Plant Operational States Research Articles

Transfer learning approach to reduce similar IOT sensor data for industrial applications

The Industrial Internet of Things (IIoT) is a developing technology that has the potential to advance industrial intelligence, achieve targeted effectiveness, and lower manufacturing costs. Data fusion, a procedure that enables the collection, analysis, and processing of the enormous amounts of Internet of Things (IoT) information created by industrialized machinery and applications, is essential to IIoT's advancement and improvement of industrial products and applications. A real-time, efficient, and private information image fusion mechanism is required by the IIoT. Moreover, the current efforts call for such training of multiple systems in data analysis that also fall short of meeting real-time IIoT needs. The ineffectiveness of internal defenses and the challenge of finding the right balance between system stability and data confidentiality, however, undermine the efficiency and privacy preservation of a data fusion process. In this paper, we propose a Transfer learning-based Secure Data Fusion (TSDF) for the IIoT to address the aforementioned issues. In addition to the proposed network, we developed and deployed a defect estimation method that makes use of sensor data fusion to evaluate the manufacturing plant's operational state. The efficiency outcomes of evaluating the conceptual model are included in the original study, including a comparison to a conventional deep neural network structure. The study's findings demonstrate that TSDF may provide privacy, preserving information fusion in diverse IIoT application environments while reaching higher system capacity and low latency.

A Pragmatic Approach to Modeling Combinations of Plant Operational States in Multi-Unit Nuclear Power Plant Probabilistic Safety Assessment

One of the technical challenges in multi-unit probabilistic safety assessment (MUPSA) is dealing with numerous combinations of plant operational states (POSs) for each nuclear power plant unit. Since the number of possible combinations of POSs increases exponentially with the number of units, it is impractical to develop separate MUPSA models and assess the risk for each POS combination. This paper proposes a pragmatic approach to modeling combinations of POSs for each reactor unit in MUPSA involving up to 10 reactor units. This approach does not focus on selecting representative POS combinations but rather on screening out non-risk-significant accident sequences in a stepwise manner according to the model quantification results. The effectiveness of the approach is demonstrated by application to cases with four different numbers of units. As a result, in the 2-, 4-, and 6-unit cases, the site and multi-unit core damage frequency (CDF) due to a multi-unit loss of offsite power initiating event are successfully calculated without screening out any accident sequences for each unit. In the 10-unit case, the quantification fails without screening, but it succeeds after reducing the model size by about 43% via the exclusion of the accident sequences in each integrated single-unit model with a CDF contribution of less than 0.1%. The results show that the minimal cut sets obtained in each case cover many POS combinations and that most non-risk-significant POS combinations can be truncated by the cutoff value of 1E-14/yr. In addition, comparing the quantification results according to the stepwise screening criteria shows that the proposed approach can effectively reduce the computational burden in MUPSA without losing much accuracy or realism.

A Risk Approach to the Management for the Pre-defueled Phase in the Decommissioning Transition Stage

We discuss the specific risk significance in the extended pre-defueled (PD) phase of the decommissioning process, particularly if spent fuels are still in the core due to the low-power and shutdown refueling plant operating state (POS). The issue of full-core discharge capability after permanent shutdown during the PD phase motivated this study on the evolution of system risks using a reference plant design of the two-unit/BWR-4/Mark-I. The effects of the reactor core and the spent fuel pool (SFP) on the incorporative risks are explored. The probabilistic risk assessment methodology, including the technical elements, is systematically developed by defining two primary configurations from the internal event analysis under the models 30, 60, 180, 365, and 942 days after permanent shutdown, respectively. The movable refueling gate between the reactor core and the SFP, as well as the residual heat removal (RHR) system, have been subjected to two sensitivity studies on system configurations in order to examine the induced impacts by the refueling gate and cooling systems. MELCOR, a realistic thermal-hydraulic code, is utilized to determine the decay heat levels and the success criteria after shutdown. The two operator tasks are assumed to be independent in the situation of decreasing decay heat after shutdown and a long time available for human actions. In addition, the WinNUPRA software package is used for the fuel uncovery sequence quantification. Plant-centered loss-of-offsite power (LOOP), flow diversion loss-of-coolant accidents (LOCAs) to the suppression pool via the RHR system, switchyard-centered LOOPs, and LOCAs in the connected systems via the RHR, have proven to be the most significant initiating events for the configurations. When compared to the low-power and shutdown refueling POS, the realistic quantification results in terms of fuel uncovery frequencies and the evolution of the risk profile for the basic and sensitivity configurations meet the expectations under the PD-phase condition of low-decay heat levels.

A plant operating state analysis method in probabilistic safety assessment for multi-unit nuclear power plant

The nuclear power plants (NPPs) with more than one unit have become widespread globally, and plant operating state (POS) is a key issue to understand and manage characteristics of NPPs, especially to the safety level. Probabilistic safety assessment (PSA) is an indispensable safety analysis tool for NPPs, while it almost addresses single unit in practice at present. To perform PSA for multi-unit NPPs, the definition and evaluation of POS related to all units should be presented as preconditions. In this paper, a general framework of multi-unit POS analysis method based on single-unit POS is proposed, and the corresponding algorithm is also implemented. A case study on high temperature gas-cooled reactor - pebble-bed module (HTR-PM) is realized to verify the feasibility of this method. All possible combinations of POSs and their risk profiles for HTR-PM are obtained which could provide guidance for the subsequent operation under low power and shutdown conditions.

Towards an Integrated PHM framework of the Mutriku Wave Power Plant. Air Turbine Case Study

The Mutriku Wave Power Plant (WPP) is a wave energy conversion plant based on the oscillating water column technology that was commissioned by the Basque Energy Agency in 2011 (Torre-Enciso, Ortubia, De Aguileta, & Marqués, 2009). The Basque Energy Agency is currently the responsible for the operation and maintenance tasks of the plant. From the beginning of the operation of the plant, different degradation and failure events have been reported for WPP components including air-turbines and electric generators (Lekube, Ajuria, Ibeas, Igareta,& Gonzalez,2018), which required unplanned maintenance actions.
 Despite the thorough monitoring system included in the WPP, a-posteriori root cause failure diagnostics has been challenging due to the lack of experience in similar systems. In this context, without a direct cause-effect correlation between failures and events, the implementation of maintenance actions has been implemented through trial-and-error events, i.e. replacement of components based on intuition and expert knowledge, until the system recovered its optimal operation mode.
 The Mutriku WPP is designed as a test facility and it is located onshore into the breakwater. Therefore, the operational consequence of unplanned maintenance actions are not as critical as in future commercial open ocean WPPs. However, all the monitored information collected over the years of operation can be used to develop diagnostics models that integrate statistical learning strategies with expert knowledge and accordingly assist engineers in the maintenance decision-making processes of future WPPs.
 This paper presents an integrated prognostics & health management (PHM) framework for the Mutriku WPP. Figure 1 shows the conceptual block diagram.
 FIGURE 1 (see attached PDF)
 The expert knowledge of plant engineers will be combined with collected data and signal-processing methods to detect anomalies, diagnose the failure cause, and predict the remaining useful life (RUL) of plant components and the overall plant (Aizpurua & Catterson, 2015). The development of this approach will permit the prompt detection of anomalies for future operation events and avoid unplanned maintenance actions.
 The main components evaluated in this paper will be the air-turbines, including different information of the WPP, such as rotational speed, bearing vibration, generated power of the turbine, and pressure loss through the turbine impeller. Firstly, the paper will provide a detailed view of the developed PHM framework for Mutriku WPP (cf. Figure 1). Secondly, after the identification of abnormal patterns, a conditional anomaly detection model will be designed (Catterson, McArthur, & Moss, 2010) from the characteristic operation curve of the turbine and operation condition of the plant as shown in Figure 2.
 FIGURE 2 (see attached PDF)
 The proposed approach will be validated with real on-site monitored data. Figure 3 shows the empirical characteristic curve of an air turbine.
 FIGURE 3 (see attached PDF)
 Based on the normal operation of the turbines, including contextual information, such as sea-state and plant operational state, probabilistic multivariate models will be developed for the turbines and the operation environment and then their probabilistic correlations will be defined so as to estimate the probability of a turbine being healthy, given the operational information (see Figure 2).
 Figure 4 shows early results of the anomaly detection model, where it is possible to observe anomalies with very low likelihood.
 FIGURE 4 (see attached PDF)
 Vertical dashed line in Figure 4 indicates end of training data, and gray dashed area indicates confidence intervals for improved decision-making under uncertainty.

Vital area identification for the physical protection of NPPs in low-power and shutdown operations

Vital area identification (VAI) is an essential procedure for the design of physical protection systems (PPSs) for nuclear power plants (NPPs). The purpose of PPS design is to protect vital areas. VAI has been improved continuously to overcome the shortcomings of previous VAI generations. In first-generation VAI, a sabotage fault tree was developed directly without reusing probabilistic safety assessment (PSA) results or information. In second-generation VAI, VAI model was constructed from all PSA event trees and fault trees. While in third-generation VAI, it was developed from the simplified PSA event trees and fault trees.While VAIs have been performed for NPPs in full-power operations, VAI for NPPs in low-power and shutdown (LPSD) operations has not been studied and performed, even though NPPs in LPSD operations are very vulnerable to sabotage due to the very crowded nature of NPP maintenance. This study is the first to research and apply VAI to LPSD operation of NPP. Here, the third-generation VAI method for full-power operation of NPP was adapted to the VAI of LPSD operation.In this study, LPSD VAI for a few plant operational states (POSs) was performed. Furthermore, the operation strategy of vital areas for both full-power and LPSD operations was discussed. The LPSD VAI method discussed in this paper can be easily applied to all POSs. The method and insights in this study can be important for future LPSD VAI that reflects various LPSD operational states. Regulatory bodies and electric utilities can take advantage of this LPSD VAI method.

A systematic approach to identify initiating events and its relationship to Probabilistic Risk Assessment: Demonstrated on the Molten Salt Reactor Experiment

One of the first steps in developing a risk assessment model is an exhaustive search for initiating events, which is a systematic and comprehensive starting point to answer the question “what can go wrong?” for a given system design. Identifying Postulated Initiating Events (PIEs) for a reactor design that is at a conceptual or preliminary stage facilitates the incorporation of risk insights into the next iteration of the design process and allows for the early establishment of more quantifiable risk assessment models, such as event sequence diagrams and event tree analysis. Liquid-Fueled Molten Salt Reactors (LF-MSRs) are an example of an advanced reactor technology that does not benefit from having a wealth of operating experience or prior risk-informed safety assessment efforts. Furthermore, design details, such as normal operating conditions and the composition of radioactive material inventories, can deviate substantially from those in other reactors, such that a systematic and comprehensive approach to identifying PIEs for an LF-MSR may highlight accident initiators that have not previously been identified. In the present work, the Master Logic Diagram (MLD) and Hazards and Operability (HAZOP) study approaches were used, together, to identify and consider PIEs for multiple inventories of radioactive material across various Plant Operating States (POSs) in a specific LF-MSR design -- the Molten Salt Reactor Experiment (MSRE). Potentially risk-significant PIEs identified during the analyses of the MSRE design are presented. Furthermore, considerations for exhaustively identifying PIEs for advanced reactor designs are discussed; for example, the combination of inductive and deductive methods was found to provide a robust identification of PIEs in a way that is conducive to the analysis of a nuclear reactor design at an early design stage.

Risk reduction design alternatives for low-power and shutdown operation of a 1500-MW advanced power reactor with a passive auxiliary feedwater system

The Korean nuclear power regulatory body issued the standard design approval for a 1500-MW advanced power reactor in 2014. The reactor was designed based on a four-train independent safety concept with a passive auxiliary feedwater system. Its full power risk, or core damage frequency (CDF), was determined to be significantly lower than that of the Advanced Power Reactor 1400 (APR1400) used in Units 3 and 4 of the Shin-Kori Nuclear Power Plant. However, because the ratio of the CDF contribution to the internal full power to that of the low-power and shutdown (LPSD) is 17:83, the risk during LPSD operation requires further assessment and reduction. In this study, we investigated design alternatives for reducing LPSD operation risks and analyzed the associated sensitivities. We propose various design alternatives, and their combinations, which are analyzed based on the reduction effect they have on the CDF for plant operating states and on initiating events during LPSD operation. The proposed alternatives, and their combinations in particular, exhibited significant reductions in LPSD CDF, indicating high potential applicability.

Contribution of Human Reliability in Power Probabilistic Safety Assessment Models Versus Shutdown Models

Abstract Human reliability analysis is a method, which evaluates the human error probabilities of human failure events, which may arise when human actions are required in operation of the considered facility or system. The objective of the work is to show the contribution of human failure events in probabilistic safety assessment with focus on comparison of this contribution over the different plant operating states. The method integrates the diagnosis and action part, which are evaluated for all steps, which are needed for modeling of the human action under investigation considering the parameters, which impact the human failure probability and which are obtained from database. The results show that the risk contribution of human failure events is notably higher in low power and shutdown states than in full power operation. The results show that the human factor in shutdown plant states is the most important risk contributor regarding the contribution to the core damage frequency and regarding the risk reduction worth and risk achievement worth. Only at some plant operating states, some other groups of equipment show larger risk achievement worth than group of human failure events.

The extended living probabilistic safety assessment

The term living probabilistic safety assessment was defined soon after the initial probabilistic safety assessments were implemented. The objective of this article is to present the extended living probabilistic safety assessment and its applications considering realistic nuclear power plant models, including the low power and shutdown plant operating states. One of the key objectives is to compare the suitability of conventional and additional risk measures, core damage frequency and conditional core damage frequency, respectively. The methods are presented considering all states of the plant from the full power operation to the low power and shutdown states. The example models of the nuclear power plants and the results of the living probabilistic safety assessment of the plant operating states are discussed. The results show that the risk of low power and shutdown states is generally smaller than the risk of full power operation, but the low power and shutdown plant operating states differ significantly among each other regarding the risk level. The deficiency of living probabilistic safety assessment applied to the plant shutdown states is connected with significantly increased human effort for the analyses, with a significantly greater amount of results and with increased uncertainty of some parameters due to the larger dynamics of actions in the plant shutdown versus the full power operation states. The benefit of the living probabilistic safety assessment applied to the plant low power and shutdown states lays in consideration of all states and potential identification of risk significant states and directions for possible safety improvements.

Application of shutdown probabilistic safety assessment

Shutdown probabilistic safety assessment represents an extension of probabilistic safety assessment performed for other plant operating states, excluding power operation, which is covered in probabilistic safety assessment.The objective is to present the method of shutdown probabilistic safety assessment and its application on real nuclear power plant example model to evaluate the feasibility of the future wider use.The main methods are similar to conventional probabilistic safety assessment including the fault tree analysis, the event tree analysis, the common cause failures analysis, the human reliability analysis and the probabilistic data collection and analysis. Results interpretation reveals differences between power and other operating states probabilistic safety assessment.Most of the results have been expected including notable or significant differences among the plat operating states regarding the minimal cut sets, regarding the main risk contributors, regarding the importance factors for equipment, regarding the variability of initiating events contributions which are easily explained due to the differences among the plant operating states.The results revealed a variability of durations of the plant operating states among different shutdowns, which causes large differences in risk results among different shutdowns and different overall risk. Such variability may require the adjustment of risk informed decision making methods.

Research of the power plant operational states with block structure

In this article the research technique block structure power plant operational states is offered. As an example the operating power plant of OOO Siberian Generation Company with block structure of turbogenerators connection is considered. The choice of the operating power plant has allowed to receive to carry out the analysis real long and emergency states. The offered technique of states identification and the analysis can be used for power plant of other structure after the corresponding correction.

Low-Power and Shut-Down Condition Medium-Break Loss-of-Coolant Accident Success Criterion Analysis for a Typical Three-Loop Nuclear Power Plant

Safety equipment demands that the success criterion of useful equipment, operator-action time window, and the damage state of the reactor core can be defined by thermal-hydraulic (T-H) analysis, which makes a basic critical contribution to probabilistic safety assessment (PSA). PSA has been widely used in the safety evaluation and assessment of nuclear power plants (NPPs). A loss-of-coolant accident (LOCA) cannot be controlled without timely safety intervention. Low-power and shut-down (LPSD) conditions of NPPs can be divided into several plant operating states (POSs) in PSA analysis. After the Fukushima nuclear accident, the topic of station black-out (SBO) has drawn widespread concern. However, some LPSD conditions, which result in severe consequences like SBO, have not drawn widespread attention and are thus analyzed and discussed herein. This paper analyzes a medium-break LOCA (MBLOCA) under a certain LPSD condition for a typical three-loop NPP. A simplified method of simulating and selecting operator-action time of MBLOCA for PSA is developed. The proposed method calculates the time windows for both manually opening the high head safety injection system (HHSI) and secondary depressurizing of the system to keep the core undamaged, which could support building PSA model and human reliability analysis.

Study of Accident Progression in Unsealed WWER-1000/V320 Reactor during Maintenance

This paper discusses the results obtained during an investigation of WWER-1000 Nuclear Power Plant (NPP) behavior at shutdown reactor during maintenance. For the purpose of the analysis is selected a plant operating state with unsealed primary circuit by removing the MCP head. The reference nuclear power plant is Unit 6 at Kozloduy NPP (KNPP) site. RELAP5/ MOD3.2 computer code has been used to simulate the transient for WWER-1000/V320 NPP model. A model of WWER-1000 based on Unit 6 of KNPP has been developed for the RELAP5/MOD3.2 code at the Institute for Nuclear Research and Nuclear Energy-Bulgarian Academy of Sciences (INRNE-BAS), Sofia. The plant modifications performed in frame of modernization program have been taken into account for the investigated conditions for the unsealed primary circuit. The most specific in this analysis compared to the analyses of NPP accidents at full power is the unavailability of some important safety systems. For the purpose of the present investigation two scenarios have been studied, involving a different number of safety systems with and without operator actions. The selected initiating event and scenarios are used in support of analytical validation of Emergency Operating Procedures (EOP) at low power and they are based on the suggestions of leading KNPP experts and are important in support of analytical validation of EOP at low power.

Outage Key Safety Functions Configuration risk assessment for a three loops Westinghouse PWR

The methodology developed provides guidance on the use of Probabilistic Safety Assessment (PSA) for the risk-informed evaluation of Guides which ensure the compliment of Outage Key Safety Functions (OKSFs) in Nuclear Power Plants. The methodology has been applied to the 3rd and 13th Plant Operational States (POSs) as a pilot experience. These POSs are within the Operating Mode 4 (Hot Shutdown) of a three loops Westinghouse Pressurized Water Reactor. The addressed Guide requires the operability of just one charge pump as boric acid supply source. PSA gives a Core Damage Frequency increase (ΔCDF) of 1.19×10−6year−1 for the unavailability of the charge pump in standby, consequently, the maximum exposure time (time for the Increase of Core Damage Probability of the configuration to reach 1.0E−06) for this situation is T=53.6h. Given an average time for the POSs of 40h, it is concluded that the charge pumps requirement is correct. However, it could be improved with the inclusion of an additional inventory replacement function. This would limit the effect on risk of the charge pump unavailability. Furthermore, the need for the external electrical sources to be available during Mode 4 is ratified. The procedure requires the operability of both supply sources during the POSs. The unavailability of one of supply sources them involves a ΔCDF equal to 1.64×10−5year−1 and a maximum exposure time of T=3.89h. This requirement is considered appropriate from the risk-informed regulation point of view.

Evaluation of plant operational states with the consideration of loop structures under accident conditions

Nuclear power plants have logical loop structures in their system configuration. This paper explains the method to solve a loop structure in reliability analysis. As ex- amples of loop structured systems, the reactor core isolation cooling system and high- pressure core injection system of a boiling water reactor are considered and analyzed under a station blackout accident condition. The analysis results show the important role of loop structures under severe accidents. For the evaluation of the safety of nuclear power plants, it is necessary to accurately evaluate a loop structure's reliability. Copyright © 2015, Published by Elsevier Korea LLC on behalf of Korean Nuclear Society.

발전소 설비 운영상태 지능감시 시스템 개발

For safe and stable operations of power plants, it is essential to monitor closely crucial measurement values related to power plant trips. In this paper, an intelligent power plant operating state monitoring technique enabling the operating crew member to monitor conveniently the status of the important measurement values and to perceive almost instantly the significance of the implications of those measurement values is developed. The proposed technique is called a “POST(Plant Operating State Tracking) Chart” technique and provides the foundations in developing an intelligent and integrated power plant operating state monitoring support system called the “P-OASIS”(Plant Operation Assessment and Support Intelligent System). The P-OASIS is applied to a thermal power plant of 500[㎿] capacity and exhibited impressive performances.

Development of Operator Action Time for SBLOCA during Plant Shutdown Operation in Power-uprated Kori 3 and 4

The ECCS performance, which mitigates a postulated catastrophic failure of the main reactor coolant piping during the full power operation, is judged to cover the consequences of LOCA occurring in other plant operational states. During Mode 3 with an accumulator isolated and Mode 4, since the normal alignment of ECCS equipments is changed from that which is available during the power operation, a potential safety issue, which involved the performance of ECCS for LOCA during Mode 3 with the accumulator isolated and Mode 4, was identified in 1985. This study is performed as the plant specific shutdown LOCA program for the power uprated Kori-3 and 4, of which the nominal core power is planned to increase by 4.5%. We determine and verify the operator action time to initiate SI following a small break LOCA in order that the peak clad temperature of fuel does not exceed the 10CFR50.46 limit of 1,477.6 K. We evaluate the 0.1524 m (6 inches) pipe break in the cold leg to develop the SI initiation time. There is a considerable margin to the 10CFR50.46 limit of 1,477.6 K in the case that the SI is manually initiated at 25 min after an operator identifies the symptom of a small break LOCA. However, in respect of the safe plant operation, we decide the operator SI initiation time as 15 min in order that the SI water is supplied to prevent the fuel heat-up during the blowdown phase of a small break LOCA. After then, we evaluate the applicability of the pre-determined SI initiation time to other small break LOCAs, which have a smaller break size, a lower initial decay heat level or a different break location. Since the peak clad temperatures of applicability evaluation cases are lower than those of the umbrella case, we confirm that the pre-determined SI initiation time can be applied to mitigate the small break LOCAs during the plant shutdown operation. The SI initiation time developed in this study will be used in the Abnormal Operating Procedure of the power uprated Kori-3 and 4 for the small break LOCAs during the plant shutdown operation.

Some Aspects of Nuclear Power Plant Safety under War Conditions

In the summer of 1991, the Krsko nuclear power plant in Slovenia found itself in an area of military operations. This was probably the first commercial nuclear power plant to have been threatened by an attack by fighter jets. A number of never-before-asked questions had to be answered by the operating staff and supporting organizations. Some aspects of nuclear power plant safety under war conditions are described, such as the selection of the best plant operating state before the attack and the determination of plant system vulnerability and dose releases from the potentially damaged spent fuel in the spent-fuel pit. The best operating mode to which the plant should be brought before the attack is cold shutdown, and radiological consequences to the environment after the spent fuel is damaged and the water in the pit is lost are not very high. The problem of nuclear power plant safety under war conditions should be addressed in more detail in the future.