• Nuclear Engineering and Technology
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• v.41 no.4
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• pp.447-454
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• 2009

This paper is a technical review of the research and development results of the Korea Nuclear Instrumentation and Control System (KNICS) project and Nu-Tech 2012 program. In these projects man-machine interface system architecture, two digital platforms, and several control and protection systems were developed. One platform is a Programmable Logic Controller (PLC) for a digital safety system and another platform is a Distributed Control System (DCS) for a non-safety control system. With the safety-grade platform PLC, a reactor protection system, an engineered safety feature-component control system, and reactor core protection system were developed. A power control system was developed based on the DCS. A logic alarm cause tracking system was developed as a man-machine interface for APR1400. Also, Integrated Performance Validation Facility (IPVF) was developed for the evaluation of the function and performance of developed I&C systems. The safety-grade platform PLC and the digital safety system obtained approval for the topical report from the Korean regulatory body in February of 2009. A utility and vendor company will determine the suitability of the KNICS and Nu- Tech 2012 products to apply them to the planned nuclear power plants.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1926-1938
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• 2020

We validated the performance of RELAP MOD3.3 code regarding the hybrid SIT with available experimental data. The concept of the hybrid SIT is to connect the pressurizer to SIT to utilize the water inside SIT in the case of SBO or SB-LOCA combined with TLOFW. We investigated how well RELAP5 code predicts the physical phenomena in terms of the equilibrium time, stratification, condensation against Separate Effect Test (SET) data. We also conducted the validation of RELAP5 code against Integrated Effect Test (IET) experimental data produced by the ATLAS facility. We followed conventional approach for code validation of IET data, which are pre-test and post-test calculation. RELAP5 code shows substantial difference with changing number of nodes. The increase of the number of nodes tends to reduce the condensation rate at the interface between liquid and vapor inside the hybrid SIT. The environmental heat loss also contributes to the large discrepancy between the simulation results of RELAP5 and the experimental data.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1537-1546
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• 2017

Many thermal-hydraulic tests have been conducted at the Korea Atomic Energy Research Institute for verification of the SMART (System-integrated Modular Advanced ReacTor) design, the standard design approval of which was issued by the Korean regulatory body. In this paper, the contributions of these tests to the standard design approval of SMART are discussed. First, an integral effect test facility named VISTA-ITL (Experimental Verification by Integral Simulation of Transients and Accidents-Integral Test Loop) has been utilized to assess the TASS/SMR-S (Transient and Set-point Simulation/Small and Medium) safety analysis code and confirm its conservatism, to support standard design approval, and to construct a database for the SMART design optimization. In addition, many separate effect tests have been performed. The reactor internal flow test has been conducted using the SCOP (SMART COre flow distribution and Pressure drop test) facility to evaluate the reactor internal flow and pressure distributions. An ECC (Emergency Core Coolant) performance test has been carried out using the SWAT (SMART ECC Water Asymmetric Two-phase choking test) facility to evaluate the safety injection performance and to validate the thermal-hydraulic model used in the safety analysis code. The Freon CHF (Critical Heat Flux) test has been performed using the FTHEL (Freon Thermal Hydraulic Experimental Loop) facility to construct a database from the $5{\times}5$ rod bundle Freon CHF tests and to evaluate the DNBR (Departure from Nucleate Boiling Ratio) model in the safety analysis and core design codes. These test results were used for standard design approval of SMART to verify its design bases, design tools, and analysis methodology.

• Journal of the Korea Institute of Building Construction
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• v.9 no.2
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• pp.47-54
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• 2009

Integrated construction site management using RFID(Radio Frequency Identification) and facility maintenance introducing USN (Ubiquitous Sensor Network) have been widely used in the mega construction project sites. But, the validation on performance of RFID systems after introducing those has not been carried out. Given that the use of RFID systems have been increased, the construction industry as well as other industries needs the evaluation of the RFID system. By regarding the necessities for evaluation, a research to the satisfaction and importance evaluation of RFID system from the end-users' view point for site management was conducted. Satisfaction-importance matrix of satisfaction standards and importance standards was created (organised) according to the analysis result of a survey, proposed improvement methods and analysis about the items presented by each region like areas of sustainable maintenance, maintenance, progressive improvement and priority improvement. The result would contribute to enhance the utilization of system and its performance.

• Journal of KIBIM
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• v.6 no.2
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• pp.29-38
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• 2016

Road bridges are deteriorating gradually, and it is forecasted that the number of road bridges aging over 30 years will increase by more than 3 times of the current number. To maintain road bridges in a safe condition, current safety conditions of the bridges must be estimated for repair or reinforcement. However, budget and professional manpower required to perform in-depth inspections of road bridges are limited. This study proposes an estimation model for safety rating of road bridges by analyzing the data from Facility Management System (FMS) and Yearbook of Road Bridges and Tunnel. These data include basic specifications, year of completion, traffic, safety rating, and others. The distribution of safety rating was imbalanced, indicating 91% of road bridges have safety ratings of A or B. To improve classification performance, five safety ratings were integrated into two classes of G (good, A and B) and P (poor ratings under C). This rearrangement was set because facilities with ratings under C are required to be repaired or reinforced to recover their original functionality. 70% of the original data were used as training data, while the other 30% were used for validation. Data of class P in the training data were oversampled by 3 times, and Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was used to develop the estimation model. The results of estimation model showed overall accuracy of 84.8%, true positive rate of 67.3%, and 29 classification rule. Year of completion was identified as the most critical factor on affecting lower safety ratings of bridges.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.