• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.103-110
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• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.551-560
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• 1998

This paper presents a neural network model representing complex hydro-thermo-dynamic characteristics of a steam generator in nuclear power plants. The key modeling processes include training data gathering process, analysis of system dynamics and determining of the neural network structure, training process, and the final process for validation of the trained model. In this paper, we suggest a training data gathering method from an unstable steam generator so that the data sufficiently represent the dynamic characteristics of the plant over a wide operating range. In addition, we define the inputs and outputs of neural network model by analyzing the system dimension, relative degree, and inputs/outputs of the plant. Several types of neural networks are applied to the modeling and training process. The trained networks are verified by using a class of test data, and their performances are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.555-561
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• 2009

The established mathematical modeling methods have limitation to know the hydraulic characteristics at the wastewater treatment plant which are complex and nonlinear systems. So, an artificial neural network (ANN) model based on hydraulic characteristics is applied for modeling wastewater quality of a full-scale wastewater treatment plant using DNR (Daewoo nutrient removal) process. ANN was trained using data which are influents (TSS, BOD, COD, TN, TP) and effluents (COD, TN, TP) components in a year, and predicted the effluent results based on the training. To raise the efficiency of prediction, inputs of ANN are added the influent and effluent information that are in yesterday and the day before yesterday. The results of training data tend to have high accuracy between real value and predicted value, but test data tend to have lower accuracy. However, the more hydraulic characteristics are considered, the results become more accuracy.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.315-323
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• 2009

Pressure oscillations triggered by the unstable interaction of dynamic flow features of the hydraulic turbine with the hydraulic plant system - including the electrical design - can at times reach significant levels and could lead to damage of plant components or could reduce component lifetime significantly. Such a problem can arise for overload as well as for part load operation of the turbine. This paper discusses an approach to analyze the overload high pressure oscillation problem using computational fluid dynamic (CFD) modeling of the hydraulic machine combined with a network modeling technique of the hydraulic system. The key factor in this analysis is the determination of the overload vortex rope volume occurring within the turbine under the runner which is acting as an active element in the system. Two different modeling techniques to compute the flow field downstream of the runner will be presented in this paper. As a first approach, single phase flow simulations are used to evaluate the vortex rope volume before moving to more sophisticated modeling which incorporates two phase flow calculations employing cavitation modeling. The influence of these different modeling strategies on the simulated plant behavior will be discussed.

• Journal of the Korean Society of Combustion
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• v.23 no.1
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• pp.44-54
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• 2018

Heat and mass balance process modeling has been conducted for a coal-firing power plant to be used as a testbed facility for development of various plant systems and equipment. As the material and design of the boiler tube bundle and fuel conversion to the biomass have become major concerns, the process modeling is required to incorporate those features in its calculation. The simulation cases for two different generation load show the satisfying results compared to the operational data from the actual system. Based on the established process conditions, the hypothetical case using wood pellet has also been simulated. Additional calculations for the tube bundle has been conducted regarding the changes in the tube material and design.

• Coupled systems mechanics
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• v.5 no.1
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• pp.21-39
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• 2016

Wastewater process models are the essential tools for understanding relevant aspects of wastewater treatment system. Wastewater process modeling provides more options for upgrades and better understanding of new plant design, as well as improvements of operational controls. The software packages (BioWin, GPS-X, Aqua designer, etc) solve a series of simulated equations simultaneously in order to propose several solutions for a specific facility. Research and implementation of wastewater process modeling in combination with computational fluid dynamics enable testing for improvements of flow characteristics for WWTP and at the same time exam biological, physical, and chemical characteristics of the flow. Application of WWTP models requires broad knowledge of the process and expertise in modeling. Therefore, an efficient and good modeling practice requires both experience and set of proper guidelines as a background.

• The Plant Pathology Journal
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• v.35 no.5
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• pp.459-472
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• 2019

The increasing variation in climatic conditions under climate change directly influences plant-microbe interactions. To account for as many variables as possible that may play critical roles in such interactions, the use of an integrated modeling approach is necessary. Here, we report for the first time a local impact assessment and adaptation study of future epidemics of kiwifruit bacterial blossom blight (KBB) in Jeonnam province, Korea, using an integrated modeling approach. This study included a series of models that integrated both the phenological responses of kiwifruit and the epidemiological responses of KBB to climatic factors with a 1 km resolution, under the RCP8.5 climate change scenario. Our results indicate that the area suitable for kiwifruit cultivation in Jeonnam province will increase and that the flowering date of kiwifruit will occur increasingly earlier, mainly due to the warming climate. Future epidemics of KBB during the predicted flowering periods were estimated using the Pss-KBB Risk Model over the predicted suitable cultivation regions, and we found location-specific, periodic outbreaks of KBB in the province through 2100. Here, we further suggest a potential, scientifically-informed, long-term adaptation strategy using a cultivar of kiwifruit with a different maturity period to relieve the pressures of future KBB risk. Our results clearly show one of the possible options for a local impact assessment and adaptation study using multiple models in an integrated way.

• The Journal of Information Systems
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• v.18 no.3
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• pp.231-249
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• 2009

Recently, plant construction industries are enjoying a favorable business climate centering around developing countries and oil producing countries rich in oil money. This paper proposes a methodology of implementing case-based reasoning(CBR) system for managing knowledge like lessons learned and various documents accumulated in performing power plant construction projects which are receiving a lot of order from foreign countries such as the Middle East, etc. Our methodology is consisted of 10 steps : user requirement gathering, information modeling, case modeling, case base design, similarity function design, user interface design, case base building, CBR module development, user interface implementation, integration test. Also, to illustrate the effectiveness of proposed methodology, the real CBR system is implemented for the plant business division of 'H' company which has international competitiveness in the field of plant construction industry. At present, the implemented CBR system is successfully utilizing as storing, sharing, and reusing knowledge which is accumulated in performing power plant construction projects in the target enterprise.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.883-888
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• 2014

The paper describes the parameter tuning of power system stabilizer (PSS) for a power plant based on hybrid system modeling. The existing tuning method based on bode plot and root locus is well applied to keep power system stable. However, due to linearization of power system and an assumption that the parameter ratio of the lead-lag compensator in PSS is fixed, the results cannot guarantee the optimal performances to damp out low-frequency oscillation. Therefore, in this paper, hybrid system modeling, which has a DAIS (differential-algebraic-impusive-switched) structure, is applied to conduct nonlinear modeling for power system and find optimal parameter set of the PSS. The performances of the proposed method are carried out by time domain simulation with a single machine connected to infinite bus (SMIB) system.

• Journal of Environmental Impact Assessment
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• v.9 no.1
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• pp.61-74
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• 2000

This study compares the results of environmental impact assessment with the results of post-environmental investigation, using the case of Taean thermal power plant construction. The atmospheric and water qualities were not greatly changed before and after the construction of the power plant. However, the site of the highest concentration predicted by the atmospheric quality modeling in environmental impact assessment was different from that after operation of 4 power plants. There was also a difference in the diffusion range of thermal discharge water between the measured result(1km) and the predicted value(1.5km) with the model. Thus, environmental impact evaluation should be based on long-term (more than a year) environmental monitoring data. For the modeling of atmospheric quality and numerical thermal discharge water diffusion, appropriate models for each plant should be selected and the numerical modeling should be accompanied by computer simulation, wind tunnel test, etc. Moreover, environmental evaluation should focus more on the degree of impact on surroundings than the prediction of changes in surroundings caused by operation of plants.