Comprehensive Failure Research Articles

Comparison of Inference Comprehension and Error Types in Preschool Children with and without Specific Language Impairment through Eye-Tracking

Objectives: The purpose of the study is to examine inference comprehension and the types of inference errors in preschool children with specific language impairment (SLI) and typically developing (TD) children using eye-tracking technology. Methods: A total of 22 children (12 TD, 10 SLI), aged 4 to 6 years, participated. Eye-tracking data were collected while they viewed a story, followed by completion of an inferential comprehension task. One-way ANOVA compared task performance and fixation variables, with correlation analysis examining the relationships between them. Inference error responses were categorized into 5 types, and the frequency of errors for each type was compared between groups. Results: Between groups, significant differences were found in performance on inferential comprehension tasks and the frequency of comprehension failures in inference error types. Average fixation time during storytelling situations, fixation count during inference situations, and fixation time also showed significant differences. A negative correlation was observed between inferential comprehension ability and fixation count, as well as between inferential comprehension ability and fixation time. Conclusion: The process of inference involves complex cognitive processing, requiring examination of error responses for successful inference and a step-by-step approach. Higher attention levels are necessary for information processing, and depending on the situation, visual or auditory cues can aid in information integration.

Visualization of integrated failure consequences of hazardous chemical leakage and explosion

Dangerous chemicals are widely present in various aspects of people's lives, but they often pose risks of leakage and explosion during transportation and storage, resulting in severe casualties and property damage. Firstly, this paper proposes a visualization method applicable to comprehensive failure consequences of hazardous chemical storage tanks. This method considers the toxic hazard range of chemical leaks and the blast overpressure injury range of leak clouds and visualizes the comprehensive failure consequences. Secondly, FLACS is employed to simulate a major leakage and explosion accident at Jinyu Petrochemical Co., Ltd. in Linyi City. The simulation reproduces the leakage and explosion processes and verifies the reliability of the simulation results. Finally, the proposed method is used to visualize the comprehensive failure consequences of this accident, providing comprehensive visual results. The method presented in this paper can serve as a theoretical reference for predicting the development of accidents and clarifying their consequences.

Sulfide stress corrosion cracking in L360QS pipelines: A comprehensive failure analysis and implications for natural gas transportation safety

This research investigates the severe weld failures in L360QS pipelines, which are integral to the infrastructure of high-pressure natural gas transportation systems. Even with strict compliance to engineering standards, two pivotal welds experienced sulfide stress corrosion cracking (SSCC) due to continuous exposure to hydrogen sulfide and stresses from construction activities. A comprehensive material analysis and stress simulation has been utilized, revealing a maximum stress concentration of 544.9 MPa that surpasses the yield strength of the pipeline material. This discovery prompts a reevaluation of current safety margins and underscores the urgent need for enhanced pipeline integrity management. Our findings, corroborated by stress distribution simulations, not only illuminate the complex interplay of material properties and environmental factors in SSCC but also provide a new perspective for the safe service of pipeline.

A Comprehensive Failure Analysis Approach Utilizing High-Resolution Targeted Patterns (HRTP) for ATPG Diagnosis Resolution Improvement, Test Coverage Resolution, and Further Fault Localization

A Comprehensive Failure Analysis Approach Utilizing High-Resolution Targeted Patterns (HRTP) for ATPG Diagnosis Resolution Improvement, Test Coverage Resolution, and Further Fault Localization

Physical Simulations of the Tool Degradation in Friction Stir Welding

Abstract The present investigation is part of a comprehensive failure study of friction stir welding (FSW) tools, where experimental non-destructive and destructive evaluations are combined with analytical- and physical- simulations of tool wear mechanisms. This paper focuses on the research methodology and the primary results of Gleeble simulations of thermal- and mechanical-cycle effects on an H13 steel material widely used for FSW tools for welding aluminum and magnesium alloys.

RISK ANALYSIS IN SANDWICH PANEL PRODUCTION WITH THE INTEGRATION OF FMEA AND FTA METHODS

General Background: Ensuring consistent product quality is crucial for maintaining competitive advantage, especially in manufacturing. PT. Starr Panel Industry, a company in the refrigeration sector, focuses on high-quality sandwich panels but experiences frequent defects in its production processes. Specific Background: Despite prioritizing premium raw materials, the company faces recurring product failures, particularly in the finishing phase, which affect production flow and on-time delivery. Knowledge Gap: Current quality assurance measures at PT. Starr Panel Industry lack a systematic approach to identifying and prioritizing the root causes of defects, hindering the development of targeted improvement strategies. Aims: This study aims to identify, analyze, and address potential failure modes and their root causes within the production processes, employing Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA). Results: The findings reveal that the finishing process has the highest Risk Priority Number (RPN) of 112, primarily due to insufficient adherence to standard operating procedures (SOPs) by the workforce. Novelty: The integration of FMEA and FTA provides a comprehensive failure analysis model, with FMEA ranking failure risks and FTA tracing them to foundational causes, offering a new dual-method approach to improve operational standards effectively. Implications: Implementing the proposed FMEA-FTA framework can significantly reduce product defects, improve quality consistency, and minimize delivery disruptions, especially in the critical finishing stage. Emphasizing SOP compliance across divisions, particularly in finishing, can lead to sustained quality improvements and enhanced operational efficiency in sandwich panel production.

An EGF technique to infer the source parameters of a circular crack growing at a variable rupture velocity

Circular crack models with a constant rupture velocity struggle to effectively model both the amplitude and duration of first P-wave pulses generated by small magnitude seismic events. Assuming a constant rupture velocity is unphysical, necessitating a deceleration phase in the rupture velocity to uphold the causality of the healing process. Moreover, a comprehensive failure model might encompass an initial nucleation phase, typically characterized by an increase of the initial rupture velocity. Studies have demonstrated that quasi-dynamic circular crack models featuring variable rupture velocities can accurately model the shape of the observed first P-wave pulse. Based on these principles, an Empirical Green’s function (EGF) approach was previously formulated to estimate the source parameters of small magnitude earthquakes, called MAIN. In addition to determine the source radius and stress drop, this method also enables the inference of the temporal evolution of rupture velocity. However, this method encounters difficulties when the noise-to-signal ratio in the recordings of smaller earthquakes used as EGF exceeds 5%, a common situation when employing regional-scale recordings of small-magnitude earthquakes as EGF. Through synthetic tests, we demonstrated that, in such instances, the problem of this technique is that the alignment between the onset of P waves of EGF and MAIN is not rightly recovered after the initial inversion step. Consequently, a novel inversion method has been developed to address this issue, enabling the identification of the optimal alignment of P-wave arrivals in EGF and MAIN across all stations. A Bayesian statistical approach is proposed to meticulously investigate the solutions of model parameters and their correlations. Using the new technique on a small magnitude earthquake (ML = 3.3) occurred in Central Italy enabled us to identify the most likely rupture models and examine the issue of correlation among model parameters. Application of Occam’s Razor Principle suggests that, for the investigated event, a circular crack model should be favored over a heterogeneous rupture model.

Reading Comprehension and Comprehension Monitoring in First-grade Children with Vocabulary Delay

Objectives: This study investigated reading comprehension and reading comprehension monitoring abilities of children with vocabulary delay at the end of the first grade. Specifically, the study examined whether children with vocabulary delays could detect internal inconsistency errors, which are contradictory pieces of information in a short story, and whether they could correct those errors to make appropriate changes to the story at the beginning stage of reading. Methods: Fourteen children with vocabulary delay and 15 typically developing children participated in this study. Each child read 10 short stories without internal inconsistency errors and 10 stories with internal inconsistency errors. After reading the text, children were asked to find any inconsistent parts of the story and correct them. Results: The results showed that children with vocabulary delay performed worse on reading comprehension than their peers. They also scored statistically lower on both the error detection and error correction tasks in stories with internal inconsistency errors compared to typically developing children. For typically developing children only, there were significant correlations between reading comprehension and reading comprehension monitoring. Conclusion: Children with vocabulary delay exhibited difficulties in both reading comprehension and comprehension monitoring. Poor vocabulary knowledge can hinder their ability to recognize when a text is misunderstood or to apply effective strategies for resolving problems, ultimately leading to reading comprehension failure. This suggests that children with language disorders, including those with vocabulary delays, need to be assessed and provided with interventions for both reading comprehension and comprehension monitoring.

Erosion and intergranular corrosion induced failure of S31254 stainless steel – Case study on Venturi scrubber in a natural gas purification plant

The flue gases such as SO2, SO3, and CO2 generated during the purification process of sulfur-containing natural gas need to be treated to a certain concentration before they can be discharged into the atmosphere. The flue gas unit of a purification plant in Sichuan adopts the new Cansolv flue gas treatment process. After running for a period of time, the Venturi scrubber experienced severe corrosion failure, resulting in equipment shutdown and significant economic losses. This paper utilizes an actual failed device as a case study to analyze the corrosion environment of the Venturi scrubber. It conducts a comprehensive failure analysis, encompassing material mechanical properties, metallographic analysis, and failure microstructure analysis, aiming to elucidate the reasons behind the Venturi scrubber failure. Systematic analysis shows that the manufacturing materials used in this scrubber meet all design requirements. However, flue gas at temperatures reaching 280 °C enters the scrubber tower at a flow rate exceeding 10 m/s. The dissolution of acidic gases leads to a significant drop in the pH of the cooling water to 1, manifesting evident signs of erosion corrosion and intergranular corrosion on the material surface. These observations suggest that erosion and intergranular corrosion in high-temperature acidic environments are the predominant factors contributing to the corrosion failure of the Venturi scrubber.

Failure analysis of stress corrosion cracking in welded structures of aluminum alloy metro body traction beam in service

A comprehensive failure analysis was carried out for a crack appearing in the welded structure of an aluminum alloy body traction beam in a service metro vehicle. The fracture composition analysis reveals the products remaining after the reaction between the external corrosive medium and the material. A three-dimensional finite element model of the welded area of the traction beam was further established to simulate the high residual tensile stress present in the welded area. Based on the dynamic stress testing, it was found that the external loads had little effect on their crack growth. A series of analyses based on material properties, microstructure, fracture morphology and residual stresses identified stress corrosion as the leading cause of crack growth failure. Finally, a new structural repair program is proposed, and the reliability of the new structure in service life is verified by comparison, avoiding catastrophic fracture accidents in the service structure.

Designing the geometry of compact tension specimens for easy fracture toughness measurement using reinforcement learning

Abstract For composite laminates, a rising R-curve is observed for their fracture toughness under Mode I stress, which is important for a comprehensive failure analysis of the materials. Since it is laborious to measure the R-curve due to its dependence on both the load and the crack extension, we put forward a novel compact tension specimen by modifying its geometry to eliminate the relation between fracture toughness and crack extension, so as to simplify the experimental process of the R-curve measurement by only recording the load history. Two machine learning models were developed for the optimum sample design based on the finite element analysis of the effect of sample geometries on the R-curve. A simple neural network model was built for designing tapered specimen and a reinforcement learning model was created for further finding the best design from a broader design space. The results showed that, in contrast to the specimens with a tapered shape, which only ensure the independence between the R-curve and crack extension in the case of a small extension, the design provided by the reinforcement learning provides such independence across a wider range of crack length and an improved accuracy.

Experimental study on the punching failure model of soft red rock subgrade by BPT-BVM methods and it’s assessment of the load bearing capacity

The recommended bearing capacity of medium weathering mudstone foundation is less than the capacity of the rock structure to withstand loads in Southwest China. A comprehensive failure characterization of medium weathering mudstone in Chengdu has been performed including bearing plate test (BPT), binocular vision measurement (BVM) test, uniaxial compressive strength test, trial trench test of shallow rock surface and 3D imaging in this paper. Failure behavior of rock has been modeled with 3D imaging algorithm that utilizes Zhang’s calibration method in BVM system combination with trial trench test of shallow rock surface. The bearing capacity of medium weathering mudstone foundation were extracted from uniaxial experiments and BPT-BVM test by fitting relevant material properties to the data. The results revealed that: Bearing capacity of medium weathering mudstone of layered isotropic in Chengdu is undervalued. Specifically, the characteristic load carrying value is in the range 1500–2500 kP, that is 50% higher than in the local standard system. Failure process is different from Hoek–Brown Failure Criterion, presenting a wave peak transfer phenomenon of the increment displacement into the distance. Thus, it can be reduced to that of punching failures for thin bedded structures of Moudstone foundations. Compressive strength of soft rock proves to be main factor limiting the bearing capacity, a clear correlation between the uniaxial compressive strength reduction coefficient and the bearing capacity has been used to establish, leading to the proposal of a load bearing capacity prediction model.

Evaluation of the Reliability of a Standby Redundancy System Under Real Conditions

This paper presents a novel analysis of a standby redundancy system under real conditions. The study considers the presence of a real commutator and failure detector in the system. Through a comprehensive failure mode analysis, mathematical relationships between different module characteristics are established. The results of investigation provide valuable insights for manufacturers, allowing them to evaluate the Mean Time To Failure (MTTF) of the system during the design phase and make informed decisions regarding the selection of failure rates for the detector and commutator. Overall, this work contributes to the effective operation of standby redundancy systems in practical applications.

Identification of key potential risk areas and key potential failure modes in hemodialysis rooms by the FMEA method following routine prevention and control of the COVID-19 pandemic.

Hemodialysis is an important part of nosocomial infection prevention and control (IPC). This study aimed to identify the key potential risk areas and failure modes in hemodialysis rooms in hospitals and put forward a series of improvement measures to prevent and control the spread of the coronavirus disease 2019 (COVID-19). Hemodialysis patients are highly susceptible to COVID-19 and usually have a high incidence of severe illness and mortality after infection with COVID-19. Therefore, IPC in hemodialysis patients is of crucial strategic significance. Based on 30 domain experts' interviews and careful analysis of prevention and control documents, we constructed a comprehensive failure system for a model that identifies the potential risks for nosocomial COVID-19 infection in the hemodialysis room. Subsequently, a thorough risk assessment of the potential failure factors identified in our model was conducted. The failure key factors corresponding to the human element in medical waste (garbage) disposal (C2) are verified to be the highest risk factors. They are as follows: The cleaning staff did not dispose of different types of medical waste (garbage) (C21), did not wear masks according to the regulations (C22), and lacked knowledge and norms of nosocomial IPC (C23). This study provides valuable insights for hospital decision-makers on the potential failure factors related to COVID-19 infections in hemodialysis rooms. By working with hospital infection specialists, the suggested improvement measures can help reduce the risk of virus exposure among hospital medical staff, patients, and cleaning staff.

The formation mechanism of low-angle loess-mudstone seismic landslides

Seismic-induced landslides represent intricate geological phenomena requiring a multidisciplinary investigative approach. This study examines the formation mechanisms of low-angle loess-mudstone landslides triggered by the 1920 Haiyuan M8.5 earthquake. We employ a synthesis of field investigations, high-density electrical resistivity tests, drilling, laboratory experiments, and numerical simulations. High-density resistivity results support the identified zone at the loess-mudstone interface, indicating a saturated area prone to liquefaction. Dynamic triaxial tests further verify liquefaction occurrences during seismic events within this zone. Additionally, numerical simulations conducted with FLAC2D and the PM4Silt constitutive model provide valuable insights into the temporal and spatial progression of landslides. The liquefaction zone experiences severe shear strain, precisely aligning with the location of the sliding band. Shear strain time-history analyses elucidate early manifestations and time-dependent behaviors at interfaces, providing a nuanced understanding of deformation patterns. The study delineates a comprehensive failure mechanism, unraveling how liquefaction in the saturated loess layer initiates in the upper and toe regions, subsequently propagating throughout the slope. Tension in the upper part and compressive uplift at the toe manifest, resulting in overall landslide movement. These findings highlight the significance of differential shear strain, leading to a layered shear deformation zone. The results yield invaluable insights for seismic stability assessments in regions with similar geological characteristics. This research not only advances the understanding of earthquake-induced landslides but also demonstrates the synergy between field investigations, advanced geotechnical testing, and numerical modeling in unraveling complex geological processes.

Failure prediction of mechanical system based on meta‐action

AbstractHighly reliable mechanical systems can lead to significant losses in the event of failure, and the lack of comprehensive failure data presents challenges for developing techniques such as critical part identification and failure prediction. In light of this, this paper proposes a meta‐action‐based fault prediction method that effectively addresses the issue of limited fault data. Initially, the mechanical system is decomposed utilizing the “Function‐Motion‐Action” (FMA) methodology to derive individual meta‐action units (MAUs). Subsequently, the limited sample of fault data from the mechanical system is combined with processed expert knowledge to construct the corresponding fault propagation‐directed graph. Furthermore, the key MAUs are determined by applying the Decision–Making Trial and Evaluation Laboratory (DEMATEL) method. Last, the degradation data of the key MAUs is acquired by monitoring them, and a non‐homogeneous discrete grey model (DNGM) integrated with an improved BP neural network is proposed to facilitate the fault prediction of MAUs. Using an industrial robot as a case study, the prediction results demonstrate the superiority of the method proposed in this paper over a single gray model and neural network, thereby providing a reliable prediction approach for anticipating the future trends of data‐deficient mechanical systems.

Comparative analysis of harmonic sensitivity for stator fault diagnosis in induction motors

Induction motors play a vital role in various industrial applications due to their commendable efficiency and reliability. However, their susceptibility to faults, especially in challenging industrial environments, highlights the need for vigilant fault detection to prevent unforeseen downtimes and reduce subsequent repair costs. Early fault diagnosis is crucial in this context. A systematic approach to diagnosing faults in asynchronous motors involves the application of signal processing techniques, particularly utilizing the Fast Fourier Transform (FFT). The FFT, as a mathematical tool, enables a comprehensive analysis of signals, facilitating the identification and isolation of their frequency components. Monitoring the frequency components within a motor's signal provides a means to determine the existence and severity of faults. FFT analysis allows for the monitoring of four distinct categories of harmonics: time harmonics (TH), rotor slot harmonics (RSH), rotor bar fault harmonics (RBFH), and eccentricity fault harmonics (EFH). Each type of harmonic offers valuable insights into specific fault categories. Empirical evidence, drawn from experimental results, emphasizes the heightened sensitivity of rotor slot harmonics (RSH) in detecting stator faults. Continuous monitoring of the RSH frequency component enables the prompt detection and localization of stator faults, along with an assessment of their severity. Additionally, this diagnostic methodology proves effective in identifying micro short-circuits between stator coils, allowing for a proactive strategy in predictive maintenance. This proactive approach enables anticipatory part replacement before degradation progresses to the point of causing comprehensive failure in the production chain. The combination of FFT-based signal processing and harmonic analysis establishes a robust framework for the early detection and localization of faults in asynchronous motors within industrial settings. This contributes to enhanced operational reliability and efficiency, ultimately ensuring smoother industrial processes.

Joint optimization of flexible job shop scheduling and preventive maintenance under high-frequency production switching

To secure a larger market share in the dynamically evolving personalized market demand, enterprises have to adopt a more flexible production mode. In this context, the implementation of parallel production with multiple product types necessitates frequent switching between different products, imposing elevated requirements on machine fault-free operation and stable production. There is a compelling motivation to investigate the joint optimization of the flexible job shop scheduling problem and preventive maintenance (FJSSP-PM). However, existing research has primarily focused on utilizing predetermined maintenance as inputs for optimizing production scheduling, while overlooking the uncertain maintenance requirements of machines during the production process. Therefore, this paper proposes a two-stage joint optimization model to simultaneously address three subproblems: machine assignment, operation sequencing, and maintenance arrangement. Specifically, the first stage involves constructing a mathematical model for the FJSSP to minimize penalties for tardiness and workload balancing. Subsequently, a comprehensive failure rate model is developed to determine maintenance requirements for machines with production-dependent failure behavior, particularly under high-frequency production switching scenarios. Furthermore, a feedback-updated strategy is proposed to achieve synchronous optimization of production and maintenance activities in an economically and operationally efficient manner. Given the complexity of the problem, a hybrid meta-heuristic algorithm is designed to effectively handle large-scale cases. The effectiveness of the proposed model in terms of cost-savings has been verified compared with existing relevant methods.

Failure mode analysis of Austria's first road-integrated photovoltaic system

The exploration of traffic areas as a novel photovoltaic integration opportunity within the traffic sector, specifically in road surfaces, has been demonstrated in various projects. Limited data and publications about the performance and failure modes of these innovative road-integrated modules highlights the need for a comprehensive failure analysis. This study focuses on first time assessing failure modes of road-integrated photovoltaic modules installed at Austria's first road-integrated PV system in Teesdorf. A comprehensive failure mode analysis is conducted at the 100 m2 PV parking place using a combination of quantitative and qualitative methods. These methods include regular visual inspections, I-V-curve measurements at both string- and module-levels (with a simplified STC correction), electroluminescence- and dark-I-V-curve measurements, and the use of monitoring data. The PV parking place produced 10.2 MWh in its first operation year, 27.18% less than the estimated yield. Visual inspections reveal various failure modes, including detachment of the module top layer, delamination, and broken module edges. In the analysed monitoring data continuous power losses are observed over the systems operation time. String-level power losses of up to 47.8% (mean: 33.5%) are calculated for the first year of operation. For the second year of operation the power losses reach a up to of 77.5% (mean: 56.2%). Cell cracks as the main cause of these power losses, attributed to vehicle loads, are identified through electroluminescence images. Out of 16 analysed strings with dark I-V-curve measurements three showed at least one bypass diode malfunctions. The combination of quantitative and qualitative methods identified multiple failure modes and their main causes. As a conclusion, the study highlights the challenges of integrating PV modules into road surfaces, emphasizing the need for standardisation and quality assurance in the field of road-integrated PV applications.

Mechanical properties and failure mechanisms of all-CFRP corrugated sandwich truncated cone

Cone-shaped sandwich structures are extensively employed in various fields due to their excellent bearing efficiency and designability. In this work, the design approach and integrated manufacturing method for the carbon fiber reinforced plastic (CFRP) corrugated sandwich truncated cone (CSTC) are proposed to improve the anti-debonding ability and ensure the reliability of the sandwich cone. First, the theoretical model for the stiffness of the CSTC is derived, in which the conservative prediction and the upper limit considering the fiber orientation of the cone are derived. The multiple failure modes of the CSTC under axial compression are theoretically established. Then, the failure mechanism map of the CSTC is established to forecast the possible failure modes. The typical failure modes of local buckling, face fracture, and core buckling are captured by experiments and finite element analysis (FEA). The theoretical model of the stiffness and failure modes is verified by the experiments and FEA. The effect of the semi-vertex angle and circumferential cell number on the failure modes is revealed. Furthermore, a more comprehensive failure mechanism map is generated by altering the geometric parameters of the CSTC. The failure modes of Euler buckling and global buckling are acquired by the comprehensive failure mechanism map and verified by FEA. Finally, the optimum design of the CSTC structure is performed. The results show that the failure mode of face fracture has the best bearing efficiency. This research provides a solid foundation for designing and applying lightweight CSTCs in constructions, such as the adapter of launch vehicles.