Safety Systems Of Nuclear Power Plants Research Articles

Establishing operator trust in machine learning for enhanced reliability and safety in nuclear Power Plants

The advancement of safety and reliability in Nuclear Power Plants (NPP) is essential for ensuring the protection of human life, the environment, and the sustainable use of clean energy. The key factor to achieve this goal is enhancing operator performance, as their decisions play a crucial role during reactor accidents. In this sense, the integration of artificial intelligence (AI) with safety systems in NPP could provide suggestions and recommendations to the operator, leading to a quick and accurate response. However, the complexity of models like Convolutional Neural Networks (CNN), often considered as black boxes, presents challenges for operators to comprehend the decision-making process. This difficulty leads to a lack of trust in the model's output. Therefore, ensuring algorithm transparency becomes crucial to maintain a positive relationship between humans and AI technology. In this study, the necessary data were collected through the automation technique implemented in the (PCTRAN) software. Subsequently, CNN was employed to classify various design-based accidents (DBA), accompanied by transfer learning to optimize accuracy. Finally, Shapley Additive Explanation (SHAP) was used to provide outcome explainability. The results show the effectiveness of automation in reducing time consumption and optimizing hardware resource utilization. Among the pre-trained models, MobileNet exhibits superior performance by requiring a smaller dataset and less time, achieving the highest accuracy, and demonstrating an optimal balance of (correct and incorrect) data prediction within the classes. Furthermore, the use of Explainable AI (XAI) provides result transparency and clarifies the reasons behind CNN incorrect predictions.

원전의 안전계통 설정치 불확도 평가에서의 중심극한정리 타당성 확인

In evaluating the uncertainty of nuclear power plant safety system setpoints, the central limit theorem(CLT) is often used when combining the uncertainties of each element. However, depending on the distribution characteristics of individual elements and the number of elements to be combined, there are cases where the central limit theorem cannot be applied. International standards are being revised to reflect this. In this paper, we describe various methodologies for calculating safety system setpoints and confirm whether the combined components follow the central limit theorem according to the distribution characteristics of the individual elements. The Monte Carlo simulation method is used as a basic tool to confirm this, and normality is verified using KS test in Python program library. Additionally, the variance characteristics of each distribution are examined and differences from the uniform distribution are analyzed. As a result of the analysis, in order for the combined component to follow the central limit theorem, if the distribution is concentrated on both sides compared to the uniform distribution, the number of input variables needs to be four or more. That is, when the number of input element uncertainty of the safety system setpoint exceeds 4, the combined uncertainty was evaluated to have normality regardless of the distribution of input element uncertainty. Therefore, it was confirmed that the method of applying CLT to calculate the coverage factor and then using it to obtain the expanded uncertainty was valid. In the case of a distribution concentrated toward the center compared to a uniform distribution, the number of variables less than 3 was required. The U type distribution, which is used to evaluate the uncertainty of wireless communication, showed characteristics closer to a uniform distribution than an inverted triangular distribution. Also, in the case of variance, it was found that the variance of the uniform distribution was larger than that of the linear distribution, confirming that this conformed to the maximum entropy principle.

Event Sequence Based Fault Tree Analysis to Evaluate Minimal Combination of Event Sequences Leading to the Reactor Core Damage

Probabilistic safety assessment has been widely used to evaluate nuclear power plant safety systems. It couples fault tree (FT) analysis and event tree (ET) analysis. FT analysis is to develop failure scenarios, to quantify the failure probability and to identify critical components. ET analysis is to develop event sequences (ESs) leading to reactor core damage and quantify core damage frequency. Currently, there is no approach in probabilistic safety assessment that can be used to identify minimal combinations of safety system failures leading to reactor core damage. This study proposes an event sequence based fault tree analysis, which integrates FT model with ET model. The ET model is to identify the ESs leading to the reactor core damage. Meanwhile, the FT model is to identify minimal combinations of those ESs found in the ET model. The motivation of this study is on how to identify critical safety systems in nuclear power plants to mitigate disturbances caused by a group of postulated initiating events to avoid core damage. To confirm the feasibility and the applicability of the proposed approach, the performance of the AP1000 passive core cooling system is evaluated. It is found that if in-containment refueling water storage tank, automatic depressurization system - full, accumulator, core make-up tank, and passive residual heat removal work properly, the reactor core will intact. These results confirmed that the proposed approach can be applicable to identify minimal combinations of safety systems to keep the reactor core intact.

Uncertainty Study of the In-Vessel Phase of a Severe Accident in a Pressurized Water Reactor

A comprehensive uncertainty analysis in the event of a severe accident in a two-loop pressurized water reactor is conducted using an uncertainty package integrated in the ASYST code. The plant model is based on the nuclear power plant (NPP) Krško, a Westinghouse-type power plant. The station blackout scenario with a small break loss of coolant accident is analyzed, and all processes of the in-vessel phase are covered. A best estimate plus uncertainty (BEPU) methodology with probabilistic propagation of input uncertainty is used. The uncertain parameters are selected based on their impact on the safety criteria, the operation of the NPP safety systems and to describe uncertainties in the initial and boundary conditions. The number of required calculations is determined by the Wilks formula from the desired percentile and confidence level, and the values of the uncertain parameters are randomly sampled according to appropriate distribution functions. Results showing the thermal hydraulic behaviour of the primary system and the propagation of core degradation are presented for 124 successful calculations, which is the minimum number of required calculations to estimate a 95/95 tolerance limit at the 3rd order of the Wilks formula application. A statistical analysis of the dispersion of results is performed afterwards. Calculation of the influence measures shows a strong correlation between the decay heat and the representative output quantities, which are the mass of hydrogen produced during the oxidation and the height of molten material in the lower head. As the decay heat increases, an increase in the production of hydrogen and the amount of molten material is clearly observed. The correlation is weak for other input uncertain parameters representing physical phenomena, initial and boundary conditions. The influence of the order of the Wilks formula is investigated and it is found that increasing the number of calculations does not significantly change the bounding values or the distribution of results for this particular application.

A Dialogic Perspective on Managing Knowledge Differences: Problem-solving while building a nuclear power plant safety system

To manage knowledge differences, existing research has documented two sets of practices: traversing and transcending knowledge boundaries. What research has yet to explore, however, is the dynamics through which traversing or transcending practices emerge in response to a particular problem situation. Using a qualitative, inductive study of the problem episodes encountered by groups of experts working on a large-scale project to build the safety system for a nuclear power plant, we observed that the emergence of traversing or transcending depended on how experts interpreted problems and initiated dialogues around specific problems. Our work provides insight into the condition through which knowledge integration trajectories may emerge.

Dynamic Reliability Evaluation of Diesel Generator System of One Chinese 1000MWe NPP Considering Temporal Failure Effects

Loss of power supply from the diesel generator system (DGS) after loss of offsite power (LOOP) will pose great threat to the safety of GEN-II pressurized water reactors (PWR). Therefore, it is very desirable to evaluate the DGS’s reliability. The traditional analyzing tools are limited to static approaches neglecting the dynamic sequence failure behaviors, such as reliability block diagram (RBD), static fault tree (SFT). Static reliability modeling techniques are not capable of capturing the dynamic sequence-dependent failure behaviors typically existing in NPP safety systems such as DGS, and thus often overestimate the unreliability of systems. In this paper, motivated to study the effects of sequence failure behaviors, dynamic fault tree (DFT) is applied to evaluate the reliability of the DGS of one Chinese 1000MWe Nuclear Power Plant (NPP), and an integrated two-phased Markov Chain model is also developed, which can be considered as a contribution of this article. Comparative study of DGS reliability between DFT and SFT is carried out. The results indicate that compared with the result derived from the DFT model, the unreliability of DGS calculated by SFT is greatly overestimated by about one to two orders of magnitude. Therefore, DFT has a potential to improve the economy of NPP by relaxing the overestimated unreliability of nuclear power systems.

Cost- and Risk-Based Seismic Design Optimization of Nuclear Power Plant Safety Systems

Seismic analysis, design, and qualification of systems, structures, and components (SSCs) is a significant contributor to the capital cost of a nuclear power plant. To reduce capital costs of advanced nuclear power plants and make commercial nuclear energy more competitive, innovations are needed in their structural design and construction, and not just in the reactor core and associated systems. Seismic isolation has been identified as an important cost-cutting technology that enables standardization of equipment across various sites. This paper develops and demonstrates a cost- and risk-based seismic design optimization of a representative safety system in a nuclear power plant with the dual goals of minimizing overnight capital cost and meeting safety goals. The design optimization can also include component seismic isolation, in which case, the optimized design includes a set of equipment that needs to be seismically isolated to minimize capital cost. The open-source codes MASTODON and Dakota are used for seismic probabilistic risk assessment and design optimization, respectively. A generic nuclear facility with a safety system comprising SSCs that are common to nuclear power plants is considered for the demonstration of the design optimization and is assumed to be located at the Idaho National Laboratory site. Generic costs and seismic design cost functions are assumed for the SSCs of the safety system. The sum of the costs of the SSCs is minimized in the optimization process, while the risk of failure of the safety system is provided as a constraint. Results show that the optimization process reduces capital costs significantly while automatically prioritizing the safety of SSCs that contribute most to the risk of the safety system.

Dynamic fault tree analysis of auxiliary feedwater system in a pressurized water reactor

Abstract The safe and secure designs of any nuclear power plant together with its cost-effective operation without accidents are leading the future of nuclear energy. As a result, the Reliability, Availability, Maintainability, and Safety analysis of NPP systems is the main concern for the nuclear industry. But the ability to assure that the safety-related system, structure, and components could meet the safety functions in different events to prevent the reactor core damage requires new reliability analysis methods and techniques. The Fault Tree Analysis (FTA) is one of the most widely used logic and probabilistic techniques in system reliability assessment nowadays. The Dynamic fault tree technique extends the conventional static fault tree (SFT) by considering the time requirements to model and evaluate the nuclear power plant safety systems. Thus this paper focuses on developing a new Dynamic Fault Tree for the Auxiliary Feed-water System (AFWS) in a pressurized water reactor. The proposed dynamic model achieves a more realistic and accurate representation of the AFWS safety analysis by illustrating the complex failure mechanisms including interrelated dependencies and Common Cause Failure (CCF). A Simulation tool is used to simulate the proposed dynamic fault tree model of the AFWS for the quantitative analysis. The more realistic results are useful to establish reliability cantered maintenance program in which the maintenance requirements are determined based on the achievement of system reliability goals in the most cost-effective manner.

Performance evaluation of a Terry GS-2 steam impulse turbine with air-water mixtures

• A Terry GS-2 turbine was tested under gas mass fractions from 1.00 to 0.05. • Terry turbine performance degrades with decreasing gas mass fraction. • Results demonstrate capabilities for extended use in nuclear plant systems. Terry steam turbines are widely used in various industries because of their robust design. Within the nuclear power generation industry, they are used in the Reactor Core Isolation Cooling System to remove decay heat during reactor isolation events. During the Fukushima Daiichi nuclear power station disaster in Japan in 2011, the Reactor Core Isolation Cooling System and associated Terry turbine operated for over 70 hours in Unit 2; this runtime is well beyond the expected operating duration. Theories suggest the turbine was subjected to a two-phase inlet flow, which could degrade the turbine performance. In this work, an experimental test rig was constructed to test a full-scale Terry model GS-2 steam turbine under two-phase air/water flows. Steady-state efficiency and torque performance maps of the turbine were developed over a range of turbine inlet pressures (1.38–4.83 bar or 20–70 psia), air mass fractions (0.05–1.0) and rotational speeds up to 4000 RPM. Turbine performance followed expected trends with torque varying linearly and efficiency varying quadratically with rotational speed. In addition, high-speed images of the two-phase flow entering the turbine were also analyzed to understand how changes in inlet pressure and air mass fraction affect the flow regime and homogenization. The present tests with air–water two-phase mixtures are an important step towards providing an understanding of the full-scale Terry turbine’s behavior and performance curves under two-phase conditions. The results of this work will be combined with air/water and steam/water data gathered using a small-scale Terry ZS-1 steam turbine in order to understand the scaling relationship between large and small size Terry turbines and fluid pairs. The combined data set will enable further development of analytical models over a wide range of conditions and may be used to provide technical justification for expanded use of the Terry turbines in nuclear power plant safety systems and other systems.

Developing Digital Instrumentation and Control System for Experimental Power Reactor by Following IEEE Std 1012 −2004 to be Verified and Validated

We will develop the Experimental Power Reactor of Indonesia (RDE), by adopting the HTR-10 type from Tsinghua University-China. The–Instrumentation and Control (I&C) for RDE will developed with digital system technology which in the development process will have verification, validation, design and implementation, reviews, and audits for digital computer software activities. Software design for I&C system of Nuclear Power Plant (NPP) should be started by developing software requirement specification (SRS) to meet the requirement that systems and components should be designed, fabricated, erected, tested, and inspected. In the regulatory structure of developing nuclear power plant in Indonesia, BAPETEN also concern for the design development of important to safety with computer based system for nuclear power plant (NPP) by PERKA BAPETEN No.6 in 2012. Since BAPETEN did not state which standards should be use, we can refer to the standards that are commonly used globally. IEEE Std 1012™-2004 is recommended by the latest US. Nuclear Regulatory Commission Guide 1.168 in 2013 about verification, validation, reviews, and audits for digital computer software used in safety systems of NPP. This guide also recommends IEEE Std 279, “Criteria for Protection Systems for Nuclear Power Generating Stations,” or in IEEE Std 603-1991, “Criteria for Safety Systems for Nuclear Power Generating Stations. In this research we will examine the recommendation activity that should be follow to meet the requirement of the regulatory body which is also covered in IEEE Std 1012-2004. Developing traceability analysis in the first activity will help the designer to trace the requirement to meet the design criteria and reach the effectiveness and performance of the I&C system. By tracing from the top tier recommendation, it will help the development I&C system of RDE to be verified and validate as the design criteria for HTR-10

A Numerical Study on the Transient Response of VVER-1200 Plant Parameters during a Large-break Loss of Coolant Accident

Objectives: To study the transient response of a VVER-1200 based nuclear power plant parameters and safety systems during a Large-break Loss of Coolant Accident (LBLOCA) for two distinct cases; one in which SCRAM is initiated and the other one in which SCRAM is not initiated due to malfunction of the system. Method: Personal Computer Transient Analyzer (PCTRAN) has been used to obtain transient response of the plant for 300 seconds during these accidents. A break of 0.1 m2 size in the hot leg of the primary coolant circuit has been considered in this work. It has also been assumed that off-site AC power supply is completely cut-off for both cases. Findings: Results show that for Loss of Coolant Accident followed by SCRAM, core thermal power drops to only 5% of the normal operating power within 5seconds. The peak fuel and cladding temperature is recorded to be slightly higher than 1800o C and 610o C respectively, showing no failure for any of the two. Maximum pressures inside reactor core structure and reactor containment building are recorded to be 162 bar and 3.5 bar respectively, which are within design limits. However, for Loss of Coolant Accident with no SCRAM, core thermal power is recorded to be around 80% of the normal operating value after 300 seconds. Peak fuel and cladding temperatures are recorded to be around 2100o C and 650o C respectively, low enough to avoid failure. Maximum pressure inside reactor core structure is recorded to be 162 bar but pressure inside containment building has risen to around 13.5 bar after 300 seconds time. Applications: PCTRAN is one of the most reliable simulation tools for analyzing a nuclear facility. The results obtained from this study may be used as a reference for designing different components and safety systems of VVER-1200 based nuclear power plants so that the risk of a severe accident is minimized. Keywords: Loss of Coolant Accident, Safety Systems, Transient Response, VVER-1200

Gray wolf optimizer approach to the reliability‐cost optimization of residual heat removal system of a nuclear power plant safety system

AbstractTo ensure the safety of nuclear power plants (NPPs), nuclear regulatory agencies set technical specifications (TSs). TSs define the safety‐related operational measures and specify essential requirements and set specific limitations that is necessarily be followed by a nuclear industry to meet the requirements for the safety of an NPP. One of the important bases for the setting of TSs is the estimates of the availability and reliability of various systems and costs associated with an NPP. In this work, authors have presented a framework based upon a hodiernal nature‐inspired metaheuristic called multiobjective gray wolf optimizer (MOGWO) algorithm, which mimic the hierarchal and hunting behavior of gray wolves (Canis lupus), for technical specifications optimization of residual heat removal system (RHRS) of an NPP safety system. The efficiency of MOGWO in optimizing the TSs is demonstrated by comparing its results with a very popular swarm‐based optimization technique named multiobjective particle swarm optimization (MOPSO).

Simulation of SB-LOCA of typical PWR with MELCOR code

Safety of Nuclear Power Plants (NPPs) is one of the main issues in nuclear industry mainly because of the probability of radionuclides release to the environment. Due to this fact nuclear safety is continuously being improved by vendors to face the growing demands especially after the accident in Fukushima. This accident because of its character (station blackout scenario) resulted in putting more emphasis than ever on passive safety systems in NPPs. Such systems are one of main focus points in presented simulation. One of the ways to improve NPPs’ safety and check its robustness is to proceed simulations of different events and find the weakest points inside the system. First thing is to create simulation model of NPP which has to be validated in order to prove reliability of future results. This paper presents simulation run of design basis accident for large PWR reactor based on AP1000. Model was developed using publicly available data only, which means that it should be considered only as “AP1000-like model”. MELCOR code which was used in presented calculations is a severe accident code which simulates core melting during the worst possible accidents in NPP. Here it was decided to simulate design basis accident namely small break loss of coolant accident (SB-LOCA) and compare obtained results with those from the safety reports. Main motivation to create such simulation was to increase authors’ knowledge about MELCOR behaviour and sensitivity in case of thermal hydraulic response to learn what kind of errors and uncertainty could be expect. Second motivation was to check if Melcor is capable to simulate design basis accident with acceptable results. Finally the obtained results are in relatively good agreement with the expectations and some differences that have appeared do not affect general course of the accident. Shape of transient curves and timing of events are reasonable correct.

Research on High Reliability Power Supply Design Scheme of Nuclear Power Plant

After the Fukushima nuclear accident, the reliability requirements for Nuclear Power Plant (NPP) safety systems have been further improved worldwide. Therefore, it is necessary to provide a safe, reliable and economical scheme of the power supply system to cope with the abnormal conditions. Based on the reliability of the power supply of the 3rd generations of NPPs and combined with the application of the defend in depth concept in the electrical system, this paper provides a brief introduction of the typical 3rd generation NPP electrical system in the following area: the configuration of the electrical power system, defence in depth principle of the power supply, the basic structure of electrical power system. On this basis, an optimal power supply scheme is proposed.

The Implementation of Importance Measure Approaches for Criticality Analysis in Fault Tree Analysis: A Review

THE IMPLEMENTATION OF IMPORTANCE MEASURE APPROACHES FOR CRITICALITY ANALYSIS IN FAULT TREE ANALYSIS: A REVIEW.Fault tree analysis (FTA) has been widely applied in nuclear power plant (NPP) probabilistic safety assessment to evaluate the reliability of a safety system. In FTA, criticality analysis is performed to identify the weakest paths in the system designs and components. For this purpose, an importance measure approach can be applied. Risk managers can apply information obtained from this analysis to improve safety by implementing risk reduction measure into the new design or build a more innovative design. Various importance measure approaches have been developed and proposed for criticality analysis in FTA. Each important measure approach offers specific purposes and advantages but has limitations. Therefore, it is necessary to understand characteristics of each approach in order to select the most appropriate approach to reach the purpose of the study. The objective of this study is to review the current implementations of importance measure approaches to rank individual basic events and/or minimal cut sets regarding their contributions to the unreliability or unavailability of NPP safety systems. This study classified importance measure approaches into two groups, i.e. probability–based importance measure approaches and fuzzy–based importance measure approaches. This study concluded that clear understanding of the purpose of the study, the type of reliability data at hands, and the uncertainty in the calculation need to be considered prior to the selection of the appropriate importance measure approach to the study of interest.

Harmonization of IEEE 1012 and IEC 60880 standards regarding verification and validation of nuclear power plant safety systems software using model-based methodology

This paper compares two standards, namely IEC 60880 and IEEE 1012, and defines a harmonized core amongst them with regard to their verification and validation processes for the nuclear power plant instrumentation and control safety system software. The problem of harmonizing standards requires a transparent representation of standards in order to make comparison possible. A model-based methodology using SysML is used to establish this transparency. Transformation rules are a crucial part of the methodology. These enable the natural language used in a standard to be translated into structural and behavioural models in SysML. Due to the high level of ambiguity of natural language, certainty definition rules for objects and operations are established as well. The result is a rigorously developed harmonized core that is traceable to the parent standards. The core developed using our methodology supports the argument that there is no one-to-one mapping between major IEEE and IEC standards. Nevertheless, some intersections between them do exist, which support the opinion of other experts. The extent of the harmonization depends on the conformance or traceability. The methodology also offers promise to address the challenge of establishing a harmonized core and the formal transferability between future standards.

ADS-IRWST transient evaluation model for AP1000 SBLOCA analysis

The AP1000 nuclear power plant safety system is characterized by its unique passive Emergency Core Cooling System (ECCS), including Core Makeup Tanks (CMTs), Automatic Depressurization System (ADS), and In-containment Refueling Water Tank (IRWST), to mitigate SBLOCA accident. The most challenging period of AP1000 SBLOCA transient is the transition from CMT injection to IRWST injection after the actuation of the fourth stage ADS (ADS4). This paper is to report a transient evaluation model for AP1000 SBLOCA analysis during CMT to IRWST transition. The model simulates ADS4, CMT injection, IRWST injection, reactor core mixture level and upper plenum entrainment to hotlegs. Both critical and non-critical flow models are used to calculate mass flow loss through ADS1-4 vents. The most important feature of this model is that it constantly traces core/upper plenum two-phase mixture level, which demonstrates cooling capability of ECCS during the transient. A baseline case is analyzed to study the ADS-IRWST transient using AP1000 prototypic information. In addition, a sensitivity analysis is performed to further study the robustness of AP1000 ECCS during SBLOCA transient.

Risk-Based Allowed Outage Time and Surveillance Test Interval Extensions for Angra 1

In this work, Probabilistic Safety Assessment (PSA) is used to evaluate Allowed Outage Times (AOT) and Surveillance Test Intervals (STI) extensions for three Angra 1 nuclear power plant safety systems. The interest in such an analysis lies on the fact that PSA comprises a risk-based tool for safety evaluation and has been increasingly applied to support both the regulatory and the operational decision-making processes. Regarding Angra 1, among other applications, PSA is meant to be an additional method that can be used by the utility to justify Technical Specification relaxation to the Brazilian regulatory body. The risk measure used in this work is the Core Damage Frequency, obtained from the Angra 1 Level 1 PSA study. AOT and STI extensions are evaluated for the Safety Injection, Service Water and Auxiliary Feedwater Systems using the SAPHIRE code. In order to compensate for the risk increase caused by the extensions, compensatory measures as (1) test of redundant train prior to entering maintenance and (2) staggered test strategy are proposed. Results have shown that the proposed AOT extensions are acceptable for two of the systems with the implementation of compensatory measures whereas STI extensions are acceptable for all three systems.

Particle Swarm Optimization of safety components and systems of nuclear power plants under uncertain maintenance planning

Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it, and can be formulated in terms of a multi-objective optimization problem where reliability, availability, maintainability and cost act as decision criteria and surveillance test and maintenance strategies act as decision variables. Usually, the frequency of performing a maintenance task is considered, in the optimization process, as a constant value but a certain range of variation from such value is observed in real practice. Thus, to obtain a more realistic approach, a certain degree of uncertainty should be considered in the decision variables. This paper presents two examples of maintenance optimization using Particle Swarm as optimization technique and a tolerance interval based approach to address uncertainty, one is focused on a safety component and the other considers a nuclear power plant safety system.

Fuzzy uncertainty modeling applied to AP1000 nuclear power plant LOCA

This article presents an uncertainty modeling study using a fuzzy approach applied to the Westinghouse advanced nuclear reactor. The AP1000 Westinghouse Nuclear Power Plant (NPP) is provided of passive safety systems, based on thermo physics phenomenon, that require no operating actions, soon after an incident has been detected. The use of advanced passive safety systems in NPP has limited operational experience. As it occurs in any reliability study, statistically non-significant events report introduces a significant uncertainty level about the failure rates and basic events probabilities used on the fault tree analysis (FTA). In order to model this uncertainty, a fuzzy approach was employed to reliability analysis of the AP1000 large break Loss of Coolant Accident (LOCA). The final results have revealed that the proposed approach may be successfully applied to modeling of uncertainties in safety studies.