• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.80-93
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• 2023

We performed numerical simulations of blood flow in an arterial cerebral artery aneurysm to investigate the hemodynamic behavior after coil embolization. A patient-specific model was created based on CTA data. We also conducted the coil embolization simulation to obtain the coil placement within the aneurysm. Blood was assumed to be an incompressible Newtonian fluid, and both the vessel and coil were considered rigid walls. The pulsatile boundary condition was applied at the inlet, and the outflow boundary conditions were used at the outlets. Our findings demonstrated that the coil embolization significantly reduces the blood volume flowrate entering the aneurysm by effectively blocking the inflow jet, leading to a decrease in both TAWSS and WSS, especially at the systolic peak in the impingement zone. While several high OSI regions disappeared over the aneurysm surface, we observed high OSI regions with a relatively small area where the coil did not completely occlude the aneurysm. Overall, these results quantitatively analyzed the effectiveness of coil embolization by focusing on hemodynamic indicators, potentially preventing aneurysm rupture. The present work could contribute to the development of patient-specific coil embolization.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.291-298
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• 2023

SRAM-based in-memory computing is one of the technologies to solve the bottleneck of von Neumann architecture. In order to achieve SRAM-based in-memory computing, it is essential to design efficient SRAM bit-cell. In this paper, we propose a low-power differential sensing 8+T SRAM bit-cell which reduces power consumption and improves circuit performance. The proposed 8+T SRAM bit-cell is applied to ripple carry adder which performs SRAM read and bitwise operations simultaneously and executes each logic operation in parallel. Compared to the previous work, the designed 8+T SRAM-based ripple carry adder is reduced power consumption by 11.53%, but increased propagation delay time by 6.36%. Also, this adder is reduced power-delay-product (PDP) by 5.90% and increased energy-delay- product (EDP) by 0.08%. The proposed circuit was designed using TSMC 65nm CMOS process, and its feasibility was verified through SPECTRE simulation.

• Journal of Korean Port Research
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• v.3 no.1
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• pp.35-55
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• 1989

Today, about 99% of total import and export cargo in Korea is being transported through the port. The general trends of cargo handling show increases in capacity and speed, In order to cope with these trends, it is not only required to raise the efficiencies of port operation and function but also necessary to decide the optimal amount of the skilled labor force for cargo handling in the port. Cargo handling in the port is basically relied on the cargo handling facilities. Therefore, it is very important to reserve the amount of labor force for cargo handling system has been developed up to a certain level but the personnel management system which is the superior structure has not been followed well. In this study, therefore, we show a method to determine the required amount of labor force for cargo handling considering the amount of cargo and type of cargo handling work per each cargo, and the optimal amount labor force in cope with the fluctuation of the basic cargo handling labor force with respect to the time of in and out cargo flow in the viewpoint of minimizing the expences due to reservation of extra labor force than needed and firing employment of labor force using the Dynamic Programming. The derived algorithm is introduced into the computer simulation for Pusan port with the analyzed real data such as amount of cargo handling in the port with respect to working hour, cargo capacity, working step, the ratio of cargo handling facility and actual number of workers and we estimated the required labor force. As a result of analysis the labor force of Pusan port showed the over-employment such as maximum 21.4%, minimum 8.2% when we assumed that the averages of actual working hours and days were 8 hours in a day and 20 day in a month.

• Geomechanics and Engineering
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• v.33 no.2
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• pp.133-140
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• 2023

Soil erosion can cause scouring and failures of underwater structures, therefore, various soil improvement techniques are used to increase the soil erosion resistance. The microbially induced calcium carbonate precipitation (MICP) method is proposed to increase the erosion resistance, however, there are only limited experimental and numerical studies on the use of MICP treatment for improvement of surface erosion resistance. Therefore, this study investigates the improvement in surface erosion resistance of sands by MICP through laboratory experiments and numerical modeling. The surface erosion behaviors of coarse sands with various calcium carbonate contents were first investigated via the erosion function apparatus (EFA). The test results showed that MICP treatment increased the overall erosion resistance, and the contribution of the precipitated calcium carbonate to the erosion resistance and critical shear stress was quantified in relation to the calcium carbonate contents. Further, these surface erosion processes occurring in the EFA test were simulated through the coupled computational fluid dynamics (CFD) and discrete element method (DEM) with the cohesion bonding model to reflect the mineral precipitation effect. The simulation results were compared with the experimental results, and the developed CFD-DEM model with the cohesion bonding model well predicted the critical shear stress of MICP-treated sand. This work demonstrates that the MICP treatment is effective in improving soil erosion resistance, and the coupled CFD-DEM with a bonding model is a useful and promising tool to analyze the soil erosion behavior for MICP-treated sand at a particle scale.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.884-894
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• 2023

Design and safety assessment of fuel pins for application in innovative Generation IV fast reactors calls for a dedicated nuclear fuel modelling and for the extension of the fuel performance code capabilities to the envisaged materials and irradiation conditions. In the INSPYRE Project, comprehensive and physics-based models for the thermal-mechanical properties of U-Pu mixed-oxide (MOX) fuels and for fission gas behaviour were developed and implemented in the European fuel performance codes GERMINAL, MACROS and TRANSURANUS. As a follow-up to the assessment of the reference code versions ("pre-INSPYRE", NET 53 (2021) 3367-3378), this work presents the integral validation and benchmark of the code versions extended in INSPYRE ("post-INSPYRE") against two pins from the SUPERFACT-1 fast reactor irradiation experiment. The post-INSPYRE simulation results are compared to the available integral and local data from post-irradiation examinations, and benchmarked on the evolution during irradiation of quantities of engineering interest (e.g., fuel central temperature, fission gas release). The comparison with the pre-INSPYRE results is reported to evaluate the impact of the novel models on the predicted pin performance. The outcome represents a step forward towards the description of fuel behaviour in fast reactor irradiation conditions, and allows the identification of the main remaining gaps.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2112-2124
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• 2023

With the rise of economic and safety standards for nuclear reactors, new concepts of Gen-IV reactors and modular reactors showed more complex designs that challenge current tools for reactor physics analysis. A Monte Carlo (MC) two-step method was proposed in this work. This calculation scheme uses the continuous-energy MC method to generate multi-group cross-sections from heterogeneous models. The multi-group MC method, which can adapt locally-heterogeneous models, is used in the core calculation step. This calculation scheme is verified using a Gen-IV modular lead-based fast reactor (LFR) benchmark case. The influence of homogenized patterns, scatter approximations, flux separable approximation, and local heterogeneity in core calculation on simulation results are investigated. Results showed that the cross-sections generated using the 3D assembly model with a locally heterogeneous representation of control rods lead to an accurate estimation with less than 270 pcm bias in core reactivity, 0.5% bias in control rod worth, and 1.5% bias on power distribution. The study verified the applicability of multi-group cross-sections generated with the MC method for LFR analysis. The study also proved the feasibility of multi-group MC in core calculation with local heterogeneity, which saves 85% time compared to the continuous-energy MC.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1586-1591
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• 2022

Kirchhoff-Love plate (KLP) equation is a well established theory for a description of a deformation of a thin plate under certain outer source. Meanwhile, analysis of a vibrating plate in a frequency domain is important in terms of obtaining the main frequency/eigenfunctions and predicting the vibration of plate. Among various modal analysis methods, dynamic mode decomposition (DMD) is one of the efficient data-driven methods. In this work, we carry out DMD based modal analysis for KLP where thin plate is under effects of sine-type outer force. We first construct discrete time series of KLP solutions based on a finite difference method (FDM). Over 720,000 number of FDM-generated solutions, we select only 500 number of solutions for the DMD implementation. We report the resulting DMD-modes for KLP. Also, we show how DMD can be used to predict KLP solutions in an efficient way.

• Steel and Composite Structures
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• v.46 no.6
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• pp.839-856
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• 2023

This work presents a simple four-unknown refined integral plate theory for mechanical and thermal buckling behaviors of functionally graded (FG) plates resting on Visco-Pasternak foundations. The proposed refined high order shear deformation theory has a new displacement field which includes indeterminate integral variables and contains only four unknowns in which any shear correction factor not used, with even less than the conventional theory of first shear strain (FSDT). Governing equations are deduced from the principle of minimum total potential energy and a Navier type analytical solution is adopted for simply supported FG plates. The Visco-Pasternak foundations is considered by adding the impact of damping to the usual foundation model which characterized by the linear Winkler's modulus and Pasternak's foundation modulus. The accuracy of the present model is demonstrated by comparing the computed results with those available in the literature. Some numerical results are presented to show the impact of material index, elastic foundation type, and damping coefficient of the foundation, on the mechanical and thermal buckling behaviors of FG plates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.110-113
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• 2022

Nowadays, breaking through the conventional traffic signal control method based on mathematical optimization, artificial intelligence began to be used in the area. In response to this trend, many studies are ongoing to figure out how to utilize AI technology properly for traffic signal optimization. They just simply focus on which method will work well besides lots of machine learning techniques and abandon the reward function engineering. In many cases, the reward function consists of the average delay of the vehicles in the intersection. However, this may lead to AI's misunderstanding about the traffic signal control: what AI regards as a good situation may not be realistic. Even the reward function itself may not meet the service level. Therefore, this study analyzes the problems of previous reward functions and will suggest how to reward function can be enhanced.