• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.603-610
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• 2021

The major drawback of zirconia-based materials, in view of their applications as targets for minor actinide transmutation, is their poor thermal conductivity. The addition of MgO, which has high thermal conductivity, to zirconia-based materials is expected to improve their thermal conductivity. On these grounds, the present study aims at phase characterization and thermophysical property evaluation of neodymium-substituted zirconia (Zr_0.8Nd_0.2O_1.9; using Nd₂O₃ as a surrogate for Am₂O₃) and its composites with MgO. The composite was prepared by a solid-state reaction of Zr_0.8Nd_0.2O_1.9 (synthesized by gel combustion) and commercial MgO powders at 1773 K. Phase characterization was carried out by X-ray diffraction and the microstructural investigation was performed using a scanning electron microscope equipped with energy dispersive spectroscopy. The linear thermal expansion coefficient of Zr_0.8Nd_0.2O_1.9 increases upon composite formation with MgO, which is attributed to a higher thermal expansivity of MgO. Similarly, specific heat also increases with the addition of MgO to Zr_0.8Nd_0.2O_1.9. Thermal conductivity was calculated from measured thermal diffusivity, temperature-dependent density and specific heat values. Thermal conductivity of Zr_0.8Nd_0.2O_1.9-MgO (50 wt%) composite is more than that of typical UO₂ fuel, supporting the potential of Zr_0.8Nd_0.2O_1.9-MgO composites as target materials for minor actinides transmutation.

• Composites Research
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• v.34 no.2
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• pp.115-122
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• 2021

SMC(Sheet molding compound) composite is mainly used for forming of vehicle's body. Considering the car accident, it is essential to research the impact behavior and characteristics of materials. It is difficult to identify them because the impact process is completed in a short time. Therefore, the impact damage analysis using FE(finite element) model is required for the impact behavior. The impact damage analysis requires the parameters for the damage model of SMC composite. In this paper, ANN(artificial neural network) technique is applied to obtain the parameters for the damage model of SMC composite. The surrogate model by ANN was constructed with the result in LS-DYNA. By comparing the absorption energy in drop weight test with the result of ANN model, the optimized parameters were obtained. The acquired parameters were validated by comparing the results of the experiment, the FE model and the ANN model.

• 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.

• Health Policy and Management
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• v.33 no.1
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• pp.19-28
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• 2023

Background: With the enactment of the Hospice, Palliative, Care, and Life-sustaining Treatment Decision-Making Act in February 2018, legal guidelines for physician orders for life-sustaining treatment (POLST) were presented. This study was conducted to analyze the association of writing POLST on the use of health care before death. Methods: The study analyzed the electronic medical records and POLSTs of 1,003 adult patients who died at a tertiary hospital located in Seoul from February 4, 2018 to February 4, 2019. Results: Of the deaths, 80% (n=804) completed POLST. Among patients who completed POLST before death, 51% (n=412) were written 1-7 days before death, and only 31% (n=246) were completed by patients themselves. 99% (n=799) decided to withdraw or withhold cardiopulmonary resuscitation. As a result of analyzing the effect of POLST on medical use before death, it was found that POLST and inpatient cost had a significant negative correlation, and POLST completion significantly reduced death in the intensive care unit (ICU). However, both inpatient costs and death at ICU increased when the POLST was completed by surrogate decision-makers rather than patients themselves. Conclusion: The enactment of the Hospice, Palliative, Care, and Life-sustaining Treatment Decision-Making Act provided a legal basis for withdrawing and withholding meaningless life-sustaining treatment. By specifying the treatment to be received at the end of one's life through the POLST, inpatient treatment costs and death at the ICU were decreased. However, the frequent decision-making by the surrogates and completion of POLST close to death may hinder the original purpose of the law.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4431-4440
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• 2022

An advanced nuclear reactor based on molten salts including a molten salt reactor and pyroprocessing needs a sensitive monitoring system suitable for operation in harsh environments with limited access. Multi-element detection is challenging with the conventional technologies that are compatible with the in-situ operation; hence laser-induced breakdown spectroscopy (LIBS) has been investigated as a potential alternative. However, limited precision is a chronic problem with LIBS. We increased the precision of LIBS under high temperature by protecting optics using a gas protective layer and correcting for shotto-shot variance and lens-to-sample distance using a laser-induced acoustic signal. This study investigates cerium as a surrogate for uranium and corrosion products for simulating corrosive environments in LiCl-KCl. While the un-corrected limit of detection (LOD) range is 425-513 ppm, the acoustic-corrected LOD range is 360-397 ppm. The typical cerium concentrations in pyroprocessing are about two orders of magnitude higher than the LOD found in this study. A LIBS monitoring system that adopts these methods could have a significant impact on the ability to monitor and provide early detection of the transient behavior of salt composition in advanced molten salt-based nuclear reactors.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.47-47
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• 2020

하천 유사량 자료는 하천관리를 위해 기초적으로 활용되는 자료로 하천의 유지관리를 위한 유사량 자료의 측정은 필수적이다. 따라서, 현재 국내에서는 전국에 138개소의 국가유사량관측망에서 지속적인 유사량 측정을 수행하고 있지만, 기존의 재래식 부유사 채집기를 이용한 부유사 측정을 수행하고 있어 연간 약 20개소 내외에서만 직접조사가 수행되고 있고, 2019년도 기준 전국 138개소 중에서 2006년~2018년 동안 최소 1회 이상 유사량 측정을 수행한 지점은 40개소로 국가 유사량관측망의 약 29% 지점에 대해서만 조사가 수행되고 있다. 해외의 경우에도 기존 재래식 채집기를 통한 유사량 관측을 주로 수행하고 있지만 최근에는 기존 채집기를 이용한 유사량 조사방법의 고비용·저효율로 인한 시공간적 한계로 인해 대안기술이 개발되고 있다. 특히, 최근 해외에서는 ADCP를 활용한 유사량 측정 기술이 기존 부유사 채집기를 이용한 유사량 조사방법의 대안으로 시도되고 있다. ADCP를 이용한 유사량 측정방법은 ADCP의 초음파산란도를 활용하여 간접적으로 부유사의 농도를 추정하는 기술로 ADCP를 이용하여 유량자료과 함께 유사량 자료를 확보할 수 있을 것으로 기대되는 기술이다. 특히, 기존에 설치된 국가하천 자동유량측정장치(H-ADCP)에 적용이 가능하다면 다지점에서의 지속적인 유량측정과 함께 부유사 농도의 측정이 가능할 것으로 기대되고 있다. 이에 본 연구에서는 기존 국가하천에 설치되어 있는 자동유량측정장치(H-ADCP)의 초음파산란도를 활용한 부유사농도 측정 기술의 적용성을 검토하였다. 적용성의 검토를 위해 2016년 진동지점에서 수집된 H-ADCP 원시자료를 사용하여 초음파산란도를 활용한 부유사농도 측정 방법을 시범적으로 적용하였다. 적용결과, 실측 부유사농도와 H-ADCP로부터 추정된 부유사 농도를 비교를 통해서 H-ADCP를 활용한 부유사농도 측정 방법의 가능성을 확인할 수 있었지만, 기술적인 보완 및 개선이 필요할 것으로 판단되었다. 추후에는 지속적인 연구를 통해 ADCP 유사량 측정기술이 개발된다면 기존 부유사 채집기를 이용한 유사량 측정 방법의 대안으로 유사량 조사를 목적으로 활용이 될 수 있을 것으로 기대한다.

• Journal of the Korean Society of Food Culture
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• v.23 no.2
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• pp.243-251
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• 2008

This purpose of this study was to develop a functional muffin by adding yam powder in the shape of a muffin as a partial surrogate for wheat flour. The yam has been found to be effective for liver and kidney function, as well as the digestion of protein, since it produces glucuronic acid in the body. Therefore, the purpose of this study was to determine the optimal mixing conditions of yam muffins by adjusting the amounts yam powder, butter, and sugar. The mixing conditions for the yam muffins included 3 categories: yam powder $(X_1)$, sugar $(X_2)$, and butter $(X_3)$ by Central Composite Design (CCD) which was optimized by Response Surface Methodology (RSM). The effects of the three variable additions on muffin quality were examined via physical and chemical experiments, such as the analysis of texture (hardness, cohesiveness, springiness, gumminess), coloration (lightness, redness, yellowness), and height. Lastly, we performed a sensory test, which revealed significant findings for gumminess, color, appearance, flavor, softness (p<0.05), redness, and overall quality (p<0.01). Consequently, the optimal mixing rate which best satisfied the sensory items were 34.35g of yam powder, 80.15 g of sugar, and 80.55 g of butter.

• Journal of English Language & Literature
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• v.58 no.1
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• pp.117-142
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• 2012

The education of children is one of the most important parts in children's literature. Children's literature, whose implied readers are both children and parents, is a good means to teach how they should behave and interact. Therefore, literary conventions of children's literature tend to be conservative with happy endings or fairy tale elements. Most of the children's literature of the 18th century were read as a conduct book which teaches children good manners and proper behavior, and at the same time served as a guidebook which tells parents how to discipline children. It emphasized the need of discipline to ascertain the hierarchy and order of the family, and cherished the close relationship between parents and children. In the 19th century, the ideal of family becomes more internalized. In the early 20th century, the ideology of family still remained, even though the world wars and economic depressions caused the cracks and collapses of the family. In the later 20th century, the disintegration of the traditional family was accelerated. The ideal of family based on the close relationship between parents and children, has had problems from the start. The attachment and over-closeness became stressful and sometimes could be poisonous. Recent children's literature shows the process of disintegration of the traditional nuclear family, children suffering in the fractured family, children's mental trauma, and nostalgia for the lost family. However, modern children's literature manages to find the lost or ideal surrogate family, and often shows fairy-tale elements such as mystical and heroic child protagonists or helpers who might solve all the difficult problems at once, despite the collapse of the family in reality.

• IMMUNE NETWORK
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• v.21 no.6
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• pp.39.1-39.18
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• 2021

The high virulent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that emerged in China at the end of 2019 has generated novel coronavirus disease, coronavirus disease 2019 (COVID-19), causing a pandemic worldwide. Every country has made great efforts to struggle against SARS-CoV-2 infection, including massive vaccination, immunological patients' surveillance, and the utilization of convalescence plasma for COVID-19 therapy. These efforts are associated with the attempts to increase the titers of SARS-CoV-2 neutralizing Abs (nAbs) generated either after infection or vaccination that represent the body's immune status. As there is no standard therapy for COVID-19 yet, virus eradication will mainly depend on these nAbs contents in the body. Therefore, serological nAbs neutralization assays become a requirement for researchers and clinicians to measure nAbs titers. Different platforms have been developed to evaluate nAbs titers utilizing various epitopes sources, including neutralization assays based on the live virus, pseudovirus, and neutralization assays utilizing recombinant SARS-CoV-2 S glycoprotein receptor binding site, receptor-binding domain. As a standard neutralization assay, the plaque reduction neutralization test (PRNT) requires isolation and propagation of live pathogenic SARS-CoV-2 virus conducted in a BSL-3 containment. Hence, other surrogate neutralization assays relevant to the PRNT play important alternatives that offer better safety besides facilitating high throughput analyses. This review discusses the current neutralization assay platforms used to evaluate nAbs, their techniques, advantages, and limitations.