• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.596-597
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• 2005

• Journal of Practical Agriculture & Fisheries Research
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• v.25 no.3
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• pp.14-18
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• 2023

White leg shrimps cultured in an inland private aquaculture farm with low salinity waters showed abnormal swimming behavior and appetite reduction in July 2022. Then, gradual mortality was observed in the aquaculture farm. During the diagnosis, bacterial strain KNUAF-SHP3 was isolated from the hepatopancreas of the dead shrimps. Based on the sequence of 16S rRNA gene, KNUAF-SHP3 was proved to be Shewanella sp., clustering into a group with S. algae MARS 14 and S. chilikensis JC5T. According to the result of experimental infection test, all shrimps challenged with high concentrations, 2.1×108 CFU/ml and 2.1×109 CFU/ml showed apparent disease symptoms and the cumulative mortality rates reached 100% in 7 days post challenge. These results emphasized that Shewanella isolate in this study can be a potential pathogen of white leg shrimp cultured in low salinity water.

• Geomechanics and Engineering
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• v.14 no.3
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• pp.257-269
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• 2018

Analysis of slope stability failures, as one of the complex natural hazards, is one of the important research issues in the field of civil engineering. Present paper adopts and investigates four soft computing-based techniques for this problem: Patient Rule-Induction Method (PRIM), M5' algorithm, Group Method of data Handling (GMDH) and Multivariate Adaptive Regression Splines (MARS). A comprehensive database consisting of 168 case histories is used to calibrate and test the developed models. Six predictive variables including slope height, slope angle, bulk density, cohesion, angle of internal friction, and pore water pressure ratio were considered to generate new models. The results of test studies are used for feasibility, effectiveness and practicality comparison of techniques with each other, and with the other available well-known methods in the literature. Results show that all methods not only are feasible but also result in better performance than previously developed soft computing based predictive models and tools. It is shown that M5' and PRIM algorithms are the most effective and practical prediction models.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.1
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• pp.51-58
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• 2021

Chemical decontamination of primary systems in a nuclear power plant (NPP) prior to commencing the main decommissioning activities is required to reduce radiation exposure during its process. The entire process is repeated until the desired decontamination factor is obtained. To achieve improved decontamination factors over a shorter time with fewer cycles, the appropriate flow characteristics are required. In addition, to prepare an operating procedure that is adaptable to various conditions and situations, the transient analysis results would be required for operator action and system impact assessment. In this study, the flow characteristics in the steady-state and transient conditions for the chemical decontamination operations of the Kori-1 NPP were analyzed and compared via the MARS-KS code simulation. Loss of residual heat removal (RHR) and steam generator tube rupture (SGTR) simulations were conducted for the postulated abnormal events. Loss of RHR results showed the reactor coolant system (RCS) temperature increase, which can damage the reactor coolant pump (RCP)s by its cavitation. The SGTR results indicated a void formation in the RCS interior by the decrease in pressurizer (PZR) pressure, which can cause surface exposure and tripping of the RCPs unless proper actions are taken before the required pressure limit is achieved.

• Journal of the Korean Geotechnical Society
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• v.38 no.9
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• pp.19-33
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• 2022

Planarity geotechnical exploration missions were actively performed during the 1970s and there was a period of decline from the 1 990s to the 2000s because of budget. However, exploring space resources is essential to prepare for the depletion of Earth's resources in the future and explore resources abundant in space but scarce on Earth, such as rare earth and helium-3. Additionally, the development of space technology has become the driving force of future industry development. The competition among developed countries for exoplanet exploration has recently accelerated for the exploration and utilization of space resources. For these missions and resource exploration/mining, geotechnical exploration is required. There have been several missions to explore exoplanet ground, including the Moon, Mars, and asteroids. There are Apollo, LUNA, and Chang'E missions for exploration of the Moon. The Mars missions included Viking, Spirit/Opportunity, Phoenix, and Perseverance missions, and the asteroid missions included the Hayabusa missions. In this study, space planetary mineral resource exploration technologies are explained, and the future technological tasks of Korea are described.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.11
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• pp.1700-1713
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• 2018

Objective: The aim of this study was to verify the usefulness of artificial neural networks (ANN), multivariate adaptive regression splines (MARS), naïve Bayes classifier (NBC), general discriminant analysis (GDA), and logistic regression (LR) for dystocia detection in Polish Holstein-Friesian Black-and-White heifers and cows and to indicate the most influential predictors of calving difficulty. Methods: A total of 1,342 and 1,699 calving records including six categorical and four continuous predictors were used. Calving category (difficult vs easy or difficult, moderate and easy) was the dependent variable. Results: The maximum sensitivity, specificity and accuracy achieved for heifers on the independent test set were 0.855 (for ANN), 0.969 (for NBC), and 0.813 (for GDA), respectively, whereas the values for cows were 0.600 (for ANN), 1.000 and 0.965 (for NBC, GDA, and LR), respectively. With the three categories of calving difficulty, the maximum overall accuracy for heifers and cows was 0.589 (for MARS) and 0.649 (for ANN), respectively. The most influential predictors for heifers were an average calving difficulty score for the dam's sire, calving age and the mean yield of the farm, where the heifer was kept, whereas for cows, these additionally included: calf sex, the difficulty of the preceding calving, and the mean daily milk yield for the preceding lactation. Conclusion: The potential application of the investigated models in dairy cattle farming requires, however, their further improvement in order to reduce the rate of dystocia misdiagnosis and to increase detection reliability.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2789-2802
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• 2020

Small Modular Reactors (SMRs) are attracting wide attention due to their outstanding performance, extensive studies have been carried out for lead-based fast reactors (LFRs) that cooled with Lead or Lead-bismuth (LBE), and small modular natural circulation LFR is one of the promising candidates for SMRs and LFRs development. One of the challenges for the design small modular natural circulation LFR is to master the natural circulation thermal-hydraulic performance in the reactor primary circuit, while the natural circulation characteristics is a coupled thermal-hydraulic problem of the core thermal power, the primary loop layout and the operating state of secondary cooling system etc. Thus, accurate predicting the natural circulation LFRs thermal-hydraulic features are highly required for conducting reactor operating condition evaluate and Thermal hydraulic design optimization. In this study, a thermal-hydraulic analysis code is developed for small modular natural circulation LFRs, which is based on several mathematical models for natural circulation originally. A small modular natural circulation LBE cooled fast reactor named URANUS developed by Korea is chosen to assess the code's capability. Comparisons are performed to demonstrate the accuracy of the code by the calculation results of MARS, and the key thermal-hydraulic parameters agree fairly well with the MARS ones. As a typical application case, steady-state analyses were conducted to have an assessment of thermal-hydraulic behavior under nominal condition, and several parameters affecting natural circulation were evaluated. What's more, two characteristics parameters that used to analyze natural circulation LFRs natural circulation capacity were established. The analyses show that the core thermal power, thermal center difference and flow resistance is the main factors affecting the reactor natural circulation. Improving the core thermal power, increasing the thermal center difference and decreasing the flow resistance can significantly increase the reactor mass flow rate. Characteristics parameters can be used to quickly evaluate the natural circulation capacity of natural circulation LFR under normal operating conditions.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• Journal of Bio-Environment Control
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• v.14 no.3
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• pp.218-231
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• 2005

This paper reviews the engineering approach needed to support humans during their long-term missions in space. This approach includes closed plant production systems under microgravity or low pressure, mass recycling, air revitalization, water purification, waste management, elimination of trace contaminants, lighting, and nutrient delivery systems in controlled ecological life support system (CELSS). Requirements of crops f3r space use are high production, edibility, digestibility, many culinary uses, capability of automation, short stems, and high transpiration. Low pressure on Mars is considered to be a major obstacle for the design of greenhouses fer crop production. However interest in Mars inflatable greenhouse applicable to planetary surface has increased. Structure, internal pressure, material, method of lighting, and shielding are principal design parameters for the inflatable greenhouse. The inflatable greenhouse operating at low pressure can reduce the structural mass and atmosphere leakage rate. Plants growing at reduced pressure show an increasing transpiration rates and a high water loss. Vapor pressure increases as moisture is added to the air through transpiration or evaporation from leaks in the hydroponic system. Fluctuations in vapor pressure will significantly influence total pressure in a closed system. Thus hydroponic systems should be as tight as possible to reduce the quantity of water that evaporates from leaks. And the environmental control system to maintain high relative humidity at low pressure should be developed. The essence of technologies associated with CELSS can support human lift even at extremely harsh conditions such as in deserts, polar regions, and under the ocean on Earth as well as in space.

• Journal of the Korean Society of Visualization
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• v.15 no.3
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• pp.20-26
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• 2017

The two-fluid equations are widely used to simulate two-phase flows in a nuclear reactor. For the two-fluid momentum equation, the wall and interfacial drag terms play an important role in predicting a two-phase flow behavior. Since the bubble density is much smaller than the water density, the bubble accelerates faster than the liquid in a nozzle. As a result, the bubble phase becomes faster than the liquid phase in the nozzle. In contrast, the opposite phenomena occur in the diffuser. The purpose of our study is to experimentally show these behaviors in an area-varying channel such as nozzle and diffuser. Experiments were made of turbulent bubbly flows in an area-varying horizontal channel. The velocities of the bubble and liquid phases were measured by the PIV technique. It was shown that the two-phase velocities were no longer close to each other in the area-varying regions. The bubble was faster than the liquid in the nozzle; in contrast, the bubble was slower than the liquid in the diffuser. Code simulations were also performed using the MARS code. By replacing the original wall drag model in the MARS code with Kim (1)'s wall drag partition model, we obtained the simulation results being consistent with experimental observations.