System Failure Research Articles

Here Comes the Hurricane

This two-section article and interview with Jesús Hilario-Reyes, a queer, non-binary, Afro-Caribbean artist, explores their artwork to connect trans new media histories to contemporary trans Chicanx scholarship via recent notions on “glitch” and “stitch.” The introduction connects Hilario-Reyes’s uprootedness to trans thoughts on “the cut” and trans Chicanx scholar Francisco Galarte’s concept of “Brown transfiguration.” In Section One, Hilario-Reyes discusses their new media practices in relation to land, water, displacement, and diasporic disembodiment. The interview in Section One reveals their experiences with migration, as they reflect on their 3D animated work about Puerto Rico's post-Hurricane Maria flooding, and their role as a DJ creating queer Black space. Section Two delves deeper into their 3D art and music as a healing response to displacement, mourning, and “destierro” (being ripped from one's homeland). Hilario-Reyes’s creativity, expressed through 3D animations, performance, and sound, becomes an embodied and world-building practice infused with resistance and queer Black sovereignty. Their perspectives on "glitch, love, and storms" offer adjacent strategies to resistance optics, addressing the visibility/invisibility dynamics inherent in transphobia and white supremacy. Their understanding of climate change's white supremacist root cause affecting Puerto Rico leads to a transformation of the disembodying effects of systemic violence through trans and Black-informed gestures. Through Hilario-Reyes’s 3D animations and video games, the article connects their work to larger trans scholarship, new media, and trans video game histories. Embodying non-binary and Afro-Caribbean thought, Hilario-Reyes re-engages the body, love, humanness, and their multiple possible selves, turning systemic violence's cataclysmic failures into trans and Afro-Caribbean liberation.

Study on Cable Tension Characteristics of Shore-Based Constant Tension Mooring Systems Under the Coupling Effect of Wind, Wave, and Current

Abstract This paper proposes a shore-based constant tension mooring system, which improves the cable tension distribution by adjusting the length of the cable to maintain the constant tension of the cable between the ship and the mooring pile in order to solve the problem of poor safety and reliability of the traditional mooring system in the mooring process. First, based on the three-dimensional potential flow theory, this paper uses the hydrodynamic software AQWA to numerically simulate the dynamic response of the traditional mooring system under the coupling of wind, wave, and current in different sea states. Subsequently, a shore-based constant tension mooring system using the principle of volume-varying hydraulic control was studied. On the basis of a comprehensive analysis of the working principle of the constant tension hydraulic control mooring system, a mathematical model of the main working circuit is established. The system was numerically simulated by relying on matlab/Simulink simulation software. Finally, by comparing with traditional mooring systems, the results show that the maximum cable tension of the shore-based constant tension mooring system is significantly reduced so that the tension is controlled within a fixed range, and the safety factor of the mooring cable is significantly improved, thus reducing the risk of mooring system failure and improving the ship's survivability.

Use of simple lymphatic drainage on truncal lymphoedema for a patient with diabetes and peripheral arterial disease.

Lymphoedema is the gradual, abnormal build-up of lymph fluid in the tissues resulting from a failure of the lymphatic system. The swelling impedes movement and is painful. Compression garments are contraindicated and not tolerated by patients with extensive peripheral arterial disease. In this case study, simple lymphatic drainage was therefore considered a safer treatment option to reduce oedema and to encourage proactive self-management for a patient with bilateral amputations, diabetes and peripheral arterial disease.

Comparative Studies on Load Frequency Control with Different Governors connected to Mini Hydro Power Plant via PSCAD Software

Mini Hydropower Plants (MHPPs) are increasingly popular for rural electrification in developing nations due to their ecologically friendly operation. However, constant load fluctuation in these facilities poses a speed control issue. The mechanical, hydraulic governor, commonly used to face this challenge, cannot provide the best speed control due to its mechanical component system. Thus, an electrohydraulic PID-based governor is proposed to control the frequency and speed of MHPPs in a distribution network. This governor’s suitability for regulating the system's frequency in response to significant load variations within the distribution network is going to be determined in this study. The small hydropower plant and distribution system are modeled using the PSCAD software. A comparison between the mechanical hydraulic governor and the electro-PID governor was conducted by analyzing load fluctuations between 5% and 20%. The electro-PID governor responded faster and more actively to load connections and disconnections than the mechanical hydraulic governor, as the latter reduces large overshoots and undershoots, which can be dangerous and damaging to equipment. The electro-PID governor also helps to maintain a stable frequency within acceptable limits, ensuring smooth operation and minimizing the risk of system failures or disruptions.

Reliability and Mean Time to System Failure of a Parallel System' by Using One or Two Decimal Random Data Points

Focusing on Weibull failure rules, which govern the stopping of components, this work evaluates reliability metrics such as stability and the mean time to system failure (MTSF) of a structure that is parallel. These metrics' behaviour has been seen for one or two decimal random values of component failure rates, operation times, form parameters, and the total quantity of components used in the parallel structure. In order to analyze the variation in the ethics of reliability as well as MTSF, the particular case of the Weibull distribution has also been taken up.

An Open-Circuit Fault Diagnosis Method for LLC Converters

In electrified transportation systems, power system failures can lead to greater disasters. Therefore, the reliability of converters in transportation systems has been a concern. Fault-tolerant techniques are widely applied to ensure that converters can continue to supply loads under fault conditions. Fault diagnosis as a prerequisite for fault tolerance has also become a research hotspot. This paper proposes a fast method for fault diagnosis of high-frequency LLC converters. The proposed fault diagnosis method is based on the observation of the voltage across the resonant capacitor to determine and locate the faulty power switch, providing a basis for fault tolerance. This diagnosis method requires a voltage sensor, which is also necessary for some control methods. When applying these control methods, the proposed fault diagnosis method can be used without additional sensors, beneficial for cost reduction. A full-bridge LLC converter controlled by a digital signal processor was used as an experimental platform to verify the effectiveness and speed of the proposed diagnostic method. The results show that the proposed fault diagnosis method can achieve the fast diagnosis of high-frequency LLC converters in a short time and with only minimal computational resources.

Estimating Flood Inundation in Urban Areas Using a Scenario Generation Method and Inundation Graphs

As the frequency and intensity of natural and social disasters increase due to climate change, damage caused by disasters affects urban areas and facilities. Of those disasters, inundation occurs in urban areas due to rising water surface elevation because of concentrated rainfall from storm surges or urban drainage system failures. For this research, a scenario generation method for estimating flood inundation was developed to analyze the flood effects on urban areas to prepare for disasters and minimize damage. A scenario generation method using various distribution functions and return periods was developed and applied to create input values for the flow model for inundation analysis. By simulating multiple scenarios using a two-dimensional flow model and storing its results into a graph-form database called an inundation graph, it is possible to assess the probability and potential impact of different flood events quickly, which could be later used for disaster response and prevention. The flood risk and flood vulnerability of each section of the urban area could be evaluated based on the input data from the scenarios and the results of the flood analysis.

Hidden multiscale organization and robustness of real multiplex networks.

Hidden geometry enables the investigation of complex networks at different scales. Extending this framework to multiplex networks, we uncover a different kind of mesoscopic organization in real multiplex systems, named clan, a group of nodes that preserve local geometric arrangements across layers. Furthermore, we reveal the intimate relationship between the unfolding of clan structure and mutual percolation against targeted attacks, leading to an ambivalent role of clans: making a system fragile yet less prone to complete shattering. Finally, we confirm the correlation between the multiscale nature of geometric organization and the overall robustness. Our findings expand the significance of hidden geometry in network function, while also highlighting potential pitfalls in evaluating and controlling catastrophic failure of multiplex systems.

Credible and comprehensive? Comparing policy mixes for Local Energy Systems in England, Scotland and Wales

Integrated Local Energy Systems (LES) are being pursued internationally as a component of net zero, with additional benefits to regions and communities. This paper develops and tests a policy mixes approach to examine differential development of LES policies over 11 years in the three political jurisdictions (England, Scotland and Wales) which comprise Great Britain's (GB) single energy market. The analysis contributes to knowledge about the strengths and weaknesses of the policy mixes concept as an analytical tool for exploring divergence in devolved governments. It also considers the likely effectiveness of these policy mixes for stimulating LES developments in practice. Analysis of over 50 policy strategies and 105 policy instruments is used to evaluate the credibility of the policy mixes, ie. whether these are believable and reliable, and their comprehensiveness, ie. whether all market, system and institutional failures are addressed. The policy mix in England exhibits fluctuation and short-termism, making it the least credible. Strategies in Scotland and Wales demonstrate a more credible and ambitious policy mix for LES, including long term policies and new instruments added over time. However, limited political powers mean that the policy mixes in Scotland and Wales are less comprehensive than in England, making the realisation of LES uncertain. Further, none of the policies are designed to challenge systemic interdependencies of GB's liberalised and largely centralised energy system. This ultimately limits capacity to deliver LES and highlights the need for policy development, in GB and elsewhere, to encompass regulatory and institutional innovation to realise LES benefits.

Martha's rule: applying a behaviour change framework to understand the potential of complementary roles of clinicians and patients in improving safety of patients deteriorating in hospital.

Martha's rule stipulates the right of patients and their families to escalate care as a way to improve safety while in hospital. This article analyses the possible impact of the proposed policy through the lens of a behaviour change framework and explores new opportunities presented by the implementation of Martha's rule.. A descriptive analysis was undertaken of interactions between patients, family, friends and clinicians during clinical deterioration in hospital. The capability-opportunity-motivation behaviour change framework was applied to understand reasons for failure to respond to deterioration. Care of deteriorating patients requires recording of vital signs, recognition of abnormalities, reporting through escalation and response by a competent clinician. Regarding the care of patients who deteriorate in hospital, healthcare professionals have capability and motivation to provide safe, high-quality care, but often lack the physical and social opportunity to report or respond through lack of time and peer pressure. Patients and family members have motivation and might have time to support safety systems. Martha's rule or similar arrangements allow healthcare organisations to create opportunities for patients and families to report and escalate care to experts in critical care when they recognise deterioration. The capability-opportunity-motivation behaviour change framework provides insights into the causes of failure to rescue in deteriorating patients and an argument for opportunities through escalation by patients and families through Martha's rule. This might reduce the number of system failures and enable safer care.

Thermally Driven Multi-Objective Packing Optimization Using Acceleration Fields

Abstract The packing optimization of three-dimensional components into a design space is a challenging and time-intensive task. Of particular concern is the thermal performance of the system, as tightly packed components typically exhibit poor heat dissipation performance which can result in overheating and system failure. As temperature modeling can be quite complex, there is a growing demand in the industry for software tools that aid designers in the packing process whilst considering heat transfer. This work outlines a novel multi-objective algorithm that considers temperature and thermal effects directly within the packing optimization process itself using thermal optimization objectives. In addition, the algorithm can consider functional objectives such as a desired center of mass position and minimizing rotational inertia. The algorithm packs components from initial to optimal positions within a design domain using a set of dynamic acceleration fields. There are multiple accelerations, each designed to improve the objective values for the systems (e.g., minimize temperature variance). Component temperatures are calculated using thermal finite element analyses modeling conduction and natural convection. Forced convection is approximated via computational fluid dynamics simulations. Numerical results for two academic and one real-world case studies are presented to demonstrate the efficacy of the presented algorithm.

Diagnostics of failures of technological equipment of chemical industries using artificial intelligence

The paper considers the problem of automated recognition of single emergencies in chemical and oil refining industries. Modern chemical and technological production facilities are maintained and managed by a small number of personnel, which increases the burden on each operator. To reduce the number of operator errors, their training is regularly conducted on simulators equipped with a set of both standard situations (routine start-up, shutdown, normal process management, switching from one mode to another) and emergency scenarios (column depressurization, pump failure, failure of the power supply system). Nevertheless, it is impossible to foresee all possible failures during operator training, and even a trained operator may not notice the first signs of an accident, and therefore it is necessary to create a decision support system that helps the operator to recognize failures of technological equipment in a timely manner. To recognize failures, it is proposed to use a neural network trained on an array of simulated accident data. An industrial simulator based on the RTsim platform was used to simulate typical accidents. The novelty of the research lies in the use of artificial intelligence methods to diagnose the property of the technological process according to the SCADA system and the use of data for training a neural network not from a real object (which will always be insufficient), but from a model that exactly corresponds to a specific technological site. The number of simulated scenarios used to train a neural network can be quite large, which reduces the proportion of erroneous system responses. The developed system confidently copes with the recognition of individual equipment failures. The results obtained can be used to help process operators and to improve emergency protection systems. The analysis of the time required by the system to recognize an emergency situation can be used to design new production facilities, modify the control and management system.

Stability assessment of forestry plant power system based on improved long short-term memory network

The stability assessment of forestry power system plays a vital role in many aspects. First of all, the stability of the power system is directly related to the production efficiency, employee safety and environmental sustainability of the factory. If the power system is unstable, it may cause power outage or power fluctuations, which will interrupt the production and turn the production line, which will lead to a reduction in production capacity and the increase in production costs. In addition, the stability of the power system is directly related to the security of employees. Sudden power failure or voltage fluctuations may cause improper equipment operation, and may even cause accidents and damage. Therefore, by evaluating the stability of the power system, potential security risks can be reduced. In addition, unstable power systems may cause waste and increase environmental burden. In order to improve the stability of the power system, this article proposes an improved LSTM (long and short memory) model of improved stability prediction. This model uses the power system to operate data, including current, voltage, frequency, and other parameters, and external factors related to weather conditions and load changes to predict the stability of the power system. Compared with traditional methods, this method performs well in predicting the failure and abnormalities of the power system, and has the ability to evaluate high accuracy and stability. Therefore, the improved LSTM model method can be regarded as a powerful tool for power system management and maintenance.

Evaluation of Failure in Single-Piece Implant Systems: A One-Year Follow-Up Study.

This study's goal was to assess the failure rate and peri-implant complications of single-piece implant systems over the course of a one-year follow-up. Patient records were examined retrospectively. 150 single-piece dental implants were analyzed. Clinical results, implant features, and demographic information were gathered. Implant failure, which is characterized as the total loss of osseointegration, served as the key outcome indicator. Patient satisfaction and peri-implant problems were secondary outcomes. Data analysis employed descriptive statistics. During the one-year follow-up period, the failure rate for single-piece implant systems was 6.7%. The two main factors leading to implant failure were found to be poor osseointegration (60%) and biomechanical overload (40%). 20% of the cases had peri-implant problems, such as peri-implantitis. 85% of the panelists felt that single-piece implants had satisfied their patients. A 6.7% failure rate in single-piece implant systems was seen in this one-year follow-up investigation. The major causes of implant failure were found to be poor osseointegration and biomechanical loading. In 20% of the cases, peri-implant problems such as peri-implantitis, were noted. There was great patient satisfaction. These results highlight the significance of regulating occlusal forces, optimizing osseointegration, and applying preventive measures to ensure the long-term viability of single-piece implant systems.

A novel single-loop simulation algorithm combined with adaptive Kriging model for estimating the system failure probability function with multi-dimensional distribution parameter

A novel single-loop simulation algorithm combined with adaptive Kriging model for estimating the system failure probability function with multi-dimensional distribution parameter

Single-Center Real-World Experience with Primary Central Nervous System Lymphoma in the 21st Century

Background/Aims: In Korea, the incidence of primary diffuse large B-cell lymphoma of the central nervous system (PCNSL) is increasing and autologous stem cell transplantation (ASCT) has improved the survival of younger patients. We explored our real-world experience with PCNSL at Asan Medical Center (AMC).Methods: We used the AMC lymphoma registry to collect patient data prospectively. We analyzed 279 patients diagnosed from 2002 until August 2019.Results: The PCNSL incidence at AMC increased progressively and comprised 7.4-8.9% of new non-Hodgkin lymphoma patients annually during the most recent 4 years. The median age was 60 years (range, 17-85) and males comprised 55%. Patients under 65 years of age (n = 183) had no significant differences in characteristics compared to those aged 65 years or over, with the exception of less occipital lobe involvement and lower beta-2 microglobulin levels. Rituximab, methotrexate, procarbazine, and vincristine (R-MPV) combination induction had the best overall response, of 95%. The median overall survival was 3.8 years with 5- and 10-year survival rates of 41.5% and 30.2%, respectively. Survival was better in younger patients and those treated with ASCT. Thiotepa, busulfan, and cytoxan (TBC) conditioning chemotherapy had better survival than other combinations. The International Extranodal Lymphoma Study Group and Memorial Sloan Kettering Cancer Center prognostic score systems were valid in this cohort. Age and performance status were independent prognostic factors. Exclusive extra-central nervous system failure occurred in six patients (5.6%) among 107 failures.Conclusions: The incidence of PCNSL is rising. R-MPV induction therapy followed by ASCT with TBC has improved the survival of young, fit PCNSL patients.

Memory built-in self-repair and correction for improving yield: a review

Nanometer memories are highly prone to defects due to dense structure, necessitating memory built-in self-repair as a must-have feature to improve yield. Today’s system-on-chips contain memories occupying an area as high as 90% of the chip area. Shrinking technology uses stricter design rules for memories, making them more prone to manufacturing defects. Further, using 3D-stacked memories makes the system vulnerable to newer defects such as those coming from through-silicon-vias (TSV) and micro bumps. The increased memory size is also resulting in an increase in soft errors during system operation. Multiple memory repair techniques based on redundancy and correction codes have been presented to recover from such defects and prevent system failures. This paper reviews recently published memory repair methodologies, including various built-in self-repair (BISR) architectures, repair analysis algorithms, in-system repair, and soft repair handling using error correcting codes (ECC). It provides a classification of these techniques based on method and usage. Finally, it reviews evaluation methods used to determine the effectiveness of the repair algorithms. The paper aims to present a survey of these methodologies and prepare a platform for developing repair methods for upcoming-generation memories.

A Review of Automation and Sensors: Parameter Control of Thermal Treatments for Electrical Power Generation

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electrical power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters, such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electrical power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

Lung regeneration: diverse cell types and the therapeutic potential.

Lung tissue has a certain regenerative ability and triggers repair procedures after injury. Under controllable conditions, lung tissue can restore normal structure and function. Disruptions in this process can lead to respiratory system failure and even death, causing substantial medical burden. The main types of respiratory diseases are chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), and acute respiratory distress syndrome (ARDS). Multiple cells, such as lung epithelial cells, endothelial cells, fibroblasts, and immune cells, are involved in regulating the repair process after lung injury. Although the mechanism that regulates the process of lung repair has not been fully elucidated, clinical trials targeting different cells and signaling pathways have achieved some therapeutic effects in different respiratory diseases. In this review, we provide an overview of the cell type involved in the process of lung regeneration and repair, research models, and summarize molecular mechanisms involved in the regulation of lung regeneration and fibrosis. Moreover, we discuss the current clinical trials of stem cell therapy and pharmacological strategies for COPD, IPF, and ARDS treatment. This review provides a reference for further research on the molecular and cellular mechanisms of lung regeneration, drug development, and clinical trials.

Flood countermeasure management in bulak banteng Surabaya

The rainy season in Indonesia occurs due to the west monsoon wind blowing from the Asian continent which carries a lot of water vapor to the Australian continent due to climate change, it causes high rainfall and can potentially cause floods. In addition, the phenomenon of garbage accumulation in the river and the failure of the drainage system are the reasons for flooding in metropolitan cities, especially in Surabaya. This study aims to determine the preparedness of the community, especially the people of Bulak Banteng Village, in facing floods during the rainy season. Data were collected using the Simple Random Sample (SRS) method with 30 correspondents randomly selected at the research location. The results showed that many people were aware of the causes of flooding and the signs and impacts caused by flooding. Therefore, some people have prepared themselves in case of flooding by raising the floor of their houses so that water does not enter the house. In the event of a flood, the community prefers to evacuate themselves to a relative's place that is not affected by flooding rather than going to the disaster evacuation site provided by the local government, this happens because of the lack of training or socialization of flood response in the community, resulting in the lack of flood disaster information obtained by the community.