1,721,002 research outputs found
Algebraic approach for the diagnosis of turbine cycles in nuclear power plants
No full textAccording to plant operating staff's practical needs, authors proposed a diagnosis model to identify the performance degradation of steam turbine cycles in nuclear power plants (NPPs). The essential idea of this study is how to identify the intrinsically degraded component which causes electric loss. Authors found that there were not so many turbine cycle diagnosis applications in NPPs currently because of technical, financial, or social characteristics of the plant. So a great part of the diagnosis has been dependent on operating staff's experience and knowledge. However as economic competition becomes severe, the efficiency staffs is asking for reliable and practical advisory tools. For the solution of these shortcomings, authors proposed a simple and intuitive diagnosis concept based on the superposition rule of degradation phenomena, which can be derived by simple algebra and correlation analysis. Though the superposition rule is not so significant statistically, almost all of the performance indices under normal operation are fairly compatible with this model. Authors developed a prototype model of quantitative root-cause diagnosis and validated the background theory using the simulated data. The turbine cycle advisory system using this model was applied to Gori NPP units 3&4. (c) 2005 Elsevier B.V. All rights reserved
Comparative study on state analysis of BOP in NPPs
No full textUnder the deregulation environment, the performance enhancement of balance of plant (BOP) or turbine cycle in nuclear power plants is being highlighted. To analyze performance level of turbine cycle, we use the performance test procedures provided from an authorized institution such as American Society of Mechanical Engineers. However, through plant investigation, it was proved that the requirements of the performance test procedures about the reliability and quantity of sensors was difficult to be satisfied. As a solution of this weakness, a state analysis method that is the expanded concept of signal validation, was proposed on the basis of the statistical and the neural network approaches. Authors recommended the statistical linear regression model by analyzing correlation among turbine cycle parameters as a reference state analysis method. Its advantage is that its derivation is not heuristic, it is possible to calculate model uncertainty, and it is easy to apply to an actual plant. The error of the statistical linear regression model is below 3% under normal as well as abnormal system states. Additionally the auto-associative neural network (AANN) model was recommended since the statistical model is impossible to apply to the validation of all of the sensors and is sensitive to the outlier that is the signal located out of statistical distribution. Because there are a lot of sensors need to be validated in turbine cycle, principal component analysis (PCA) and wavelet analysis (WA) were applied as a pre-processor for the reduction of input dimension and for the enhancement of training accuracy, and the results were compared. Both are effective to reduce the number of the input and output, dimension, but WA is superior to PCA in the compensation of the outliers. The outlier localization capability of WA enhanced the robustness of the AANN. In case of the AANN with WA, the training accuracy of the model was nearly 100% and the trained neural network restored the degraded signals to the values within +/-3% of the true signals
Risk-informed approach to the safety improvement of the reactor protection system of the AGN-201K research reactor
Full text linkPeriodic safety reviews (PSRs) are conducted on operating nuclear power plants (NPPs) and have been mandated also for research reactors in Korea, in response to the Fukushima accident. One safety review tool, the probabilistic safety assessment (PSA), aims to identify weaknesses in the design and operation of the research reactor, and to evaluate and compare possible safety improvements. However, the PSA for research reactors is difficult due to scarce data availability. An important element in the analysis of research reactors is the reactor protection system (RPS), with its functionality and importance. In this view, we consider that of the AGN-201K, a zero-power reactor without forced decay heat removal systems, to demonstrate a risk-informed safety improvement study. By incorporating risk- and safety-significance importance measures, and sensitivity and uncertainty analyses, the proposed method identifies critical components in the RPS reliability model, systematically proposes potential safety improvements and ranks them to assist in the decision-making process
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Interactive system design using the complementarity of Axiomatic Design and Fault Tree Analysis
No full textTo efficiently design safety-critical systems such as nuclear power plants, with the requirement of high reliability, methodologies allowing for rigorous interactions between the synthesis and analysis processes have been proposed. This paper attempts to develop a reliability-centered design framework through an interactive process between Axiomatic Design (AD) and Fault Tree Analysis (FTA). Integrating AD and FTA into a single framework appears to be a viable solution, as they compliment each other with their unique advantages. AD provides a systematic synthesis tool while FTA is commonly used as a safety analysis tool. These methodologies build a design process that is less subjective, and they enable designers to develop insights that lead to solutions with improved reliability. Due to the nature of the two methodologies, the information involved in each process is complementary: a success tree versus a fault tree. Thus, at each step a system using AD is synthesized, and its reliability is then quantified using the FT derived from the AD synthesis process. The converted FT provides an opportunity to examine the completeness of the outcome from the synthesis process. This study presents an example of the design of a Containment Heat Removal System (CARS). A case study illustrates the process of designing the CURS with an interactive design framework focusing on the conversion of the AD process to FTA
Thermal power estimation by fouling phenomena compensation using wavelet and principal component analysis
No full textA small percentage of reactor thermal power can be overestimated because of fouling phenomena in a secondary feedwater flowmeter. This study proposes a signal processing technique for the compensation of a degraded flowmeter such a secondary feedwater flowmeter in nuclear power plants. The technique proposed is mainly focused on noise classification and step-by-step noise reduction. The noises focused are classified into the rapid distortion caused by environmental interference, the flow fluctuation according to plant state transition and the degradation by fouling phenomena qualitatively. The multi-step de-noising technique reduces each noise by three techniques step-by-step. The wavelet analysis as a low frequency pass filter to remove the rapid distortion, the linear principal component analysis (PCA) to pl edict a steady-state value from the fluctuation, and the non-linear PCA implemented as an autoassociative neural network (AANN) to predict an original value from the signal including fouling phenomena are developed. The main purpose of this approach is to make an AANN concentrate on compensating the degradation by fouling phenomena itself. For the demonstration the signals from a simulator and signal modeling were used so that the role and the performance of each noise removal step was represented. In addition a thermal power deviation estimator is proposed to recognize the degradation effect of each operating parameter for reactor thermal power calculation. (C) 1000 Published by Elsevier Science S.A. All rights reserved
Development of a need-oriented steam turbine cycle simulation toolbox
No full textWe call an electric generation mechanism, whose working fluid is water, as a steam turbine cycle or Rankine cycle. A steam turbine cycle has been adopted in fossil-fuel or nuclear power plants because it is suitable for large-scale and continuous operation. To check the performance level of a steam turbine cycle, performance tests are carried out according to the performance test codes (PTCs) provided by the authorized institute. However, authors found that it was too difficult to follow the PTCs in actual plants. The reason is signal reliability and the prerequisites of the PTCs. The effort to overcome these shortcomings already started and some commercial solutions were also developed. These solutions include a general-purpose simulation code with signal validation techniques. Despite these achievements, performance engineers are suffering from the inconsistency between their previous performance analysis work and new performance analysis tools. This study proposed the solution, a need-oriented turbine cycle simulation toolbox, which is another general-purpose simulation code with the signal validation method based on multivariate statistics. This toolbox removed the inconsistency by customizing the actual needs of performance engineers. The accuracy of the developed simulation code was validated with other commercial turbine cycle simulation codes
Prediction of the human response time with the similarity and quantity of information
No full textMemory is one of brain processes that are important when trying to understand how people process information. Although a large number of studies have been made on the human performance, little is known about the similarity effect in human performance. The purpose of this paper is to propose and validate the quantitative and predictive model on the human response time in the user interface with the concept of similarity. However, it is not easy to explain the human performance with only similarity or information amount. We are confronted by two difficulties: making the quantitative model on the human response time with the similarity and validating the proposed model by experimental work. We made the quantitative model based on the Hick's law and the law of practice. In addition, we validated the model with various experimental conditions by measuring participants' response time in the environment of computer-based display. Experimental results reveal that the human performance is improved by the user interface's similarity. We think that the proposed model is useful for the user interface design and evaluation phases. (c) 2005 Elsevier Ltd. All rights reserved
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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