Simultaneous Failure Research Articles

Vulnerability Comparisons of Various Complex Urban Metro Networks Under Multiple Failure Scenarios

Urban metro networks, characterized by their complex systems of interdependent components, are susceptible to a wide range of operational disturbances and threats. Such disruptions can cascade through the system, leading to service delays, operational inefficiencies, and substantial economic losses. Consequently, assessing and understanding network vulnerabilities have become crucial to ensuring resilient metro operations. While many studies focus on single-failure scenarios, comparative vulnerability analyses of various urban metro networks under multiple or simultaneous failures remain limited. To address this gap, our study introduces a comprehensive analytical framework comprising three key components: quantitative indices operating at both network and node levels, methodological approaches to assess the importance of network components (nodes, edges, and lines), and systematic protocols for evaluating vulnerabilities across multiple failure scenarios (stations, tunnels, lines, and areas). A comparative analysis of the Shenzhen Metro Network (SZMN) and the Zhengzhou Metro Network (ZZMN) validates the proposed methods. The results indicate that the SZMN demonstrates higher connectivity and accessibility than the ZZMN, despite a lower network density. Both networks are disassortative and heterogeneous, with edges connecting multiline transfer stations showing significantly higher edge betweenness centrality compared to those connecting general stations. In the SZMN, 6.63% of node failures and 4.74% of tunnel failures exceed a vulnerability threshold of 0.03, compared to 13.74% and 11.27% in the ZZMN. Failures across different lines and areas yield varying impacts on network performance and vulnerability. This study provides essential theoretical and practical insights, helping metro safety managers identify vulnerable points and strengthen the sustainable development of urban metro systems.

Simulation inversion analysis of simultaneous commutation failure of Zhaoyi and Yindong DC

Abstract Aim at the three times simultaneous commutation failure of two Multi-outfeed and Multi-infeed DC Systems in a Similar Path of Ningxia, the Ningxia power grid model is built in Power System Analysis Software Package (PSASP) with actual parameters, and the accident inversion simulation is carried out based on the operation state of the power grid before the fault. Based on the inversion simulation, the simulation results were compared with the measured PMU data. The results showed that the trend of simulation and the measured curve is consistent, and the simulation was slightly more serious than the actual fault, but the overall error was less than 10%, which verified the accuracy of the simulation model and method, and provided a basis for the subsequent simulation analysis of the power grid operation mode.

A Non-Contact AI-Based Approach to Multi-Failure Detection in Avionic Systems

The increasing electrification and integration of advanced controls in modern aircraft designs have significantly raised the number and complexity of installed printed circuit boards (PCBs), posing new challenges for efficient maintenance and rapid failure detection. Despite self-diagnostic features in current avionics systems, circuit damage and multiple simultaneous failures may arise, compromising safety and diagnostic accuracy. To address these challenges, this paper aims to develop a fast, accurate, and non-destructive, multi-failure diagnosis algorithm for PCBs. The proposed method combines a self-attention mechanism with an adaptive graph convolutional neural network to enhance diagnostic precision. A convolutional neural network with residual connections extracts features from scalar magnetic field data, ensuring robust input diversity. The model was tested on a typical dual-phase amplitude boosting circuit with up to four different simultaneous failures, achieving the experimental results of 99.08%, 98.50%, 98.78%, 98.01%, 98.93%, 98.25%, 97.03%, and 99.77% across metrics including overall precision, per-class precision, overall recall, per-class recall, overall F1 measure, and per-class F1 measure. The results demonstrated its effectiveness and feasibility in diagnosing complex PCBs with multiple failures, indicating the algorithm’s potential to improve failure diagnosis performance and offer a promising PCB diagnosis solution in aerospace applications.

Modeling complex network perturbations on resilience of the bilateral regional trade agreements

The resilience of cooperative relationships within a trade agreement network, when subjected to external shocks or internal disturbances, underscores the role of network structure in the robustness and adaptability of the trade agreement system. Addressing the gap in understanding the resilience of trade agreement network dynamics, this study constructs a complex network based on the bilateral regional trade agreements. By applying reciprocal dynamics to measure cooperative relationships among countries in the network, we model the impact of complex network perturbations on the resilience of bilateral regional trade agreements. Various complex network perturbations are considered, including node removal, link removal, and three orders of null models for network reshuffling, which correspond to the failure of a trade agreement, simultaneous agreement failure, and signing. Experimental findings reveal that network resilience gradually diminishes with the random removal of nodes and links. However, when nodes are removed based on their degree, removing nodes with larger degrees first proves to be more effective than the reverse. Specifically, network resilience decreases more rapidly when smaller nodes are removed. This highlights the significant contribution of countries with numerous trade agreements to the overall network resilience. In network reshuffling experiments, an increase in the order of reshuffling correlates with a gradual decrease in network resilience, ultimately converging toward real values. These findings emphasize the importance of network structure in maintaining the stability and adaptability of trade agreement systems.

Limiting Behavior of Mixed Coherent Systems With Lévy‐Frailty Marshall–Olkin Failure Times

ABSTRACTIn this article, we show a limit result for the reliability function of a system—that is, the probability that the whole system is still operational after a certain given time—when the number of components of the system grows to infinity. More specifically, we consider a sequence of mixed coherent systems whose components are homogeneous and non‐repairable, with failure‐times governed by a Lévy‐Frailty Marshall–Olkin (LFMO) distribution—a distribution that allows simultaneous component failures. We show that under integrability conditions the reliability function converges to the probability of a first‐passage time of a Lévy subordinator process. To the best of our knowledge, this is the first result to tackle the asymptotic behavior of the reliability function as the number of components of the system grows. To illustrate our approach, we give an example of a parametric family of reliability functions where the system failure time converges in distribution to an exponential random variable, and give computational experiments testing convergence.

Performance assessment of new reliability index of energy in water distribution networks equipped with PATs based on component simultaneous failure scenarios

For a water distribution network (WDN) equipped with pump as turbines (PATs), when a pipe failure scenario occurs, the network performance in renewable energy supply is very important by issues in pressure supply, leakage control, and quality of water. Due to the importance for both water and energy approaches in WDNs equipped with PAT, a reliability of networks performance under pipe failure is evaluated by a novel reliability index with the nature of energy called ERI for the two cases studies as 25-node network (case 1) and the network connected to reservoir No. 23 in Tehran (case 2) in this study. To increase the accuracy and to make the more realistic results for examining higher-order simultaneous failure scenarios given from one to three pipes, the multidimensional performance is considered by energy, water equity, water adequacy and their combinations in ERI. The ERI provided a correlation of the energy assessment for studied networks as 0.99 for case 1 and 0.98 for case 2. The results of the energy performance analysis in case 1 introduced that pipes number 2 and 36 are the most critical pipes, similarly by performance for Case 2, pipes number 2, 4, 31, and 55 are the most critical pipes for repair and maintenance. The loss energy due to worst failure scenario showed that the simultaneous failure of pipes 2-12-21 in case 1 and pipes 2-4 in case 2 can be provided a completely loss energy produced by PATs.

Research on Design and Staged Deployment of LEO Navigation Constellation for MEO Navigation Satellite Failure

Low Earth orbit (LEO) satellites have unique advantages in navigation because of their high signal intensity and rapid geometric changes in a short period. In order to solve the problem of constellation performance degradation after a potential failure pertaining one or more medium Earth orbit (MEO) navigation satellites, this paper designs the LEO navigation constellation and considers the task requirements of different stages of constellation deployment. Firstly, the LEO navigation constellation is designed by a non-dominated sorting genetic algorithm II (NSGA-II). The average position dilution of precision (PDOP) is 1.676, which is an improvement compared to the average PDOP offered by the four traditional GNSS. Secondly, the staged deployment of constellation takes into account the degradation of constellation performance caused by the failure of MEO navigation satellites, and the Monte Carlo method is used to analyze the case of three simultaneous satellite failures. The results show that a single satellite failure within each orbital plane and adjacent satellites with close phase separation has a great impact on the performance of the MEO navigation constellation. On this basis, a staged deployment strategy was adopted in order to balance cost, risk, and performance. The three phases deploy 66, 156, and 288 satellites, respectively; as a make-up constellation under contingencies, a navigation enhancement constellation, and an independent navigation constellation, the deployment of the staged sub-constellations meets the mission requirements. The constellation design and staged deployment method proposed in this paper can provide reference for the future study of LEO navigation constellations.

Cushing syndrome in paediatric population: who and how to screen.

Cushing's syndrome (CS) is characterised by signs and symptoms resulting from excessive and prolonged exposure to exogenous glucocorticoids or endogenous hypercortisolism. In childhood, exogenous CS represents the main cause of CS due to the widespread therapeutic use of glucocorticoids, while endogenous CS is very rare and accounts for about 10% of CS cases. According to the origin of the hypercortisolism, the ACTH-dependent form due to pituitary ACTH-secreting tumours is the most common form of endogenous CS in paediatric age (about 75-80% of cases), following by adrenal causes (about 15-20% of cases) including adenoma, carcinoma (which has a peak of incidence in the first decade), bilateral adrenal hyperplasia or Carney complex, with a different distribution by age. Ectopic ACTH-secreting CS, genetic forms of pituitary adenomas are more uncommon. The insidious onset of hypercortisolism and the absence of salient early signs make the diagnosis of endogenous CS difficult. Facial changes, weight gain with simultaneous growth failure, prepubertal virilisation, or hypogonadism in adolescence represent some of the key features of CS. The diagnostic workup is essentially aimed at confirming hypercortisolism through screening tests whose diagnostic accuracy is not 100% and therefore the combination of more than two tests is mandatory to confirm the diagnosis of CS.

Integrating Null Controllability and Model-Based Safety Assessment for Enhanced Reliability in Drone Design

The increasing use of drones for safety-critical applications, particularly beyond visual lines of sight and over densely populated areas, necessitates safer and more reliable designs. To address this need, this paper introduces a novel methodology integrating Null Controllability with the Model-Based Safety Assessment (MBSA) framework AltaRica 3.0 to optimize propulsor configurations and system architectures. The main advancement of this method lies in the automation of reliability modeling and the integration of controllability assessment, eliminating restrictions on the types of propulsor configurations and system architectures that can be evaluated and significantly reducing the effort required for each design iteration. Through a hexarotor drone case study, the proposed method enabled a high number of design iterations, efficiently exploring various aspects of the design problem simultaneously, such as configuration, system architecture, and controllability hypothesis, which is not possible with state-of-the-art techniques. This approach demonstrated significant reliability improvements by implementing and optimizing redundancies, reducing the probability of loss of control by up to 99%. The case study also highlighted the increasing difficulty of enhancing reliability with each iteration and confirmed that it is unnecessary to consider more than two simultaneous failures for design optimization. A comparison of reliability figures with previous studies highlights the crucial role of system architecture in effectively enhancing drone design reliability. This work advances the field by providing an effective multidisciplinary modeling framework for drone design, enhancing reliability in safety-critical applications.

Analysis of the hydrogen safety of the NPP with a VVER-1200/V-491 reactor in a severe beyond design based accident

The results of a computational analysis of possible modes of combustion of a hydrogen-air mixture in containment during the evolution of a severe beyond design basis accident (BDBA) with the COCOSYS code are presented. The containment of the NPP with a VVER-1200/V-491 reactor was selected as the object of study. BDBA with loss of coolant occurs due to a break of the injection pipeline of the pressurizer system (LOCA DN179) and the simultaneous failure of all active channels of the emergency core cooling system (ECCS). The calculated parameters of the thermodynamic state (pressure and temperature) of the gas mixture are given, and the values of the concentration distribution of hydrogen inside the containment are presented. After calculating the hydrogen distribution and mixing in all compartments of the containment, an evaluation was made of the flammability of the mixture and the potential for self-ignition in the containment by using a three-component Shapiro-Moffette diagram. It was concluded that in BDBA (LOCA DN179 with failure of active ECCS) detonation of the hydrogen-containing mixture is excluded, and deflagration is possible only in the emergency compartment of steam generators with a pipeline break. Thus, the hydrogen risk mitigation has been achieved in accordance with the standards established by the Belarusian regulator, provided that the localization safety systems are operational in the event of hydrogen deflagration. And the efficiency of the hydrogen removal system from the containment using catalytic recombination is considered sufficient for the considered BDBA.

Development of Yield Forecast Model in Bread Wheat Using Regression Analysis

Background: Studies highlighted the possibilities of simultaneous crop failures in the world’s “breadbaskets” (wheat) due to heat and 40% of the variability in inter-annual wheat production is already related to temperature extremes. The global yield numbers hide the degree of variability of wheat production, yet several environmental conditions pose a threat to wheat production. Objective: The main objective of the study was to develop a regression model that fitted the dependent variable sufficiently well to account for the total variability. Method: For this, sixty advance lines along with four standard checks were evaluated for fifteen yield-associated traits and eight quality traits during Rabi 2020-21 at the research area of Wheat and Barley section, Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar. Multiple regression analysis revealed that 98.5% of the variability is explained by the studied morphological and quality traits. Result: The stepwise regression analysis retained a total of seven traits (six morphological and one quality) viz. biological yield per plot, harvest index, grain weight per spike, flag leaf length, main spike weight, number of spikelets per spike and grain appearance score; explaining 97.8 % of the total variability. Conclusion: The seventh model among all, indicated good yield predicting performance without modifying the traits.

Startup and Multiphysics Analysis of a Compact kW-Class Thermal Spectrum Microreactor

Self-regulating compact nuclear microreactor concepts are being developed for use in space and at terrestrial remote sites. The current emphasis is on the development of high-assay low-enriched uranium–fueled reactors that rely on metal hydrides to achieve size, specific weight, and power parity with the legacy highly enriched uranium systems. In the case of terrestrial applications, metal hydride–moderated systems can also improve economic feasibility. The neutronic design of metal hydride–moderated high-temperature reactor cores is complicated by the need to optimize and synchronize delayed spatial and temporal reactivity feedback from outer reflectors. Zebra is a thermal spectrum proof-of-principle core designed for demonstrating the reactor dynamics of hydride-moderated spectrum reactors, which is studied in this work. The reactor, including the fuel, yttrium hydride moderator, heat pipes, central control rod, structural supports, and the beryllium reflector, weighs ~425 kg. The design shares several features common with nuclear criticality test geometries routinely used in National Criticality Experiments Research Center (NCERC) experiments such that a prototype of the reactor can be readily assembled and tested. Additional features, such as heat pipes and hydrogen barrier clads, were added to minimize the potential for large thermal gradients that in turn could induce hydrogen loss or structural deformation during extended periods of operation at ~1000 K. In this work, normal and off-normal state performance of the Zebra rector core was analyzed using MCNP and Abaqus-based Reactor Multiphysics (MARM) software. Up-to-date nuclear, thermal, and mechanical performance data were used to characterize the performance of the yttrium hydride moderator. Steady-state analyses established that at a postulated power between 20 and 50 kW(thermal), the reactor core is nearly isothermal irrespective of quality of conduction coupling between heat pipes and fuel plates. Additionally, heat pipe failure modes, including simultaneous failure of all heat pipes in a quadrant of a reactor, were examined to bound the maximum credible temperature spike in the reactor core for extreme off-normal operating conditions. Finally, we detail the startup design challenges for the hydride-moderated thermal core, and analyze load-following cases to achieve “self-regulation” using the Dynamic Analysis of Reactor Transients module of MARM. The reactor is self-regulating with a reactivity temperature coefficient of ~−1 pcm/K at the operating point based solely on nuclear cross-section feedback. It can be further strengthened using additional spectral shift neutron absorbers and incorporating design features that enhance core expansion. This work captures that hydride-moderated systems are feasible for various self-regulating applications once systematic checks are verified in order to achieve a well-engineered core design.

Algorithms for online fault tolerance server consolidation

We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures. In this mechanism, each item represents a computing task and is replicated into ξ+1 servers for some integer ξ≥1, with workloads specified by the amount of required resources. If one or more servers fail, the affected workloads can be redirected to other servers that host replicas associated with the same item, such that the service is not interrupted by the failure of up to ξ servers. This requires that any feasible assignment algorithm must reserve some capacity in each server to accommodate the workload redirected from potential failed servers without overloading, and determining the optimal method for reserving capacity becomes a key issue. Unlike existing algorithms that assume that no two servers share replicas of more than one item, we first formulate capacity reservation for a general arbitrary scenario. Due to the combinatorial nature of this problem, finding the optimal solution is difficult. To this end, we propose a Generalized and Simple Calculating Reserved Capacity (GSCRC) algorithm, with a time complexity only related to the number of items packed in the server. In conjunction with GSCRC, we propose a robust replica packing algorithm with capacity optimization (RobustPack), which aims to minimize the number of servers hosting replicas and tolerate multiple server failures. Through theoretical analysis and experimental evaluations, we show that the RobustPack algorithm can achieve better performance.

Study on the Anti-Progressive Collapse Behavior of Steel Frame Structures under Close-Range Blast Loading

The steel frame structure plays an important role in strategic deployments and is widely used in heavy machinery, metallurgy, military, and other important industries. To study the impact of explosive loads on the anti-progressive collapse performance of steel structures, this paper proposes to establish the vulnerability characteristics of steel frame structures and provides a method for calculating vulnerability characterization indicators. A finite element model is used to analyze the dynamic response of steel frame structures under the action of close-range explosive loads, and factors influencing the anti-progressive collapse of steel frame structures are proposed, including the number of stories and diagonal bracing. A comparison is made between the various column types of steel structures under explosive loads, such as corner columns, long-edge middle columns, short-edge middle columns, inner columns, also in various coupling conditions. The results show that the progressive collapse of steel frame structures is greatly influenced by the position of the explosion and less affected by the amount of explosive material. The simultaneous failure of corner columns and long-edge middle columns is more likely to cause overall structural failure. The addition of diagonal bracing significantly improves the anti-progressive collapse ability and prevents the lateral displacement of steel frame structures; increasing the number of stories provides more alternative load transfer paths for steel frame structures, thereby preventing their collapse.

How are microstructural defect interactions linked to simultaneous intergranular and transgranular fracture modes in polycrystalline systems?

The major objective of this investigation is to fundamentally understand and predict how intergranular (IG) and transgranular (TG) fracture modes nucleate and propagate in f.c.c. polycrystalline systems due to defects, such as total and partial dislocation densities and grain boundary (GB) structures and misorientations. A dislocation density crystalline plasticity (DCP) formulation based on the evolution and interaction of total and partial dislocation densities was integrated with a recently developed fracture approach to investigate the fracture nucleation and propagation of simultaneous multiple fracture events, including both IG and TG fracture events. The aggregate grains and GB orientations and morphologies are based on EBSD measurements that are representative of polycrystalline copper aggregates with a broad range of random high angle and low angle GBs. The predictions indicate that dislocation density pileups induce IG fracture due to interrelated stress, slip, and total and partial dislocation density accumulations and interactions for both high angle GBs (HAGBs) and low angle GBs (LAGBs). TG fracture nucleation and propagation occurred due to normal stress accumulations, which exceeds the fracture stress, along cleavage planes. Furthermore, it is shown how IG cracks transition from the GB plane to the cleavage planes as cracks nucleate and propagate. Accumulated plastic zones due to different slip system activities can impede and blunt crack propagation and fronts. These plastic zones form due to high Lomer and Shockley partial dislocation densities. These predictions, which are consistent with experimental observations, provide a fundamental understanding of how simultaneous failure modes initiate and propagate for physically representative microstructures.

Lethal combination for seedlings: extreme heat drives mortality of drought-exposed high-elevation pine seedlings.

Hotter drought- and biotically-driven tree mortality are expected to increase with climate change in much of the western United States, and species persistence will depend upon ongoing establishment under novel conditions or migration to track ecological niche requirements. High-elevation tree species may be particularly vulnerable to increasing water stress as snowpack declines, increasing the potential for adult mortality and simultaneous regeneration failures. Seedling survival will be determined by ecophysiological limitations in response to changing water availability and temperature. We exposed seedlings from populations of Pinus longaeva, Pinus flexilis, and Pinus albicaulis to severe drought and concurrent temperature stress in common gardens testing timing of drought onset under two different temperature regimes. We monitored seedling functional traits, physiological function, and survival. The combined stressors of water limitation and extreme heat led to conservative water use strategies and declines in physiological function, with these joint stressors ultimately exceeding species' tolerances and leading to complete episodic mortality across all species. Growing conditions were the primary determinant of seedling trait expression, with seedlings exhibiting more drought-resistant traits such as lower specific leaf area in the hottest, driest treatment conditions. Water stress-induced stomatal closure was also widely apparent. Under adequate soil moisture, seedlings endured prolonged exposure to high air and surface temperatures, suggesting broad margins for survival. The critical interaction between soil moisture and temperature suggests that rising temperatures will exacerbate growing season moisture stress. Our results highlight the importance of local conditions over population- and species-level influences in shaping strategies for stress tolerance and resistance to desiccation at this early life stage. By quantifying some of the physiological consequences of drought and heat that lead to seedling mortality, we can better understand the future effects of global change on the composition and distribution of high-elevation conifer forests.

Network design with vulnerability constraints and probabilistic edge reliability

AbstractThe network design problem with vulnerability constraints and probabilistic edge reliability (NDPVC‐PER) is an extension of the NDPVC obtained by additionally considering edge reliability. We consider the design of a telecommunication network in which every origin‐destination pair is connected by a hop‐constrained primal path, and by a hop‐constrained backup path when certain edges in the network fail. The edge failures occur with respect to their reliability, and the network is designed by considering a minimum reliability level. Therefore, a hop‐constrained backup path must be built by considering all simultaneous edge failures that have a certain probability of realization. While there exist models to solve the NDPVC without enumerating all edge subsets, edge reliability cannot be dealt with by applying the techniques applied to the NDPVC. Therefore, we develop models based on a new concept of resilient length‐bounded cuts, and solve the NDPVC‐PER without edge set enumerations. We perform extensive testing of the model to determine the best performing settings, and demonstrate the computational efficiency of the developed model. Our findings on these instances show that, in the dataset considered in this study, increasing the reliability level from 90% to 95% increases the average cost only by 12.4%, while increasing it from 95% to 99% level yields a cost increase of 93.9%.

Multi-label deep transfer learning method for coupling fault diagnosis

With the development of complexity and integration of machines, the multiple components of the system are prone to simultaneous failures and the multi-fault signals may be measured in limited sensors. This fault mode is defined as coupling fault in this paper and becomes more common and attracts great attention. Current coupling fault diagnosis approaches rely on labeled data under consistent working conditions. However, in practical varying working conditions, the data is difficult to label and the traditional methods perform poorly. To address the challenge problem, we utilize some related annotated data under other working conditions for auxiliary learning and abstract this problem as a multi-label transfer learning problem which is a new research topic in fault diagnosis. We proposed a novel deep transfer coupling fault diagnosis method from the global and local views to achieve the effect of transfer, which is the first attempt to address this practical problem as far as we know. At the global level, we used Maximum Mean Discrepancy (MMD) at multiple stages of the network to reduce the hypothesis space of the model. Furthermore, we design a special manifold framework with multi-level similarity to constrain the hierarchy of the distance of the sample and the hierarchy of the labels being consistent between the two domains, to further improve the effect of local alignment. The proposed method has high accuracy in multiple transfer tasks for both public and laboratory datasets, powerfully demonstrating its effectiveness.

Investigating Behavior of Slider–Crank Mechanisms with Bearing Failures Using Vibration Analysis Techniques

This study focuses on investigating the behavior of slider–crank mechanisms with different bearing failures using a vibration analysis technique. The reliability and lifespan of bearings are crucial for such mechanisms, which convert rotary motion to reciprocating motion. Previous research primarily addressed ball-bearing failures, neglecting needle bearings due to their specific applications. To bridge this gap, our experimental setup integrated both roller and ball bearings within a slider–crank mechanism. Vibration data were collected during normal operation, as well as under failure conditions of the ball and roller bearings. By analyzing the vibration signatures during simultaneous multiple failures, we gained insights into the nature of vibrations in the system. Furthermore, a mathematical model based on Hertzian contact was employed to calculate the theoretical frequency of ball bearings; however, due to the variable motion of the needle bearing, a novel mathematical model was proposed to estimate the defective impulse frequency, considering the inter-impact time between two impacts. The experimental results were compared with the healthy crank mechanism setup to draw meaningful conclusions. This research contributes to a comprehensive understanding of bearing failures in slider–crank mechanisms and provides valuable insights for designing reliable and long-lasting systems.

Application of FMEA and FTA techniques for assessing the occurrence of LOCA in a TRIGA MARK I Reactor

This study presents a framework merging failure mode and effect analysis (FMEA) and fault tree analysis (FTA) techniques to evaluate loss of coolant accident (LOCA) in the Brazilian Reactor TRIGA IPR-RI. At first, FMEA identified failure modes and prioritized risk management based on the risk priority number (RPN). Subsequently, FTA established logical relationships between these failure modes, revealing minimal cut sets. Results indicated that the path involving “loss of coolant from reactor tank” correlate to an externally caused leak, exhibiting a low probability and, consequently, a low RPN. On the other hand, the path involving “loss of coolant through primary circuit rupture without a pump shutdown” highlighted high RPN due to the lack of shutdown signals from the monitoring indicators. Finally, FTA unveiled that LOCA associates with a primary circuit rupture and the simultaneous failure of safety mechanisms, including ultimately human error.