• Nuclear Engineering and Technology
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• v.56 no.11
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• pp.4481-4486
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• 2024

As the use of nuclear and radiation technologies increases, the importance of radiation safety and monitoring increases. In this study, we develop a nuclear facility monitoring system (NFMS) for rapid response to radiation accidents in nuclear material storage facilities; (1) multi-sensor network based on NaI(Tl) detector and FPGA-DAQ system and (2) an artificial neural network (ANN) algorithm for tracking radiation source location. Energy resolution and sensitivity of the detectors were evaluated to accurately track the location of radioactive materials and to identify nuclides using the multi-sensor network. To evaluate the localization accuracy of NFMS, a test storage facility was built and experiments were performed. Localization accuracy was obtained by analyzing the measured counts for each detector using an artificial intelligence (AI) based ANN algorithm, confirming an accuracy of over 99 %. The developed NFMS is expected to contribute to the safe management of radioactive materials in nuclear facilities.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1463-1471
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• 2017

In order to monitor the pipe thinning caused by flow-accelerated corrosion (FAC) that occurs in coolant piping systems, a shear horizontal ultrasonic pitch-catch waveguide technique was developed for accurate pipe wall thickness monitoring. A clamping device for dry coupling contact between the end of the waveguide and pipe surface was designed and fabricated. A computer program for multi-channel on-line monitoring of the pipe thickness at high temperature was also developed. Both a four-channel buffer rod pulse-echo type and a shear horizontal ultrasonic waveguide type for high-temperature thickness monitoring system were successfully installed to the test section of the FAC proof test facility. The overall measurement error can be estimated as ${\pm}10{\mu}m$ during a cycle from room temperature to $200^{\circ}C$.

• Nuclear Engineering and Technology
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• v.38 no.6
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• pp.575-584
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• 2006

As the development of total management systems for sites along with site environmental information is becoming standard, the system known as the Site Information and Total Environmental database management System (SITES) has been developed over the last two years. The first result was a database management system for storing data obtained from facilities, and a site characterization in addition to an environmental assessment of a site. The SITES database is designed to be effective and practical for use with facility management and safety assessment in relation to Geographic Information Systems. SITES is a total management program, which includes its database, its data analysis system required for site characterization, a safety assessment modeling system and an environment monitoring system. It can contribute to the institutional management of the facility and to its safety reassessment. SITES is composed of two main modules: the SITES Database module (SDM) and the Monitoring & Assessment (M&A) module [1]. The M&A module is subdivided into two sub-modules: the Safety Assessment System (SAS) and the Site Environmental Monitoring System (SEMS). SAS controls the data (input and output) from the SITES DB for the site safety assessment, whereas SEMS controls the data obtained from the records of the measuring sensors and facilities. The on-line site and environmental monitoring data is managed in SEMS. The present paper introduces the procedure and function of the M&A modules.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.4
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• pp.263-269
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• 2004

During the last two years, Site Information and Total Environmental database management System (SITES) ver. 1.0 has been developed for the systematic SITES Database Module (SDM), which includes site information, facility information and environmental information. The SITES includes the module for site environmental monitoring system and safety assessment (M&A) system for the nuclear facility. SITES is expected to be an effective system for the radioactive waste disposal management facility. Currently, SITES ver.2.0 is under development after the SITES ver.1.0 that is focused on the M&A system. The main purpose of this paper is to introduce and try to account for the major development in the concept of SEMS sub-module of the M&A module. The SEMS is purposed of development of the program for real time environmental monitoring, prediction, and automatic alarm system using SITES Database and related information.

• Proceedings of the Korean Nuclear Society Conference
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• 2001.10a
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• pp.289.2-289
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• 2001

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.306-314
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• 2003

Engineered barrier test facility is specially designed to demonstrate the performance of engineered barrier system for the near-surface disposal facility under the domestic environmental conditions. Comprehensive measurement systems for the water content, temperature, matric potential are installed within each test cell. In this study, short-term monitoring of the behavior of multi-layered cover system is implemented with artificial rainfall system. The periodic measurement data are collected and analyzed by a dedicated database management system, and provide a basis for performance verification of the disposal cover design.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2011.10a
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• pp.503-504
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• 2011

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.2
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• pp.245-261
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• 2019

Radioactive contaminant from a nuclear facility moves to the ecosystem by run-off or groundwater flow. Among the two mechanisms, contaminant plume through a river can be easily detected through a surface water monitoring system, but radioactive contaminant transport in groundwater is difficult to monitor because of lack of information on flow path. To understand the contaminant flow in groundwater, understanding of the geo-environment is needed. We suggest a method to decide on monitoring location and points around an imaginary nuclear facility by using the results of site characterization in the study area. To decide the location of a monitoring well, groundwater flow modeling around the study area was conducted. The results show that, taking account of groundwater flow direction, the monitoring well should be located at the downstream area. Also, monitoring sections in the monitoring well were selected, points at which groundwater moves fast through the flow path. The method suggested in the study will be widely used to detect potential groundwater contamination in the field of oil storage caverns, pollution by agricultural use, as well as nuclear use facilities including nuclear power plants.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3898-3906
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• 2023

The paper notes that the most common way of handling spent nuclear fuel (SNF) of power reactors is its temporary long-term dry storage. At the same time, the operation of the dry spent fuel storage facilities almost never use the modern capabilities of information systems in safety control and collecting information for the next studies under implementation of aging management programs. The author proposes a structure of an information system that can be implemented in a dry spent fuel storage facility with ventilated storage containers. To control the thermal component of spent fuel storage safety, a database structure has been developed, which contains 5 tables. An algorithm for monitoring the thermal state of spent fuel was created for the proposed information system, which is based on the comparison of measured and forecast values of the safety criterion, in which the level of heating the ventilation air temperature was chosen. Predictive values of the safety criterion are obtained on the basis of previously published studies. The proposed algorithm is an implementation of the information function of the system. The proposed information system can be used for effective thermal monitoring and collecting information for the next studies under the implementation of aging management programs for spent fuel storage equipment, permanent control of spent fuel storage safety, staff training, etc.