly expressed, remains to be elucidated. Although our understanding of the basic molecular events underlying ALK7 signaling has benefited from the vast knowledge available on TGF-β receptor mechanisms, how these connect to the physiological functions regulated by ALK7 in different cell types is still incompletely understood. Findings of missense and nonsense variants in the Acvr1c gene, encoding ALK7, of some mouse strains and human subjects indicate a tolerance to ALK7 loss of function. Recent discoveries suggest that specific inhibitors of ALK7 may have therapeutic applications in obesity and metabolic syndrome without overt adverse effects.

Potential roles of super enhancers in inflammatory gene transcription.

Acute and chronic inflammation is a basic pathological event that contributes to atherosclerosis, cancer, infectious diseases, and immune disorders. Inflammation is an adaptive process to both external and internal stimuli experienced by the human body. Although the mechanism of gene transcription is highly complicated and orchestrated in a timely and spatial manner, recent developments in next-generation sequencing, genome-editing, cryo-electron microscopy, and single cell-based technologies could provide us with insights into the roles of super enhancers (SEs). Initially, SEs were implicated in determining cell fate; subsequent studies have clarified that SEs are associated with various pathological conditions, including cancer and inflammatory diseases. Recent technological advances have unveiled the molecular mechanisms of SEs, which involve epigenetic histone modifications, chromatin three-dimensional structures, and phase-separated condensates. In this review, we discuss the relationship between inflammation and SEs and the therapeutic potential of SEs for inflammatory diseases.

Human Reliability Analysis for Cardiopulmonary Resuscitation Process in Emergency Medicine Using a Modified Hybrid Method Based on the Markov Model and Fault Tree Analysis

Introduction:In emergency departments (ED), human reliability assessment is essential for improving the quality of treatment and preventing medical accidents. A medical accident is expressed as an injury to a patient caused by the negligence of a doctor or nurse who is providing medical care. This study aimed to assess the human reliability in the cardiopulmonary resuscitation (CPR) process and recommend some comments to minimize human errors and improve patient safety.Materials and Methods: The main factors in the CPR process (such as rate and depth of chest compression and rate of ventilation) are identified based on the American heart association (AHA) roles. Data were recorded during three months in the evening shifts in the ED and CPR room of Imam Reza Hospital in Mashhad, Iran. In total, 42 samples were collected, and a modified hybrid approach according to the fault tree analysis and Markov method was proposed for the analysis of CPR team (including emergency medicine, medical interns, and nurses) reliability in the resuscitation process. Finally, the important basic events (errors) were selected using the Boruta algorithm by R software.Results: An FTA-Markov-based hybrid method is considered to compute the human reliability in the CPR process. The obtained results from human reliability analysis using the sensitivity analysis via Boruta algorithm and the proposed hybrid method show that an interrupt between chest compression process for rhythm control, the cycle of CPR, the depth of chest compression, and the discussion about reversible causes are the most effective factors in the human reliability of CPR process.Conclusion:The human reliability of the CPR process in the ED has been assessed using a hybrid method based on the FTA and Markov method for the first time. To improve the quality of treatment and prevent medical accidents during the CPR process, the main factors in the process are identified, and then, the proposed hybrid method is used to calculate human reliability.

The Synergic Role of Actomyosin Architecture and Biased Detachment in Muscle Energetics: Insights in Cross Bridge Mechanism beyond the Lever-Arm Swing

Muscle energetics reflects the ability of myosin motors to convert chemical energy into mechanical energy. How this process takes place remains one of the most elusive questions in the field. Here, we combined experimental measurements of in vitro sliding velocity based on DNA-origami built filaments carrying myosins with different lever arm length and Monte Carlo simulations based on a model which accounts for three basic components: (i) the geometrical hindrance, (ii) the mechano-sensing mechanism, and (iii) the biased kinetics for stretched or compressed motors. The model simulations showed that the geometrical hindrance due to acto-myosin spatial mismatching and the preferential detachment of compressed motors are synergic in generating the rapid increase in the ATP-ase rate from isometric to moderate velocities of contraction, thus acting as an energy-conservation strategy in muscle contraction. The velocity measurements on a DNA-origami filament that preserves the motors’ distribution showed that geometrical hindrance and biased detachment generate a non-zero sliding velocity even without rotation of the myosin lever-arm, which is widely recognized as the basic event in muscle contraction. Because biased detachment is a mechanism for the rectification of thermal fluctuations, in the Brownian-ratchet framework, we predict that it requires a non-negligible amount of energy to preserve the second law of thermodynamics. Taken together, our theoretical and experimental results elucidate less considered components in the chemo-mechanical energy transduction in muscle.

Risk Assessment of Petroleum Products Loading Arm by BTA Technique

Background: Loading of petroleum products consists of several parts, of which the arm platform section is known to be the source of most accidents. Objectives: Therefore, this study was done to evaluate the risk of arm loading platforms using the bow-tie analysis (BTA) technique to identify the causes and the probability of occurrence of hazardous events. Methods: In this study, we first identified the risks of the loading arm using the expert’s judgment. The risk of overflow is considered as the top event. Then, the basic events were identified by the fault tree analysis (FTA), and the possible consequences of the top event were predicted using the event tree. Next, using the computational equations, the probability of spillover and its consequences were calculated. The path of the risk event from the causal phase to the consequent phase was also illustrated by sketching the structure of the BTA. Results: A total of 14 basic events and 8 intermediate events were involved in the occurrence of the top event, and 5 consequences were identified for the risk of spillover. The probability of the top event occurring was calculated to be 3.12 × 10-7. Conclusions: According to the results of this study, tank overflow is one of the most important hazards in the loading arm section.