• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.582-588
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• 2018

Accident diagnosis is one of the complex tasks for nuclear power plant (NPP) operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN) has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM), which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents.

• Journal of Power Electronics
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• v.13 no.6
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• pp.985-990
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• 2013

This paper proposes a novel fault diagnosis scheme using parameter estimation of the stator resistance, especially in the case of the open-phase faults of PMSM drives. The stator resistance of PMSMs can be estimated by the recursive least square (RLS) algorithm in real time. Fault diagnosis is achieved by analyzing the estimated stator resistance of each phase according to the fault condition. The proposed fault diagnosis scheme is implemented without any extra devices. Moreover, the estimated parameter information can be used to improve the control performance. The feasibility of the proposed fault diagnosis scheme is verified by simulation and experimental results.

• International Journal of High-Rise Buildings
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• v.11 no.4
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• pp.331-346
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• 2022

Reproducing the horizontally homogeneous atmospheric boundary layer in computational wind engineering is essential for predicting the wind loads on structures. One of the important issues is to use fully developed inflow conditions, which will lead to the consistence problem between inflow condition and internal roughness. Thus, by analyzing the previous results of computational fluid dynamic modeling turbulent horizontally homogeneous atmospheric boundary layer, we modify the past hypotheses, detailly derive a new type of inflow condition for standard k-ε turbulence model. A group of remedial approaches including formulation for wall shear stress and fixing the values of turbulent kinetic energy and turbulent dissipation rate in first wall adjacent layer cells, are also derived to realize the consistence of inflow condition and internal roughness. By combing the approaches with four different sets of inflow conditions, the well-maintained atmospheric boundary layer flow verifies the feasibility and capability of the proposed inflow conditions and remedial approaches.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.13-16
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• 2009

Multi-view video broadcasting have been conducted with a variety of different system architectures. However, the previous systems have focused on wired broadcasting. On the contrary, our system is designed to be applied to mobile 3DTV broadcasting. We present a service framework adaptable to mobile clients where the load on the client is reduced as much as possible. MPEG-21 multiview DIA description schemes are presented for the efficient adaptation between the serer and client. Furthermore, we examine the feasibility of the proposed framework by analyzing the frame rate that a client device can process.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.6
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• pp.481-485
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• 2016

When analyzing economic feasibility for installing a PV generation plant at a certain location, the prediction of possible annual power production at the site using the target PV panels should be conducted on the basis of the local weather data provided by a local weather forecasting office. In addition, the prediction of PV generating power under certain weather conditions is useful for fault diagnosis and performance evaluation of PV generation plants during actual operation. This study analyzes PV cell characteristics according to a variety of weather conditions, including ambient temperature and irradiance level. From the analysis and simulation results, this work establishes a proper model that can predict the output characteristics of PV cells under changes in weather conditions.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.13 no.1
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• pp.40-47
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• 2017

In this paper, we investigate the feasibility of a strategy of failure detection and identification. The point of proposed strategy includes a pattern extraction approach for failure identification using Auto-Associative Kernel Regression (AAKR). We consider a simulation data concerning 605 signals of a Generic Pressurized Water Reactor(GPWR). In the application, the reconstructions are provided by a set of AAKR models, whose input signals have been selected by Correlation Analysis(CA) for the identification of the groups. The failure pattern is extracted by analyzing the residuals of observations and reconstructions. We present the possibility of extraction of patterns for six failure.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.192-200
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• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.3
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• pp.279-285
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• 2009

In this study, applied to the industrial water service, it is verified feasibility of break-even analysis method which has not been introduced in Korea. The On-san water pipeline of 7.1km among the Ul-san industrial water service is selected and the optimal replacement time calculated by break-even analysis method is year 2033 to 2044 which will be 53 to 67 years since the pipes were buried. If indirect cost such as the value of lost water and traffic disruption, service interruption, etc. is calculated as 30 and 100% of the direct cost, the financially optimum replacement time is advanced 3 to 9 years. These ways present rational criteria to establish long-term plan for budget and to execute the limited budget efficiently.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.65-67
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• 2001

This paper presents an application of UML(Unified Modeling Language) to develop the Transmission Loss Calculation Package (TLCP) and shows a feasibility of UML design for the power system analyzing software. In the rapidly restructuring electric power industry, it is required the development of efficient and transparent transmission pricing mechanism. This should be based to calculate an accurate transmission loss to prompt a fair competition and to give unbiased signals to all the market players. For those reasons, it is necessary to develop a software system for transmission loss calculation. In this paper, we design the TLCP based on UML, and describe using Rational Rose 2000.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.452-453
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• 2010

This paper proposes a novel diagnosis scheme using Extend Kalman Filter (EKF), especially, in subject to the open-phase faults of the inverter switches. The stator resistances of PMSM are estimated by the EKF in real time. The proposed diagnosis scheme is implemented without any extra devices. Moreover, since it uses a simple algorithm by analyzing only estimated stator resistances of each phase, the detection speed becomes fast. The feasibility of the proposed fault diagnosis scheme is proved by several simulation and experimental results.