• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3879-3891
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• 2021

A heat pipe residual heat removal system is proposed to be incorporated into the reactor driven subcritical (RDS) facility, which has been proposed by MIT Nuclear Reactor Laboratory for testing and demonstrating the Fluoride-salt-cooled High-temperature Reactor (FHR). It aims to reduce the risk of the system operation after the shutdown of the facility. One of the main components of the system is an air-cooled heat pipe heat exchanger. The alkali-metal high-temperature heat pipe was designed to meet the operation temperature and residual heat removal requirement of the facility. The heat pipe model developed in the previous work was adopted to simulate the designed heat pipe and assess the heat transport capability. 3D numerical simulation of the subcritical facility active zone was performed by the commercial CFD software STAR CCM + to investigate the operation characteristics of this proposed system. The thermal resistance network of the heat pipe was built and incorporated into the CFD model. The nominal condition, partial loss of air flow accident and partial heat pipe failure accident were simulated and analyzed. The results show that the residual heat removal system can provide sufficient cooling of the subcritical facility with a remarkable safety margin. The heat pipe can work under the recommended operation temperature range and the heat flux is below all thermal limits. The facility peak temperature is also lower than the safety limits.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.343-343
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• 2022

강우의 유출은 하늘에서 발생한 강우가 다양한 유역을 거쳐 하천 및 해안 등으로 방류되는 일련의 과정을 의미한다. 강우의 유출과정에서 좀 더 효율적인 유량처리를 위하여 대부분의 도시 유역에는 우수관망이 설치되어 있다. 우수관망은 일정 빈도 이하의 강우량 방재를 목적으로 설계하며, 해당 강우량을 초과하는 경우 침수피해가 발생한다. 우수관망의 목표 강우를 초과하는 경우를 위하여 우수 저류지, 펌프장 및 LID(Low Impact Development) 시설물 설치 등 다양한 노력이 지속되어 왔으며, 이를 더욱 효율적으로 관리하기 위한 연구가 지속되고 있다. 본 연구에서는 강우 발생유역을 격자로 분할하여 우수의 흐름을 파악하여 효율적인 저류지 및 LID 시설물의 설치 위치를 지정하고자 한다. 분석지역은 경상남도 창원시 마산합포구 인근이며, ArcGIS 10.8을 이용하여 해당 지역의 지형을 3D로 구현하였으며 EPA-SWMM 5.1을 이용하여 침수분석을 진행하였다. 또한, 구성된 TIN(Triangulated Irregular Network)를 10m × 10m 크기의 격자로 분할하여 지표고에 따른 유량의 흐름 및 중첩을 판단하였다. 분할된 격자들 중 유량의 중첩 정도가 가장 높으며 침수피해 정도가 높은 지역을 대상으로 종류 및 크기를 고려한 최적의 비용과 효율을 갖는 저류지 및 LID 시설물 설치 위치를 결정하였다. 우수관망 시스템, LID 시설물, 우수 저류지 각각의 시선에서 접근한 기존의 연구와 달리 다양하고 포괄적인 방재시설물 설치를 통해 더욱 효율적이고 경제적인 우수 방재 시스템 구현에 도움이 될 것으로 기대된다. 우수관망 시스템, LID 시설물, 우수 저류지 각각의 시선에서 접근한 기존의 연구와 달리 다양하고 포괄적인 방재시설물 설치를 통해 더욱 효율적이고 경제적인 우수 방재 시스템 구현에 도움이 될 것으로 기대된다.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.993-1001
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• 2024

The TANDEM project is a European initiative funded under the EURATOM program. The project started on September 2022 and has a duration of 36 months. TANDEM stands for Small Modular ReacTor for a European sAfe aNd Decarbonized Energy Mix. Small Modular Reactors (SMRs) can be hybridized with other energy sources, storage systems and energy conversion applications to provide electricity, heat and hydrogen. Hybrid energy systems have the potential to strongly contribute to the energy decarbonization targeting carbon-neutrality in Europe by 2050. However, the integration of nuclear reactors, particularly SMRs, in hybrid energy systems, is a new R&D topic to be investigated. In this context, the TANDEM project aims to develop assessments and tools to facilitate the safe and efficient integration of SMRs into low-carbon hybrid energy systems. An open-source "TANDEM" model library of hybrid system components will be developed in Modelica language which, by coupling, will extend the capabilities of existing tools implemented in the project. The project proposes to specifically address the safety issues of SMRs related to their integration into hybrid energy systems, involving specific interactions between SMRs and the rest of the hybrid systems; new initiating events may have to be considered in the safety approach. TANDEM will study two hybrid systems covering the main trends of the European energy policy and market evolution at 2035's horizon: a district heating network and power supply in a large urban area, and an energy hub serving energy conversion systems, including hydrogen production; the energy hub is inspired from a harbor-like infrastructure. TANDEM will provide assessments on SMR safety, hybrid system operationality and techno-economics. Societal considerations will also be encased by analyzing European citizen engagement in SMR technology safety.

• IMMUNE NETWORK
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• v.20 no.6
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• pp.50.1-50.11
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• 2020

Osteoporosis is prevalent in elderly women and it may cause dental implant failure. In particular, estrogen deficiency in postmenopausal women leads to higher rates of osteoporosis prevalence. Immune cell-mediated effects involving the development of osteoporosis have been studied previously; however, the role of IL-10-producing regulatory B (B10) cells in osteoporosis is largely unclear. Here, we examined the role of B10 cells in osteoporosis. C57BL/6 mice were subjected to ovariectomy (OVX). Fifteen weeks after OVX surgery, the first molar of the right maxillary was extracted, and twenty-four weeks after OVX surgery, serous progression of osteoporosis was observed in the alveolar bone. Moreover, the proportion of CD19⁺CD5⁺CD1d^high regulatory B cells, B10, and CD4⁺CD25⁺FoxP3⁺ regulatory T cells from the spleen of OVX mice decreased during the progression of osteoporosis, compared to controls. In contrast to regulatory cells, IL-17-producing Th (Th17) cell levels were increased in OVX mice. Adoptive transfer of B10 cells to OVX mice led to a decrease in Th17 cell abundance and inhibited the development of osteoporosis in the alveolar bone from OVX mice. Thus, our results suggest that B10 cells may help suppress osteoporosis development.

• IMMUNE NETWORK
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• v.24 no.3
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• pp.19.1-19.15
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• 2024

The influenza virus poses a global health burden. Currently, an annual vaccine is used to reduce influenza virus-associated morbidity and mortality. Most influenza vaccines have been developed to elicit neutralizing Abs against influenza virus. These Abs primarily target immunodominant epitopes derived from hemagglutinin (HA) or neuraminidase (NA) of the influenza virus incorporated in vaccines. However, HA and NA are highly variable proteins that are prone to antigenic changes, which can reduce vaccine efficacy. Therefore, it is essential to develop universal vaccines that target immunodominant epitopes derived from conserved regions of the influenza virus, enabling cross-protection among different virus variants. The internal proteins of the influenza virus serve as ideal targets for universal vaccines. These internal proteins are presented by MHC class I molecules on Ag-presenting cells, such as dendritic cells, and recognized by CD8 T cells, which elicit CD8 T cell responses, reducing the likelihood of disease and influenza viral spread by inducing virus-infected cell apoptosis. In this review, we highlight the importance of CD8 T cell-mediated immunity against influenza viruses and that of viral epitopes for developing CD8 T cell-based influenza vaccines.

• Journal of Platform Technology
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• v.11 no.6
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• pp.34-46
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• 2023

The design of non-pneumatic tires, which are created by filling the space between the wheel and the tread with elastomeric compounds or polygonal spokes, has become an important research topic in the automotive and aerospace industries. In this study, a system was designed for the design of non-pneumatic tires through the implementation of a generative adversarial network. We specifically examined factors that could impact the design, including the type of non-pneumatic tire, its intended usage environment, manufacturing techniques, distinctions from pneumatic tires, and how spoke design affects load distribution. Using OpenCV, various shapes and spoke configurations were generated as images, and a GAN model was trained on the projected GANs to generate shapes and spokes for non-pneumatic tire designs. The designed non-pneumatic tires were labeled as available or not, and a Vision Transformer image classification AI model was trained on these labels for classification purposes. Evaluation of the classification model show convergence to a near-zero loss and a 99% accuracy rate confirming the generation of non-pneumatic tire designs.

• The Korean Journal of Emergency Medical Services
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• v.12 no.2
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• pp.59-69
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• 2008

Purpose : This study aims to provide basic data to establish an effective emergency medical service system by analyzing health educator' understanding and use of emergency medical service system at schools. Method : 93 questionnaires from 200 elementary, middle and high school nurses in the city D were collected from May 26 to July 7, 2008 and ${\chi}^2$ analysis and frequency analysis were carried out with SPSS win PC 14.0. Results : 1. As for emergency contact points, 3(3.30%) answers 'they do not have any knowledge', 40(43.96%) said 'they have some idea' and 48(52.75%) said 'they do know about it'. Among 24 respondents who have less than five years of working experience, 2(8.33%), 16(66.67%) and 6(25.00%) answered 'have no knowledge', 'a little knowledge' and 'clear knowledge on it' respectively. As for 9 who have 6-10 years of career, 1(12.50%), 4(50.00%) and 3(37.50%) answered 'have no knowledge', 'a little knowledge' and 'clear knowledge on it' respectively. Among 32 respondents who have 11~20 years, there were no respondents with no knowledge on the given question, and 9(29.03%) said they have some understanding and 22(70.97%) answered they have clear understanding on the topic. From this result, it can be said that there is statistically meaningful differences among different working year groups with ${\chi}^2=16.583$ and p= .010. 2. As for 119 emergency contact in the given district, 24(29.63%), 30(37.04%) and 27 (33.33%) answered 'do not know', 'know' and 'know very well' respectively. As for the question to ask whether they know Emergency Medical Information Center 1339, 66(70.97%) answered 'Yes' and 27(29.03%) answered 'No'. When it comes to emergency contact numbers and list of hospitals, 59(63.44%) said 'they have some list', 20(21.51%) answered 'they have well established contact network' and 14(15.05%) said 'they have none'. 3. As for the use of 119 service at the time of emergency at schools, 59(63.44%), said 'Yes' and 12(12.90%) answered 'No'. Among those who said 'yes', 29(31.18%), 24(25.81%) and 5(5.38%) answered they have used the service 1-2, 3-5 and 6-10 times respectively. Conclusion : In order to ensure health educator to effectively deal with emergency situations at schools, there should be special activities to enhance health educator' understanding on 119 and Emergency Medical Information Center 1339 and at the same time, a system should be established to connect schools, 119 in a given district, hospitals and Emergency Medical Information Center 1339.

• Elastomers and Composites
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• v.49 no.1
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• pp.24-30
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• 2014

3-Amino-1,2,4-triazole (ATA) (2.5 and 5.0 phr) was incorporated into a immiscible maleated ethylene propylene diene rubber(mEPDM)/maleated high density polyethylene(mHDPE) (50 wt%/50 wt%) blend by melt mixing. Effects of the ATA on structure, mechanical and rheological properties of the blend was investigated. FT-IR and DMA results revealed that supramolecular hydrogen bonding interactions between the polymer chains occur by reaction of ATA with maleic anhydride grafted onto the component polymers in the blend, which induces the physical crosslinks in the blend. FE-SEM analysis showed that mEPDM forms a dispersed phase in continuous mHDPE matrix, and the blend with the ATA has finer phase morphology as compared to the blend without the ATA. By the addition of ATA in the blend, there were significant increases in tensile strength, modulus and elongation-at-break as well as elastic recoverability. Melt rheology studies revealed that ATA induced substantial increase in storage modulus and complex viscosity of the blend at the melt state.

• Geophysics and Geophysical Exploration
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• v.25 no.2
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• pp.59-70
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• 2022

Recent studies demonstrate that machine learning has expanded in the field of seismic interpretation. Many convolutional neural networks have been developed for seismic sequence identification, which is important for seismic interpretation. However, expense and time limitations indicate that there is insufficient data available to provide a sufficient dataset to train supervised machine learning programs to identify seismic sequences. In this study, patch division and data augmentation are applied to mitigate this lack of data. Furthermore, to obtain spatial information that could be lost during patch division, an artificial channel is added to the original data to indicate depth. Seismic sequence identification is performed using a U-Net network and the Netherlands F3 block dataset from the dGB Open Seismic Repository, which offers datasets for machine learning, and the predicted results are evaluated. The results show that patch-based U-Net seismic sequence identification is improved by data augmentation and the addition of an artificial channel.