scholarly journals Application of Data Mining Techniques for Sensor Drift Analysis to Optimize Nuclear Power Plant Performance

2019 ◽  
Vol 9 (1) ◽  
pp. 3087-3095
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Response Times ◽  
Protective Action ◽  
Plant Performance ◽  
Data Mining Techniques ◽  
Prime Concern

The Power Plants are engineered and instrumented to ensure safety in all modes of operation. Hence they should be continuously monitored and maintained with necessary Instrumentation to identify performance degradation and the root causes to avoid calling for frequent maintenance. The degraded performance of Instrumentation & Control systems may also lead to plant outages. Different studies have suggested that a well maintained instrumentation with errors and response times within the permissible limits may increase the availability minimizing outages. The I&C systems are designed for monitoring, control and safety actions in case of an event in a power plant. The sensors used are single, redundant, triplicated or diverse based on the type of application. Where safety is of prime concern, triplicated and 2/3 voting logic is employed for initiating safety actions. Diverse instruments are provided for protecting the plant from any single abnormal event. Redundant sensors are used to improve plant availability. Wherever 2/3 logics are used, the sensors shall uniformly behave and the drifts across the sensor may lead to crossing the threshold, initiating a protective action. Instead of waiting for the regular preventive maintenance schedule for recalibrating the sensors, the drift in the sensors are analyzed by developing a combined overall online monitoring parameter which will give an early warning to the operator the need for recalibration of the redundant sensors. This paper deals with development of one such parameter through data mining techniques for a representative process in a nuclear power plant.

scholarly journals Study of the Characteristics of Wind over Nuclear Power Plants in Korea

2021 ◽  
Vol 21 (1) ◽  
pp. 57-70
Author(s):  
Su-Bin Oh ◽  
Chun-Ji Kim ◽  
Sang-Hyun Lee ◽  
Hyun-Ha Lee ◽  
Chun-Sil Jin ◽  
...  
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Protective Action ◽  
Radioactive Materials ◽  
Sea Breezes ◽  
Wind Characteristics ◽  
And Diffusion

To establish a strategy for public protective action from radioactive leakage in the event of Nuclear Power Plant (NPP) accidents, long-term records of wind data collected at the Korean NPPs were analyzed. Wind characteristics related to the advection and diffusion of radioactive pollutants were examined by analyzing the wind direction, speed, and land-sea breezes for NPPs (Hanbit, Hanul, Wolsong, Kori, and Shin-Kori) in Korea. The study also analyzed the characteristics of calm winds causing the accumulation of radioactive materials. The wind characteristics of each NPP differ depending on the seasonal and daily variabilities; thus, a detailed time-scaled airflow database is required. In addition, the findings, through continuous updates of the airflow database, will contribute to improving preparedness.

scholarly journals Characteristics and recognition of guardians living in the urgent protective action planning zone of the Genkai Nuclear Power Plant, Saga Prefecture, Japan who wished to receive pre-distribution stable iodine for their children

2021 ◽  
Author(s):  
Hitomi Matsunaga ◽  
Makiko Orita ◽  
Yasuyuki Taira ◽  
Noboru Takamura
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Radiation Exposure ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Protective Action ◽  
Action Planning ◽  
To Receive ◽  
Stable Iodine

Abstract Purpose：The aim of this study was to clarify the characteristics and the awareness of nuclear prevention measures including prophylactic stable iodine (SI) of guardians of 0- to 6-year-old children living in the urgent protective action planning zone (UPZ) of the Genkai Nuclear Power Plant (GNPP), Japan. Methods：Of these 1172 guardians, 973 responded that they wished to receive pre-distribution of stable iodine (PDSI) and 199 did not wish to receive PDSI. Results: Logistic regression analysis showed that the following items were independently associated with guardians who wished to receive PDSI for their children: thinking that pregnant women should take prophylactic SI (odds ratio [OR]=6.57, 95% confidence interval [CI]: 4.62–9.35; p<0.01); wishing to participate in a lecture about the health effects of radiation exposure (OR=1.99, 95%CI: 1.40–2.82; p<0.01); thinking that SI can prevent exposure from all radionuclides (OR=1.93, 95%CI: 1.24–2.99; p<0.01); awareness of SI before the study (OR=1.91, 95%CI: 1.35–3.00; p<0.01); and anxiety about prophylactic SI for their children (OR=0.33, 95%CI: 0.20–0.55; p<0.01). The GNPP was one of the nuclear power plants in Japan that resumed operations after the Fukushima Dai-ichi Nuclear Power Plant accident in 2011. Conclusion: These results suggest that some residents have incomplete knowledge about nuclear prevention, including SI. Therefore, it is essential to educate residents and communicate the health risks of radiation exposure with residents living around nuclear power plants. Furthermore, it is important to train specialists to educate and communicate with residents to prepare for a nuclear accident.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Human Factors ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Cooling System ◽  
Human Reliability ◽  
Non Destructive ◽  
Plant Components

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.

scholarly journals Data Driven Modelling of Nuclear Power Plant Performance Data as Finite State Machines

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 43-62
Author(s):  
Kshirasagar Naik ◽  
Mahesh D. Pandey ◽  
Anannya Panda ◽  
Abdurhman Albasir ◽  
Kunal Taneja
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Finite State Machine ◽  
State Machine ◽  
Plant Performance ◽  
Series Data ◽  
Cyberphysical Systems ◽  
Finite State ◽  
Machine Representation

Accurate modelling and simulation of a nuclear power plant are important factors in the strategic planning and maintenance of the plant. Several nonlinearities and multivariable couplings are associated with real-world plants. Therefore, it is quite challenging to model such cyberphysical systems using conventional mathematical equations. A visual analytics approach which addresses these limitations and models both short term as well as long term behaviour of the system is introduced. Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) is used to extract features from the data, k-means clustering is applied to label the data instances. Finite state machine representation formulated from the clustered data is then used to model the behaviour of cyberphysical systems using system states and state transitions. In this paper, the indicated methodology is deployed over time-series data collected from a nuclear power plant for nine years. It is observed that this approach of combining the machine learning principles with the finite state machine capabilities facilitates feature exploration, visual analysis, pattern discovery, and effective modelling of nuclear power plant data. In addition, finite state machine representation supports identification of normal and abnormal operation of the plant, thereby suggesting that the given approach captures the anomalous behaviour of the plant.

scholarly journals Python TensorFlow Big Data Analysis for the Security of Korean Nuclear Power Plants

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1467
Author(s):  
Sangdo Lee ◽  
Jun-Ho Huh ◽  
Yonghoon Kim
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Network Traffic ◽  
Nuclear Power ◽  
Power Plants ◽  
Security Requirements ◽  
Republic Of Korea ◽  
Continuous Data ◽  
Cyber Attack ◽  
The Republic

The Republic of Korea also suffered direct and indirect damages from the Fukushima nuclear accident in Japan and realized the significance of security due to the cyber-threat to the Republic of Korea Hydro and Nuclear Power Co., Ltd. With such matters in mind, this study sought to suggest a measure for improving security in the nuclear power plant. Based on overseas cyber-attack cases and attacking scenario on the control facility of the nuclear power plant, the study designed and proposed a nuclear power plant control network traffic analysis system that satisfies the security requirements and in-depth defense strategy. To enhance the security of the nuclear power plant, the study collected data such as internet provided to the control facilities, network traffic of intranet, and security equipment events and compared and verified them with machine learning analysis. After measuring the accuracy and time, the study proposed the most suitable analysis algorithm for the power plant in order to realize power plant security that facilitates real-time detection and response in the event of a cyber-attack. In this paper, we learned how to apply data for multiple servers and apply various security information as data in the security application using logs, and match with regard to application of character data such as file names. We improved by applying gender, and we converted to continuous data by resetting based on the risk of non-continuous data, and two optimization algorithms were applied to solve the problem of overfitting. Therefore, we think that there will be a contribution in the connection experiment of the data decision part and the optimization algorithm to learn the security data.

Transition to Online Cable Insulation Condition Monitoring

2021 ◽  
Author(s):  
S. W. Glass ◽  
Leonard S. Fifield ◽  
Mychal P. Spencer
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Management Program ◽  
Capacitance Measurement ◽  
Test Bed ◽  
Test Environment ◽  
Specific Test ◽  
Motor Test

Abstract Nuclear power plant cables were originally qualified for 40 year life and generally have not required specific test verification to assure service availability through the initial plant qualification period. However, license renewals to 60 and 80 years of operation require a cable aging management program that depends on some form of test and verification to assure fitness for service. Environmental stress (temperature, radiation, chemicals, water, and mechanical) varies dramatically within a nuclear power plant and, in some cases, cables have degraded and required repair or replacement before their qualified end-of-life period. In other cases, cable conditions have been mild and dependable cable performance confirmed to extend well beyond the initial qualified life. Most offline performance-based testing requires cables to be decoupled and de-energized for specially trained technicians to perform testing. These offline tests constitute an expensive operational burden that limits the economic viability of nuclear power plants. Although initial investment may be higher, new online test practices are emerging as options or complements to offline testing that avoid or minimize the regularly scheduled offline test burden. These online methods include electrical and fiber-optic partial discharge measurement, spread spectrum time or frequency domain reflectometry, distributed temperature profile measurements, and local interdigital capacitance measurement of insulation characteristics. Introduction of these methods must be supported by research to confirm efficacy plus either publicly financed or market driven investment to support the start-up expense of cost-effective instrumentation to monitor cable condition and assure reliable operation. This work summarizes various online cable assessment technologies plus introduces a new cable motor test bed to assess some of these technologies in a controlled test environment.

Research on Earthquake Acceleration Alarm of Nuclear Power Plant

2021 ◽  
Author(s):  
Li Liang ◽  
Pan Rong ◽  
Ren Guopeng ◽  
Zhu Xiuyun
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
False Alarm ◽  
Ground Motion ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Time History ◽  
Seismic Acceleration ◽  
Trigger Signal

Abstract Almost all nuclear power plants in the world are equipped with seismic instrument system, especially the third generation nuclear power plants in China. When the ground motion measured by four time history accelerometers of containment foundation exceeds the preset threshold, the automatic shutdown trigger signal will be generated. However, from the seismic acceleration characteristics, isolated and prominent single high frequency will be generated the acceleration peak, which has no decisive effect on the seismic response, may cause false alarm, which has a certain impact on the smooth operation of nuclear power plant. According to the principle of three elements of ground motion, this paper puts forward a method that first selects the filtering frequency band which accords with the structural characteristics of nuclear power plants, then synthesizes the three axial acceleration time history, and finally selects the appropriate acceleration peak value for threshold alarm. The results show that the seismic acceleration results obtained by this method can well represent the actual magnitude of acceleration, and can solve the problem of false alarm due to the randomness of single seismic wave, and can be used for automatic reactor shutdown trigger signal of seismic acceleration.

A Quantitative Approach for Reliability Evaluation of Safety I&C Systems in Nuclear Power Plants

2017 ◽  
Author(s):  
Liu Dongxu ◽  
Xu Dongling ◽  
Zhang Shuhui ◽  
Hu Xiaoying
Keyword(s):  
Probability Theory ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Boolean Algebra ◽  
Nuclear Power ◽  
Power Plants ◽  
Block Diagram ◽  
Reliability Assessment ◽  
Simple Approach ◽  
Assessment Approach

The probability that the safety I&C system fails to actuate or advertently actuates RT or ESF functions, in part, essentially determines whether a nuclear power plant could operate safely and efficiently. Since more conservative assumptions and simplifications are introduced during the analysis, this paper achieves solid results by performing the modeling and calculation based on a relatively simple approach, the reliability block diagram (RBD) method. A typical safety I&C platform structure is involved in the model presented in this paper. From the perspective of conservation and simplicity, some assumptions are adopted in this paper. A group of formulas is derived in this paper based on Boolean algebra, probability theory, basic reliability concepts and equations, to facilitate the calculations of probabilities that the safety I&C system fails to actuate or advertently actuates RT or ESF functions. All the inputs of the analysis and calculation in this paper, which includes the I&C platform structure, the constitution of the hardware modules, and reliability data, are referenced to the nuclear power plant universal database where applicable. Although the conclusion drawn in the paper doesn’t apply to the I&C platform assessment for a specific plant, the method of modeling and process of analysis provides an illustration of an alternative quantitative reliability assessment approach for a typical safety I&C system installed in the nuclear power plant.

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