• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.703-709
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• 2017

Korea Utility Helicopter(KUH) is a project to replace the aging helicopter presently being operated by the military with a domestic helicopter. The auxiliary power unit is a device that supplies emergency power to the system by an alternator installed when the main generator fails and the start motor converts the electrical energy of the battery into mechanical rotational energy to rotate the auxiliary power unit engine. With continuing power and operation, defects of the starting motor were found and improvements were carried out to solve it. In the failure mode analysis, the causes of possible defects were classified into 5 categories. Analysis of the 5 factors revealed that the main cause of defects is mechanical wear, which was found to be related to spring pressure. 250 tests were conducted through the theoretically determined pressure and regression analysis was performed with 4 sampling.The results showed that pressure was related to wear rate. In conclusion, early wear and breakage due to wear can be controlled through spring force and test showed the prediction of wear and the validity of the result were confirmed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.503-506
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• 2001

There are four factors for patient monitoring : electrocardiography, blood pressure, temperature and respiration. While there are a lot of studies of E.C.C (electro-cardiography) monitoring system in the world, the studies of Respiratory system are not enough and leave much to be desired in the country. In this paper, we developed a respiratory system with the electrical impedance change of the lungs depending on the breath. Using the same electrode, we can monitor E.C.C and Respiration simultaneously, so we can monitor a patient's no-breathing state due to the central nerve paralysis in the emergency room easily. In this monitoring system, the analog part was made separated from the digital part for reducing power source noise and protecting patient from electric shock. The analog part consists of the several parts a high-frequency sine-wave generator, all amplifier for amplifying any impedance change signal, an analog processing part for rectifying and filtering. And the digital parts consists of three parts an AD convertor for converting analog signal to digital signal, digital filter, and a digital part for digital signal processing. This system's merits are using the same electrode with E.C.C and developing the multiple patient monitoring system easily.

• Progress in Medical Physics
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• v.18 no.3
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• pp.144-148
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• 2007

Current digital radiography systems are rapidly glowing in clinical applications. The purpose of this study was to evaluate the characteristics of a mobile digital radiographic system. The performance of the mobile DR system was evaluated by measuring the modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). Measurements were made on a LISTEM Mobix-1000 generator and a Teleoptic PRA Alpha-R4000 detector. Imaging characteristics were measured for these two systems using the IEC-61267 defined RQA5 (kVp: 74, additional filtration: 21 mmAl) radiographic condition. The MTF at 10% was measured as 2.4 cycles/mm and the DQE(0) values for radiation exposure 0.19, 0.5, and 1.3 mR were measured as 54%, 55%, and 76%, respectively. The NPS curves gradually decreased at high spatial frequencies. This high DQE at low frequencies, may be useful for low frequency information. The results suggested that mobile DR system could be integrated with emergency ambulance system in teleradiologic imaging applications.