Shutdown System Research Articles

The genesis of hydrothermal veins in the Aukam valley SW Namibia– A far field consequence of Pangean rifting?

High purity fluorite veins (acid grade > 97 % CaF2) are generally rare in a global context. The fluorite-(±quartz-calcite) veins in the Aukam Valley mining district in SW Namibia have not previously been studied but due to their excellent exposure they are an ideal natural laboratory to study such mineralization. These veins cross-cut Mesoproterozoic high-grade gneisses and granites (Namaqua-Natal Metamorphic Province) close to the unconformity with the overlying late-Neoproterozoic Nama Group sedimentary rock cover. Based on the regional context, their genesis has been assumed to be related to nearby fluorite-bearing pegmatites. However, the present contribution provides new microthermometry data from vein fluorite (with 25.0–25.6 wt% NaCl and Th of 270–300 °C) that indicate precipitation from a mixed fluid with two chemically contrasting end-members for the early paragenetic fluorite stage. However, it was not possible to identify the chemical composition of the endmembers. Based on the chemical composition of the fluid mixture and the regional geological context, we propose that these end-members are F-rich brines sourced from the Namaqua basement and Ca-rich limestone-derived formation fluids of the Nama Group. A fluorite-overgrowing quartz precipitation is likely the effect of post-mixing fluid cooling as the fluid inclusions hosted in quartz show lower homogenization temperatures (Th 230–260 °C) with similar salinity. Locally, late-stage calcite is recognized with fluid inclusion compositions (0.2–2.7 wt% NaCl and Th of 60–92 °C) different from those observed in the fluorite and quartz. With significantly lower homogenization temperatures, they likely represent precipitates formed during the shutdown and collapse of the hydrothermal system. The fluorite veins are hosted in post-Cambrian N-trending brittle structures that probably formed during the opening of the South Atlantic in late Mesozoic times. Interestingly, similar massive fluorite mineralization on both sides of the Atlantic Ocean is also likely associated with Pangea rifting and known from numerous mining districts operating on unconformity-related hydrothermal veins in Central and North America, northern Africa and Europe.

Cyber-shock and “digital withdrawal”: Organizational lLeadership and Crisis Management During a Hospital-wide Computer Shutdown Following a Ransomware Attack

Introduction:In October 2021, Hillel Yaffe, MC, suffered a ransomware attack which shutdown most hospital computer systems, including patient EMR, pharmacy, communications, administration and backup systems. Staff were left in a state of “cyber-shock” without access to essential information for maintaining safety, quality and continuity of care. The aim of this presentation is to share the hospitals' experience and insights of this cyber-attack, outlining preparedness and response strategies.Method:This attack required a multifaceted emergency response strategy, including: Immediate response activated according to specific pre-prepared emergency scenario action listsLeadership decision making in real time under conditions of uncertaintyIdentifying the extent of systems affectedEstablishing alternative communication across the organizationDistributing real-time status updates and proactive guidelines, based on pre-existing emergency preparedness protocolsFinding alternative access to patient health historiesAdaptation and distribution of alternative hardcopy versions of patient evaluation and documentation normally done by EMRDistribution of instruction materials for staff via alternative communication, ensuring quick and correct adoption of alternative protocolsSpecial emphasis on patient safety, risk management, quality and continuity of careRecognition, support and resilience-building for staff facing uncertainty and unprecedented conditionsResults:Required preparations include pre-prepared standing orders and procedures, exercises and simulations. Advanced preparation of alternative documentation and care protocols will enable uninterrupted, safe, high-quality patient care. Familiarity with pen-and-paper documentation may minimize shock and disorientation from “digital withdrawal”, especially among younger workers lacking manual documentation experience. Staff members should also be instructed in maintaining “digital hygiene”, such as using strong passwords and awareness about cyber-security threats.Conclusion:Hospitals must prepare for potential cyber-attacks and EMR/digital system shutdowns. Cyber-attack should be treated by organizations as an emergency event, and they should prepare incident response and contingency plans, to assure business continuity and quick disaster recovery.

Design and Implementation of an Oil and Gas Surface Processing Plant using Digital SCADA

Abstract: The oil and gas surface processing plant or station is the gathering station where the crude oil is separated into its constituent units of oil, water, and gas. This paper reports the sensor data capturing, the process operation, and the SCADA design of the processing unit using Wonder-ware InTouch Software. The system monitors/controls various process variables including pressure, temperature level, flowrates, and the emergency shutdown system based on the Cause & Effect Chart.

An effective PEMFC system shutdown purge strategy for improving the purging effect of liquid water and the dehydration of stack

The shutdown process is one of the critical stages when the proton exchange membrane fuel cell system runs as an actual application. Finding the effect of system operating conditions on shutdown purging could improve the purging effect of liquid water and the dehydration of the stack. In this study, an automotive fuel cell system of 350 single cells was developed on the vehicle scale and tested for factors that influence shutdown process. Seven shutdown purge cases for about 150 s were studied to investigate the shutdown purge strategy. It was found that 100% bypass valve opening reduced the purge time and improved the purge efficiency. The HCP speed should not be too slow or too fast in the shutdown process. The higher temperature of coolant water favored rapid shutdown and purge, and a large stoichiometric ratio of the cathode inlet improved the purge effect but enhanced the energy consumption of the air compressor. Neither too high nor too low purge pressure could blow out the liquid water more efficiently and improve the ohmic resistance. During purging, current density mainly influenced the water production rate and the maintenance state of stack temperature. With a higher stack temperature, purge process with a small current density could quickly reduce the stack humidity and enhance the ohmic resistance. Accelerating the opening rate of the anode purge valve could not effectively accelerate purge effect of the stack, while extending the valve closing time could improve hydrogen utilization. Future studies to investigate the combined impact of these factors on the fuel cell system shutdown purge will be carried out to develop the most effective strategy.

Analytical Modeling, Analysis and Diagnosis of External Rotor PMSM with Stator Winding Unbalance Fault

Multiple factors and consequences may lead to a stator winding fault in an external rotor permanent magnet synchronous motor that can unleash a complete system shutdown and impair performance and motor reliability. This type of fault causes disturbances in operation if it is not recognized and detected in time, since it might lead to catastrophic consequences. In particular, an external rotor permanent magnet synchronous motor has disadvantages in terms of fault tolerance. Consequently, the distribution of the air-gap flux density will no longer be uniform, producing fault harmonics. However, a crucial step of diagnosis and controlling the system condition is to develop an accurate model of the machine with a lack of turns in the stator winding. This paper presents an analytical model of the stator winding unbalance fault represented by lack of turns. Here, mathematical approaches are used by introducing a stator winding parameter for the analytical modeling of the faulty machine. This model can be employed to determine the various quantities of the machine under different fault levels, including the magnetomotive force, the flux density in the air-gap, the flux generated by the stator winding, the stator inductances, and the electromagnetic torque. On this basis, a corresponding link between the fault level and its signature is established. The feasibility and efficiency of the analytical approach are validated by finite element analysis and experimental implementation.

Application of Fast-Charging Graphite-Anode Lithium-Ion Batteries in Black Start

Industrial and commercial energy storage are widely used. Large industrial users can adjust the peak and valley power consumption during the summer peak power consumption to reduce the burden on transformers and to gain certain benefits from the peak and valley power difference. For users with important loads, the energy storage system is a alternative power supply to ensure the continuity of power supply for important loads. This paper systematically introduced the research progress based on the optimization of electrolyte and charging strategy in the field of improving the rapid charging of graphite anodes in recent years, which provided a reference for promoting the commercial application of rapid charging technology and the high-quality development of domestic energy storage technology. The high-power energy storage battery, in particular, can recover power supply as soon as possible after large-scale power system shutdown accidents or even power outages, reducing economic losses and social impact.

A safety enhanced sodium-cooled MOX fueled fast reactor core concept

ABSTRACT We have developed a 750MWe sodium-cooled MOX fueled fast reactor core with enhanced safety against typical ATWS. Design goals were set as follows: 1) negative void reactivity for the loss of flow (ULOF); and 2) burnup reactivity less than 1 $ for the transient over power (UTOP). To achieve the goals the following were considered: 1) adoption of the axially heterogeneous core with a sodium plenum and a gas expansion module to reduce void reactivity; and 2) addition of minor actinides (MAs) to the internal blanket to reduce burnup reactivity. Configurations of the core were optimized as follows. First, void reactivity was reduced by a parameter survey for the inner core height, B-10 content of the upper shield, and standby position of the backup control rods. Second, burnup reactivity was reduced by a parameter survey for the MA content in the internal blanket, etc. We designed the safety enhanced fast reactor core that did not undergo sodium boiling if the ULOF occurred and we maintained fuel integrity for the UTOP by the transient analysis. By installing a self-actuated shutdown system in the backup control rods, the improved operational reliability of this shutdown system and the improved safety can be expected.

An Empirical Analysis of State-of-Art Classification Models in an IT Incident Severity Prediction Framework

Large-scale companies across various sectors maintain substantial IT infrastructure to support their operations and provide quality services for their customers and employees. These IT operations are managed by teams who deal directly with incident reports (i.e., those generated automatically through autonomous systems or human operators). (1) Background: Early identification of major incidents can provide a significant advantage for reducing the disruption to normal business operations, especially for preventing catastrophic disruptions, such as a complete system shutdown. (2) Methods: This study conducted an empirical analysis of eleven (11) state-of-the-art models to predict the severity of these incidents using an industry-led use-case composed of 500,000 records collected over one year. (3) Results: The datasets were generated from three stakeholders (i.e., agency, customer, and employee). Separately, the bidirectional encoder representations from transformers (BERT), the robustly optimized BERT pre-training approach (RoBERTa), the enhanced representation through knowledge integration (ERNIE 2.0), and the extreme gradient boosting (XGBoost) methods performed the best for the agency records (93% AUC), while the convolutional neural network (CNN) was the best model for the rest (employee records at 95% AUC and customer records at 74% AUC, respectively). The average prediction horizon was approximately 150 min, which was significant for real-time deployment. (4) Conclusions: The study provided a comprehensive analysis that supported the deployment of artificial intelligence for IT operations (AIOps), specifically for incident management within large-scale organizations.

Passive Thermography Based Bearing Fault Diagnosis Using Transfer Learning With Varying Working Conditions

Bearing is one of the core components of any rotating machine, and its failure is widespread. This reason drives continuous monitoring and detecting bearing faults during machine operation to warn operators and prevent unforeseen damage. This paper proposes an intelligent Passive Thermography (PTG) based fault diagnosis technique for detection of bearing faults using Convolutional Neural Network (CNN) with Transfer Learning (TL) under varying working conditions. The validation of the proposed method has been done on three different datasets; bearing test rig dataset has been taken as a source domain data while Induction Motor (IM), and Machine Fault Simulator (MFS) datasets have been taken as target domain data. The proposed method enables and speeds up the training process of CNN towards accurate adaptation for fault diagnosis approach in the escalated time frame. The experimental results demonstrated that the suggested approach could successfully learn transferable characteristics from the source domain model, which can cope with the issue of limited availability of training data required for the target domain. The classification accuracy on the target domain dataset were varied in the range of 89 -95.4 % in the case of the IM dataset and 96.5-97.5% in the case of the MFS dataset. Moreover, it shows the benefits of the suggested method, which may be utilized as an effective non-invasive diagnostic tool for rotating machines to avoid unexpected system shutdowns.

Hollow fiber membranes comprising of polyvinylamine/polydopamine active layers and a polyvinylidene fluoride substrate for pervaporative concentration of KAc solutions

We report on a thin-film-composite hollow fiber membrane comprising a hydrophilic active layer and a hydrophobic substrate for pervaporative concentration of KAc solutions. A hydrophobic substrate was chosen in order to overcome the potential problems of liquid water crossover through the membrane that typically occurred with a hydrophilic substrate over a prolonged period as a result of capillary condensation and gradual pore wetting even after system shutdown. Attempts were made to co-deposit PVAm/dopamine onto a PVDF hollow fiber substrate to form thin-film-composite hollow fiber membranes. However, it was challenging to deposit hydrophilic macromolecules on a hydrophobic surface. To facilitate the deposition of dopamine/PVAm onto a hydrophobic substrate, where PVAm macromolecules were securely attached to the substrate with the assistance of adhesive dopamine, methanol was used as a co-solvent to improve surface wetting and pre-coating of dopamine was used to form a hydrophilic binding layer that was better prepared for subsequent dopamine/PVAm deposition. It was shown that the use of co-solvent water/methanol (90/10 in vol) in the depositing solution and precoating dopamine for 3 h prior to co-deposition of dopamine/PVAm were appropriate for membrane formation, and the resulting membrane showed stable performance in concentrating KAc solutions at a high feed concentration (70 wt%) over a period of 200 h at an operating temperature of 70℃. A stable water flux of 1.7–1.9 kg/m2h was achieved, with an essentially complete salt retention.

Batch Deterministic and Stochastic Petri nets Modeling for Reliability Quantification for Safety Critical Systems of Nuclear Power Plants

Safety-critical systems (SCS) are essential in maintaining and controlling the nuclear power plant (NPP) facilities, providing feedback on the plant's conditions, and safeguarding it from adverse consequences i.e., SCS plays a vital role in NPP. Thus, failure of such systems can lead to massive financial losses, human resource damage, and environmental degradation. It is, therefore, important that these systems should have a high level of reliability and accuracy. This research introduces a novel method for designing and assessing the reliability of SCS by employing batch deterministic & stochastic Petri nets (BDSPNs) and Markov chain. Our method of reliability evaluation achieved 99.9905% accuracy, proving its effectiveness. This paper illustrates the proposed approach to NPP's Shutdown System (SDS).

Deep learning for photovoltaic defect detection using variational autoencoders

Faults arising in photovoltaic (PV) systems can result in major energy loss, system shutdowns, financial loss and safety breaches. It is thus crucial to detect and identify faults to improve the efficiency, reliability, and safety of PV systems. The detection of faults in large PV installations can be a tedious and time consuming undertaking, particularly in large-scale installations. This detection and classification of faults can be achieved using thermal images; use of computer vision can simplify and speed up the fault detection and classification process. However, a challenge often faced in computer vision tasks is the lack of sufficient data to train these models effectively. We propose the use of variational autoencoders (VAEs) as a method to artificially expand the data set in order to improve the classification task in this context. Three convolutional neural network (CNN) architectures – InceptionV3, ResNet50 and Xception – were used for the classification of the images. Our results provide evidence that CNN models can effectively detect and classify PV faults from thermal images and that VAEs provide a viable option in this application, to improve model accuracy when training data are limited.Significance: Faults in PV systems can be labour and time consuming to detect and classify. This process can be automated by using computer vision and thermal images. CNN models (InceptionV3, ResNet50 and Xception) are effective in the detection and classification of PV faults from thermal images. Small data sets are a common barrier to entry for computer vision assessments. VAEs provide an effective method to artificially expand a limited data set to allow for the successful use of CNN models. The expansion of training data using VAEs for CNN models can improve the prediction accuracy in these models.

Water detection framework for industrial electric arc furnaces: Boundary modelling and formulation

AbstractThis paper describes the development of a boundary model for the off‐gas water vapour in an industrial steelmaking electric arc furnace (EAF). The solution addresses the mechanistic components of a complete EAF water detection framework. The boundary model has been implemented on an industrial alternating current (AC) EAF. The model specifies upper and lower limits in real‐time of the expected EAF off‐gas water vapour leaving the furnace, and it provides a valuable on‐line monitoring tool to the operator on what boundary to expect for the off‐gas water vapour in different circumstances. An essential data required for the framework is the EAF off‐gas composition. So, in this work, an off‐gas analyzer with a human machine interface (HMI) and a supervisory control and data acquisition (SCADA) system was installed in the first step. Then, in order to evaluate the developed water leak detection framework and verify the obtained results, industrial trials were designed in which a certain amount of water was intentionally added into the furnace by increasing the electrode spray water flow rate. Moreover, we have shown how the presented framework can be used to appropriately adjust the alarm setting values in control/emergency shutdown systems of industrial EAF to enhance the safety and availability of the plant.

Engine room thermal density specials in heating systems shutdow process

THE PURPOSE. Consider the effect of heating system turning off process on the engine room thermal density in a high-voltage city sewage pumping station. Determine how the heating system shutdown affects to the considered room thermal regimes with unchanged requirements for the indoor air microclimate thermal and moisture parameters. Do a numerical experiment which simulates the stationary thermal regime of engine room and taking into account the main technological process in this room of a high-voltage city sewage pumpingstation. Perform adaptation of thermal regime developed model to simulate the heating system turning off process. Describe the distribution of heat losses in the engine room while maintaining a constant air temperature. METHODS. When solving the task, author has used the method of calculating the engine room design stationary mode.RESULTS. Researcher describes the relevance of the topic, considers the specials of the change in the engine room thermal density when the heating system is turned of and other factors. Author has presented the results of the thermal excesses calculation for different numbers of operating pumps and changes in wastewater temperature.CONCLUSION. The turning off process of the heating system reduces the thermal density of the engine room by an average of 0.3 - 0.4 W/m3. This method of energy saving helps to reduce the consumption of thermal energy and could be used in this part of sewage pumping station. The economical effect of proposed energy saving measurement will be in economical index reducing. It will be 890 000 rubles saving per year for this type of sewage pumping station in designed mode.

Performance Evaluation of Control Compatibility for an OTEC Pump Shutdown Condition

South Korea is currently in the preparatory stage of commercializing an ocean thermal energy conversion (OTEC) system, as the demonstration of a 1 MW scale OTEC system has been accomplished. However, the commercialization of OTEC requires the establishment of a control system for various environmental changes. Therefore, pre-emptive identification of the system’s risk factors and the process of analyzing the impact of the system, building control items, and optimizing control are necessary. This study aims to establish and analyze an optimized control system for MW-scale OTEC risk factors, such as the shutdown of seawater or refrigerant pumps. The selected OTEC system was designed for 1070 kW class facilities, with a 36.6% portion of total electricity usage by the seawater pump and refrigerant pump. As a result, an on/off control system was adopted in order to eliminate the risk factors. By adjusting this option, dry operation of the refrigerant pump, water hammering, and liquid inflow into the turbine were successfully prevented. To be more specific, the initial system was to be shut down due to a sharp decrease in power at the point where the deep seawater flow rate was 538 kg/s (35.7% of max flow rate) and the surface seawater flow rate was 715 kg/s (38.4% of max flow rate). This situation was improved by adopting parallel operation of seawater pumps and on/off control, thereby leading to a more stabilized operation by maintaining a flow rate of over 1864 kg/s for surface seawater and 1507 kg/s for deep seawater. Moreover, it was confirmed that the flow rate of the pump was reduced by 1.89 kg/s per second in the process of pump shutdown during a single operation mode of the refrigerant pump. Parallel operation made it possible to maintain 60.2% of the output by increasing the power of the second pump’s flow rate in the event of the first pump shutting down. The final seawater temperature differential power generation model derived from this study consists of two refrigerant pumps and two surface seawater and deep seawater pumps in order to prevent system shutdown caused by a single pump failure. The final design was reflected in the final delivery to Kiribati, which is located near the equator.

Nonlinear dynamic verification of the boron injection lances for the Atucha-I Nuclear Power Plant

This work deals with the nonlinear transient dynamic verification of the boron injection lances for the Atucha-1 Pressurized Heavy Water Reactor backup shutdown system. The lances inside the moderator tank constitute the end part of the fast boron injection piping. The current dynamic verification of the lances is performed in the context of modifications in the piping and valve configuration for Atucha-I Long Term Operation (LTO). It is intended to ensure the structural integrity of the lances in the event of Loss of Coolant Accidents (LOCA) and spurious opening of level control valves (Spurious) scenarios. All boundary conditions have been provided by Nucleoeléctrica Argentina S.A. (NA-SA), and a 3-D numerical model of the lances was built and analyzed with the open-source suite Salome-Meca v2019 using the Code_Aster finite element solver. Results indicate that the displacement of the lances does not produce collisions with other reactor internals and that stresses on the lances and their fastening bolts are low enough to ensure the correct function of the system during LTO period.

Performance Analysis of a Hybrid of Solar Photovoltaic, Genset, and Hydro of a Rural-Based Power Mini-Grid: Case Study of Kisiizi Hydro Power Mini-Grid, Uganda

The power sector in Uganda has increased steadily, focusing majorly on rural electrification to increase the proportion of the rural population accessing electricity using grid extension and isolated mini-grid approaches. Hydropower mini-grids implemented in rural communities have issues regarding system failures leading to shutdowns and load shedding. A study on an existing isolated hydropower mini-grid was made to find the possible causes. A review of published articles and reports, and an analysis of enrollment patterns, energy sales, and load demand was carried out. A field survey with a guided questionnaire to collect information about real energy demand data was carried out. The performance of the system was accomplished through simulation using HOMER pro × 64 software. The findings from the study show a reduction in customer enrollment, a reduction in energy sales, and a reasonable number of system shutdowns. Hybridization of the existing hydropower was modeled with different options. The hybrid system proposed indicates that, when implemented, it would reduce fuel consumption from 222 to 23.2 L/day and emissions from 82.5 to 8.3 kg/year on average and increases system reliability. Simulated values of NPC, LCOE, and operating costs are appreciable. Despite mini-grid shortfalls, there is notably improved livelihood due to improved social and economic services.

Saving the environment by automation of crude oil distillation in a rectification column

The article shows the results of the development of an automated control system for the distillation of oil in a distillation column, which makes it possible to save the environment. In the theoretical part, the process of distillation of crude oil in a distillation column is described and its technological scheme is given for atmospheric distillation with a single evaporation of oil. In the calculation part, the heat and material balance of mass transfer in the rectification column has been analyzed. In the practical part, the problems of installing process control instruments, improving the emergency shutdown system reliability, expanding the automatic and automated monitoring and control functions, and improving the process control and facility performance analysis quality have been solved. The authors used the Trace Mode 6 software package to develop the SCADA of the distillation column control system. In conclusion, it was noted that the development and implementation of an automated control system for the oil distillation process provides an increase in plant productivity, as well as the quality and reliability of the process, which in turn has a positive effect on environmental conservation.

Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System

Currently, providing water in developing countries, especially in dry and hot rural areas, is a significant challenge. However, creating new electric grids is often expensive. Therefore, the use of low-cost photovoltaic (PV) panels in water pumping systems, without chemical energy storage, based on high-performance and more efficient power converters with increased time life and lower maintenance interventions is needed. In this study, a photovoltaic water pumping system with two power converters, the first is used to extract the maximum power using the maximum power point tracking (MPPT) algorithm, and the second is a three-cell multicellular power converter used to control the DC motor with a submerged pump. Meanwhile, the serial connection and redundant topology of multicellular converters render the system more vulnerable to failure. fault diagnosis-based machine learning approach and fault tolerant control (FTC) are proposed for multicellular power converters. Simulation results with MATLAB show the effectiveness and practicability of the proposed structure and control to isolate the faulty capacitor, increase the sustainability of the system, assure the supply of water under faulty conditions, minimize the mechanical vibrations in electric DC motors, and avoid PV system shutdown.

Study on current sharing characteristics of multi-column parallel arresters

The ideal working conditions of a multi-column parallel arrester is to share the energy generated when it is impacted, otherwise it will lead to a breakdown of the arrester and the forced shutdown of the HVDC system, resulting in significant economic losses. This paper analyzes the current sharing characteristics of multi-column parallel arresters under different current waveforms, different current amplitudes, different temperatures, and different cumulative impulse times. The results show that the current waveform, current amplitude, and temperature difference between the columns all affect the current sharing characteristics. The current deviation coefficient is positively correlated with the current wave head time. The closer the current value is to the balancing point, the smaller the deviation coefficient. The temperature difference between the columns has the greatest influence on the current deviation coefficient. As the temperature difference increases, the current deviation coefficient may exceed 10%. Finally, based on experimental conclusions, some suggestions are put forward to modify the operation rules of large-capacity multi-column parallel arresters, which provides an important reference for subsequent projects.