Development of a software tool for the analysis and verification of emergency operating procedures through the integrated simulation of plant and operators actions

Probabilistic safety assessment (PSA) includes operator actions as elements in the set of the considered protection performances during accident sequences. Nevertheless, its impact throughout a sequence is not usually analyzed dynamically. In this sense, it is convenient to make a more detailed analysis about its importance in the dynamics of the sequences, allowing for sensitivity studies with respect to human reliability and response times. For this reason, new developments in simulation software must be able to incorporate operator actions in conventional thermalhydraulic simulations. In this paper, we present one of these new tools, the TRETA/TIZONA–COPMA III coupled codes, which can be used for evaluating the impact in the final plant state of the execution by operators of procedures and the evaluation of the available times for the manual actions of the operators. This software tool consists of a closed-loop plant/operator simulator: a thermalhydraulic code for simulating the plant transient (TRETA for PWR NPPs and TIZONA for BWR NPPs) and the procedures processor (COPMA III) to simulate the operator actions requested by the procedures, both coupled by a data communication system which allows the information exchange (SWBus). The first pilot cases have been performed in order to analyze sequences initiated by secondary side breaks leading to loss of heat sink sequences in a PWR plant. These tests have been carried out using the real plant EOPs for COPMA-III and a PWR plant model for TRETA code. The results of these simulations are presented in this paper.     

Development of a standard communication protocol for an emergency situation management in nuclear power plants

Correct communication between main control room (MCR) operators is an important factor in the management of emergency situations in nuclear power plants (NPPs). For this reason, a standard communication protocol for the management of emergency situations in NPPs has been developed, with the basic direction of enhancing the safety of NPPs and the standardization of communication protocols. To validate the newly developed standard communication protocol, validation experiments with 10 licensed NPP MCR operator teams was performed. From the validation experiments, it was found that the use of the standard communication protocol required more time, but it can contribute to the enhancement of the safety of NPPs by an operators’ better grasp of the safety-related parameters and a more efficient and clearer communication between NPP operators, while imposing little additional workloads on the NPP MCR operators. The standard communication protocol is expected to be used to train existing NPP MCR operators without much aversion, as well as new operators.     

秦山一厂严重事故管理导则典型事故缓解对策有效性验证

在日本福岛核事故后,国家核安全局要求核电运营单位提升应对严重事故的能力。按照国家核安全局要求,秦山一厂开发了严重事故管理导则。应用MELCOR程序建立了秦山一厂严重事故分析模型,模拟典型严重事故序列,根据严重事故管理导则的缓解对策,分析实施事故缓解对策对核电厂主要参数的影响,从而验证事故缓解对策的有效性。分析结果表明:在严重事故情况下,按照严重事故管理导则实施缓解对策,可有效地延缓或终止堆芯损坏的过程。     

A neural network based operation guidance system for procedure presentation and operation validation in nuclear power plants

An operation guidance system (OGS) was developed to regulate and supervise operators’ actions during abnormal environments in nuclear power plants (NPPs). The system integrated a primitive computerized procedures system (CPS) and an operation validation system (OVS) imbedded in a virtual simulated operational environment. As the key component of the OGS, OVS provided two important functions for the operators: validated check of operations, and qualitative and quantitative effects analysis of operations. Each of operators’ action was evaluated by the system and possible results were simulated by using artificial neural networks (ANN). Finally, corresponding suggestion or warning was provided to operators. This should reduce human errors during operation in emergency scenarios.     

Investigating the effect of task complexities on the response time of human operators to perform the emergency tasks of nuclear power plants

For many decades, since the reliable performance of human operators is decisive for securing the safety of large process control systems, proceduralized tasks have been widely used to enhance their performance. For this reason, TACOM measure has been developed to quantify the complexity of proceduralized tasks to be conducted by operating personnel working in nuclear power plants (NPPs), because it is strongly expected that complicated tasks could directly result in the degradation of human performance. This expectation seems to be supported by comparing two kinds of human performance data (response time data and subjective workload scores) obtained from the simulated emergency situations of domestic NPPs with the associated TACOM scores. In addition, the results of previous studies make it possible to assume that the performance of human operators would be comparable if they have to accomplish a series of proceduralized tasks having similar levels of task complexities. In this study, in order to scrutinize the appropriateness of this assumption, response time data originated from domestic as well as overseas NPPs were compared with the associated TACOM scores. As a result, it was observed that TACOM scores are important to explain the changes of response time data collected from both the domestic and the overseas NPPs. Therefore, although additional studies are indispensable, this result is meant to show that the performance of human operators would be largely affected by the levels of task complexities, which can be properly quantified by TACOM measure.     

Investigating the execution of EOPs in LOTDFP + ATWS + LOCA scenarios for an ABWR using MAAP code

The effectiveness of the execution of emergency operation procedures (EOPs) for an advanced boiling water reactor (ABWR) during postulated accident conditions using MAAP 4 code is discussed in this paper. The simulation scenarios included the loss of turbine driven feedwater pump (LOTDRFP), the anticipated transients without scram (ATWS), and the loss of coolant accident (LOCA). Based on the comparisons of responses on different parameters for cases with and without EOP actions, we concluded that the EOPs could effectively mitigate the consequences of the accidents. In addition, the emergency depressurization (ED) timing and the times spent between executing the EOP steps were also considered. The simulation results clearly reveal that both the earlier execution of ED and the decrease of times spent between each EOP step could delay the boron injection and leave the operator ample time to take some other remedy actions for reactor safe shutdown.     

Techniques to derive additional information of operation actions for computer-based operating procedure

Most of the modern main control rooms of nuclear power plants are equipped with computer-based operating procedures (CBPs), which make it easier for operators to operate and control the reactor compared with paper-based operating procedure (PBP). However, most of the CBPs do not provide necessary information which is useful for operators, especially in an emergency situation. In addition, proper decisions and actions of the procedure steps are needed to prevent human errors in mitigating the accident. The additional information, which is the information of the impact of a counter action (by automatic system and human actions) such as the components influenced and future plant behavior will be very helpful for operators to understand the effects of the counter action. The aim of the study is to develop techniques to generate the additional information. Multilevel flow modeling (MFM) is applied to model a nuclear power plant and the counter actions described in CBPs. A simple emergency operating procedure of steam generator tube rupture accident of a pressurized water reactor (PWR) plant is used as a case study. The algorithm to generate the additional information is based on the influence propagation rules and cause–effect relations expressed in the MFM model of the PWR plant.     

大亚湾核电站停堆工况风险研究

基于传统ＰＳＡ方法学（适用于功率运行工况）及核电站停堆工况特征,提出了一套停堆ＰＳＡ特征方法,包括电站运行状态离散法,分阶段评价和主逻辑故障树评价。将该方法应用于大亚湾核电站（ＧＮＰＰ）停堆工况ＰＳＡ研究,得到了较真实反映ＧＮＰＰ实际情况的结果。研究结果对ＧＮＰＰ的停堆运行和管理有实际应用价值,以我国今后核电站设计、运行及管理也有现实意义。     

Human reliability analysis for operators in the digital main control rooms of nuclear power plants

ABSTRACT

As the main control room of nuclear power plants (NPPs) has been gradually digitized, new human reliability problems may emerge because of a series of new changes in the cognitive processes, behavioral patterns, and error mechanisms of operators. Aiming to address this situation, this paper proposes a method as guidance for human reliability analysis (HRA) of different cognitive Stages. This method first constructs the influencing factors of three cognitive processes, including monitoring, decision-making, and execution of actions, and then evaluates the weights of these influencing factors through an analytic hierarchy process (AHP). In this study, the parameters used in the proposed HRA method were determined by analyzing the test data obtained from a simulation model, and the results demonstrated the rationality and feasibility of the proposed method. A case example using this HRA method was given in which the human error probabilities at three stages in a nuclear power plant (NPP) steam generator tube ruptures (SGTR) accident were obtained. In summary, the proposed method is a simple and feasible HRA tool that can be applied in digital NPP main control rooms (MCRs).     

Guidelines for computerized presentation of emergency operating procedures

New methods of information presentation and interface design have changed the work conditions in the modern nuclear power plant control room. One area that is receiving considerable attention is that of procedures—in particular, emergency operating procedures (EOPs). Such procedures are traditionally available as printed documents; however, developments in information technology have created new opportunities for procedure presentation, and this paper reports on the development of human factor guidelines for computerized presentation of EOPs. After identifying the principle stages in the transition from procedures as documents to fully automated procedures, computerized procedure presentation (CPP) is briefly discussed. Guidelines for the presentation of such are outlined, starting with the high level goals that also constitute the criteria against which the computerized procedures are measured during implementation. Six dimensions that describe CPP are presented and explored in detail, by identifying points in each dimension that characterize different levels of information technology sophistication.     

Seismic protection technology for nuclear power plants: a systematic review

Seismic protection systems (SPS) have been developed and used successfully in conventional structures, but their applications in nuclear power plants (NPPs) are scarce. However, valuable research has been conducted worldwide to include SPS in nuclear engineering design. This study aims to provide a state-of-the-art review of SPS in nuclear engineering and to answer four significant research questions: (1) why are SPS not adopted in the nuclear industry and what issues have prevented their deployment? (2) what types of SPS are being considered in nuclear engineering research? (3) what are the strategies for location of SPS within NPPs? and (4) how may SPS provide improved structural performance and safety of NPPs under seismic actions? This review is conducted following the procedures of systematic reviews, where possible.

The issues concerning the use of SPS in NPPs are identified: cost, safety, licensing and scarcity of applications. NPPs demand full structural integrity and reactor's safe shutdown during earthquake actions. Therefore, horizontal isolation may be insufficient in active seismic zones and isolation in the vertical direction may be required. Based on the results in this review, it is likely that next generation reactors in seismic zones will include state-of-the-art SPS to achieve full standardised design.     

Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results.     

Quantum evolutionary algorithm applied to transient identification of a nuclear power plant

When transients occur during the operation of Nuclear Power Plants (NPPs), their identification is critically important for both operational and safety reasons. Thus, plant operators have to identify an event based upon the evaluation of several distinct process variables, which might difficult operators’ actions and decisions. Transient identification systems have been proposed in order to support the analysis with the aim of achieving successful or effective courses of action, as well as to reduce the time interval for a decision and corrective actions. This article presents a system for accident and transient identification in a pressurized water reactor NPP whose optimization step of the classification algorithm is based upon the paradigm of the Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and tested. The system is able to identify anomalous events related to transients of the time series of process variables related to postulated accidents. The results of the classification of transients/accidents are compared with other results in the literature.     

A post trip operational guidance system for BWR plants

A post trip operational guidance system (PTOG) for BWR power plants was developed to support the operators in achieving safe plant shutdown after a scram. The objective of PTOG is to support the operators in collecting plant information, in diagnosing plant status and in deciding corrective actions. To achieve this objective, PTOG has three main functions, i.e., the diagnosis of plant subsystems performance, the identification of safety functions status and the dynamic synthesis of operating procedures. The main advantage of PTOG is that it provides operating procedures irrespective of the transient's initiating event and evolutional history. The results of verification and validation tests showed that PTOG was a useful, effective and trustworthy vehicle in coping with abnormal plant conditions.     

A dynamic neural network based accident diagnosis advisory system for nuclear power plants

In this work, an accident diagnosis advisory system (ADAS) using neural networks is developed. In order to help the plant operators quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support systems and accident diagnosis systems have been developed. The ADAS is a kind of such accident diagnosis system, which makes the task of accident diagnosis easier, reduces errors, and eases the workload of operators by quickly suggesting likely accidents based on the highest probability of their occurrence. In order to perform better than other accident diagnosis systems, the ADAS has three main objectives. To satisfy these three objectives, two kinds of neural networks that consider time factors are used in this work. A simple accident diagnosis system is implemented in order to validate the ADAS. After training the prototype, several accident diagnoses were performed. The results show that the prototype can detect the accidents correctly with good performance.     

A technique to generate plausible counter-operation procedures for an emergency situation based on a model expressing functions of components

In large-scale engineering plants like nuclear power plants, various anomalies and accidents are usually predicted and efficient measures to minimize the damage from them have been implemented. However, when an unexpected anomaly or accident occurs, operators are asked to take flexible responsive actions to avoid its development to a catastrophic situation and to minimize the influence and damage by the accident. Considering the lessons learned from Fukushima Daiichi accidents, it is important to develop a system to support counter activities by operators and plant staff in an accidental plant condition that is not covered by emergency operating procedures prepared. The purpose of this study is to develop a technique for generating plausible operation procedures under such unexpected emergency situations. The multilevel flow modeling (MFM), a method to represent the functions of components and their relations, is applied as a framework to model functions of components. The technique uses some additional data and knowledge for deriving operation procedures. The applicability of the technique is confirmed by trial operation procedure generations for pressurized water reactor (PWR) loss-of-coolant accident cases with the conditions of some failures of safety systems.     

Transient identification in nuclear power plants: A review

A transient is defined as an event when a plant proceeds from a normal state to an abnormal state. In nuclear power plants (NPPs), recognizing the types of transients during early stages, for taking appropriate actions, is critical. Furthermore, classification of a novel transient as “don't know”, if it is not included within NPPs collected knowledge, is necessary. To fulfill these requirements, transient identification techniques as a method to recognize and to classify abnormal conditions are extensively used. The studies revealed that model-based methods are not suitable candidates for transient identification in NPPs. Hitherto, data-driven methods, especially artificial neural networks (ANN), and other soft computing techniques such as fuzzy logic, genetic algorithm (GA), particle swarm optimization (PSO), quantum evolutionary algorithm (QEA), expert systems are mostly investigated. Furthermore, other methods such as hidden Markov model (HMM), and support vector machines (SVM) are considered for transient identification in NPPs. By these modern techniques, NPPs safety, due to accidents recognition by symptoms rather than events, is improved. Transient identification is expected to become increasingly important as the next generation reactors being designed to operate for extended fuel cycles with less operators' oversight. In this paper, recent studies related to the advanced techniques for transient identification in NPPs are presented and their differences are illustrated.     

核电站计算机化规程显示技术分析

分析了传统规程的缺点,详细介绍了核电站计算机化规程显示的特征,强调了计算机化规程系统评估的重要性,主要对操纵员的任务、规程的显示格式、人机界面的改进进行了说明.合理的运用人为因素知识、指导和技术能避免许多与计算机化规程相关的潜在缺陷.对计算机化规程系统的评估措施将促进操纵员支持系统的发展,得到的经验和教训也适用于其他电站支持系统.     

An efficient Neuro-Fuzzy approach to nuclear power plant transient identification

Transient identification in nuclear power plants (NPP) is often a computational very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Recently, several works have been developed for transient identification. These works frequently present a non reliable response, using the “don´t know” as the system output. In this work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A validation of this identification system was made at the three loops Pressurized Water Reactor (PWR) simulator of the Human-System Interface Laboratory (LABIHS) of the Nuclear Engineering Institute (IEN/CNEN/Brazil). The obtained results show the potential of this new transient identification system to be used in an operational NPP in order to assist the operators to take decisions during transients/accidents.     

Evaluation of operators’ mental workload of human–system interface automation in the advanced nuclear power plants

It has been expected that the automation of certain tasks in a control room would help decrease operators’ mental workload, enhance situation awareness, and improve the whole system performance. However, there have been too many automation-induced system failures that would warrant a fresh look on the influences of automation. Automation problems include the reduction in the operator's system awareness, an increase in monitoring workload, and the degradation in manual skills. This study evaluates operators’ mental workload and system performance during a human–system interface (HSI) automation in an advanced nuclear power plant (NPP). The reactor shutdown task and alarm reset task simulations were conducted in this study to evaluate operators’ mental workload and performance. The results of this study indicated that for ensuring safe operating in NPPs, the design of automation needs to be carefully implemented. Task characteristics and degrees of automation should be carefully evaluated while designing HSIs. The reactor shutdown tasks studied in this paper suggest that a high level of automation design for the long period and low workload would be sufficient. On the other hand, the degree of automation of alarm reset task does not show a significant difference to the operator's mental workload. In conclusion, the human–system interface automation in advanced NPPs is suggested to be more flexible and needs to be continually improved.