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

• Composites Research
• /
• v.35 no.1
• /
• pp.23-30
• /
• 2022

Polycarbosilane(PCS) is an important precursor for melt-spinning the silicon carbide(SiC) fibers and manufacturing ceramics. The PCS is a metal-organic polymer precursor capable of producing continuous SiC fibers having excellent performance such as high-temperature resistance and oxidation resistance. The SiC fibers are manufactured through melt-spinning, stabilization, and heat treatment processes using the PCS manufactured by synthesis, purification, and control of the molecular structure. In this paper, we analyzed the effect of purification of unreacted substances and low molecular weight through solvent treatment of PCS and the effect of heat treatment at various temperatures change the polymerization and network rearrangement of PCS. Especially, we investigated the complex viscosity and structural arrangement of PCS precursors according to solvent treatment and heat treatment through the rheological properties.

• Journal of Radiation Industry
• /
• v.17 no.3
• /
• pp.225-232
• /
• 2023

In this study, poly(ethylene-co-vinyl acetate)/magnesium hydroxide (EVA/MDH) composites were prepared by electron beam crosslinking. EVA as a matrix resin and MDH as a flame retardant were melt-blended and compression molded to prepare EVA/MDH composites. The prepared EVA/MDH composites were electron beam-irradiated at various absorbed doses of 50~200kGy. The effects of electron beam irradiation on the gel content, tensile strength, elongation-at-break, thermal properties, and flame retardancy of the composites were investigated. The gel content and tensile strength increased, while the elongation-at-break decreased with an increase in the absorbed dose due to the formation of crosslinked network structures. In addition, the thermal stability and flame retardancy improved as the absorbed dose increased. Therefore, the EVA/MDH composites prepared in this study can be used as an insulation material for flame-retardant and heat-resistant wires and cables.

• Korean Chemical Engineering Research
• /
• v.57 no.2
• /
• pp.274-282
• /
• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of Internet Computing and Services
• /
• v.24 no.1
• /
• pp.61-69
• /
• 2023

Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.14 no.3
• /
• pp.15-20
• /
• 2015

After the US government declared 3D printing technology a next-generation manufacturing technology, there have been many practical studies conducted to expand 3D printing technology to manufacturing technologies, called AMERICA MAKES. In particular, the Keck Center, located at the University of Texas at El Paso, has studied techniques for easily combing the 3D stacking process with space mobility and expanded these techniques to simultaneous staking techniques for multiple materials. Additionally, it developed convergence manufacturing techniques, such as direct inking techniques, in order to produce a module structure that combines electronic circuits and components, such as CUBESET. However, in these studies, it is impossible to develop a unified system using traditional independent through simple sequencing connections. This is because there are many problems in the integration between the stacking modeling of 3D printers and post-machining, such as thermal deformations, the precision accuracy of 3D printers, and independently driven coordinate problems among process systems. Therefore, in this paper, the integration method is suggested, which combines these 3D printers and subsequent machining process systems through an Internet-based cloud. Additionally, the sequential integrated system of a 3D printer, an NC milling machine, machine vision, and direct inking are realized.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.5
• /
• pp.137-147
• /
• 2008

Recently, Power and thermal management are becoming major concerns in computer system design. The energy efficiency is an important attribute of the mobile and embedded systems. Today's powerful mobile processors needs more energy and longer battery life. Many research has been focused to reduce energy consumption for the mobile processors.In this paper, performance monitoring system for the Power-management techniques is implemented for Intel's XScale microarchitecture-based Marvell PXA320 processor on Windows CE platform. It also provides software interface for changing DVFS configuration. Performance and power consumption are measured for benchmark programs through performance counter value and voltage/current measurements on LabVIEW platform. By using the developed monitoring system, it is possible for dynamic power management to track processor's workload and to determine the actual power consumption.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2014.02a
• /
• pp.484.2-484.2
• /
• 2014

There are many efforts to improving the power conversion efficiencies (PCEs) of dye-sensitized solar cells (DSCs). Although DSCs have a low production cost, their low PCE and low thermal stability have limited commercial applications. This study describes the preparation of a novel multifunctional polymer gel electrolyte in which a cross-linking polymerization reaction is used to encapsulate $TiO_2$ nanoparticles toward improving the power conversion efficiency and long-term stability of a quasi-solid state DSC. A series of liquid junction dye-sensitized solar cells (DSCs) was fabricated based on polymer membrane encapsulated dye-sensitized $TiO_2$ nanoparticles, prepared using a surface-induced cross-linking polymerization reaction, to investigate the dependence of the solar cell performance on the encapsulating membrane layer thickness. The ion conductivity decreased as the membrane thickness increased; however, the long term-stability of the devices improved with increasing membrane thickness. Nanoparticles encapsulated in a thick membrane (ca. 37 nm), obtained using a 90 min polymerization time, exhibited excellent pore filling among $TiO_2$ particles. This nanoparticle layer was used to fabricate a thin-layered, quasi-solid state DSC. The thick membrane prevented short-circuit paths from forming between the counter and the $TiO_2$ electrode, thereby reducing the minimum necessary electrode separation distance. The quasi-solid state DSC yielded a high power conversion efficiency (7.6/8.1%) and excellent stability during heating at $65^{\circ}C$ over 30 days. These performance characteristics were superior to those obtained from a conventional DSC (7.5/3.5%) prepared using a $TiO_2$ active layer with the same thickness. The reduced electrode separation distance shortened the charge transport pathways, which compensated for the reduced ion conductivity in the polymer gel electrolyte. Excellent pore filling on the $TiO_2$ particles minimized the exposure of the dye to the liquid and reduced dye detachment.

• Preventive Nutrition and Food Science
• /
• v.4 no.1
• /
• pp.6-13
• /
• 1999

The quality of the buckwheat bread made with previously heated ($55^{\circ}C$) and cooled buckwheat flour 0dough with the addition of ascorbic acid(AA) or/and sodium stearoyl lactylate(SSL) was evaluated . With heat treatemtn , handling property of dough and grain of the bread crumb were markedly improved and stickiness of the dough decreased . The optimum resting time to produce the best loaf volume and grain was found to be 3hr for both unheated and heated doughs. Heat treated dough showed higher dough expansion rate during fermentation than unheated dough, even though heated dough had lower loaf volume, probably because of an improper oven spring. Increase in shortening of dough formula from 3% to 5% improved loaf volume without improvement of handling property. With the addition of 100 ppm AA or/and 0.5% SSL, loaf volume and crumb grain were improved for both unheated and heated doughs.Microscopic analysis of a mixed dough by scanning electron microscope (SEM) showed that heated dough had a continuous network whereas unheated dough was discontinuous. The addition of AA and SSL gave the dough a more continuous network whereas unheated dough was discontinuous . The addition of AA and SSL gave the dough a more continuous structure with strengthened strands or interactions between the starch granule and protein. Therefore, it appears that the presence of continuity in heated buckwheat breadwheat bread dough is related to the improved loaf volume and crumb grain without dough stickness.

• Journal of Hydrogen and New Energy
• /
• v.19 no.5
• /
• pp.403-409
• /
• 2008

Polymer electrolyte membrane fuel cell (PEMFC) is very interesting power source due to high power density, simple construction and operation at low temperature. But it has problems such as high cost, improvement of performance, effect of temperature and initial start at low temperature. These problems can be approached to be solved by using experiment and mathematical method which are general principles for analysis and optimization of control system for heat and hydrogen detecting management. In this paper, insulation vessel and control system for stable operation of fuel cell at low temperature were developed for experiment. The constant temperature capability and the heating time at sub-zero temperatures with insulation control system were studied by using a heating bar of 60W class. PEMFC stack which was made by 4 cells with $50\;mc^2$ active area in each cell is a thermal source. Times which take to reach constant temperature by the state of insulation vacuum were measured at variable environment temperatures. The test was performed at two conditions: heating mode and cooling mode. Constant temperature capability was better at lower environment temperature and vacuum pressure. The results of this experiment could be used as basis data about stable operation of fuel cell stack in low temperature zone.