Park, Il-Ryong;Kim, Je-in;Suh, Sung-Bu;Kim, Jin;Kim, Kwang-Soo;Kim, Yoo-Chul
Journal of Ocean Engineering and Technology
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v.33
no.1
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pp.1-9
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2019
This paper considers a numerical assessment of the self-propulsion performance of a damaged ferry carrying cars in irregular waves. Computational fluid dynamics(CFD) simulations were performed to see whether the ferry complied with the Safe Return to Port (SRtP) regulations of Lloyd's register, which require that damaged passenger ships should be able to return to port with a speed of 6 knots (3.09 m/s) in Beaufort 8 sea conditions. Two situations were considered for the damaged conditions, i.e., 1) the portside propeller was blocked but the engine room was not flooded and 2) the portside propeller was blocked and one engine room was flooded. The self-propulsion results for the car ferry in intact condition and in the damaged conditions were assessed as follows. First, we validated that the portside propeller was blocked in calm water based on the available experimental results provided by KRISO. The active thrust of starboard propeller with the portside propeller blocked was calculated in Beaufort 8 sea conditions, and the results were compared with the experimental results provided by MARIN, and there was reasonable agreement. The thrust provided by the propeller and the brake horsepower (BHP) with one engine room flooded were compared with the values when the engine room was not flooded. The numerical results were compared with the maximum thrust of the propeller and the maximum brake horse power of the engine to determine whether the damaged car ferry could attain a speed of 6 knots(3.09 m/s).
Eutrophication has occurred due to the inflow of various water pollutants in many Korean reservoirs with low depth, and algal blooms of surface layer and low oxygenation of deep layer have repeated every year. There are several existing technologies to alleviate the stratification of reservoirs, but it is difficult to apply them in field sites due to the necessity of electric power and low economic efficiency. In this study, a non-powered water circulation system using natural energy of wind and water flow has been developed, and two test-beds constructed in the reservoirs with different conditions and examined its field applicability. Through computational fluid dynamics (CFD) simulation, it has been shown that the water circulation system could induce the downward flow to mitigate the stratification between surface and deep layers, and its influence radius could reach about 30 m. As a result of long-term monitoring of the test-beds, various water quality improvement effects have been observed such as moderation of DO fluctuation by water circulation, reduction of DO supersaturation and prevention of excessive pH rising. In order to improve the applicability of the water circulation system, it is considered necessary to review countermeasures against flood and depth conditions of each reservoir.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.15
no.1
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pp.56-61
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2022
In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.
With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.
A directional coupler device, one of the fundamental components of photonic integrated circuits, distributes optical power by evanescent field coupling between two adjacent optical waveguides. In this paper, the design process for manufacturing a directional coupler device is reviewed, and the accuracy of the design results, as seen from the characteristics of the actual fabricated device, is confirmed. When designing a directional coupler device through a two-dimensional (2D) beam-propagation-method (BPM) simulation, an optical structure is converted to a two-dimensional planar structure through the effective index method. After fabricating the directional coupler device array, the characteristics are measured. To supplement the 2D-BPM results that are different from the experimental results, a 3D-BPM simulation is performed. Although 3D-BPM simulation requires more computational resources, the simulation result is closer to the experimental results. Furthermore, the waveguide core refractive index used in 3D-BPM is adjusted to produce a simulation result consistent with the experimental results. The proposed design procedure enables accurate design of directional coupler devices, predicting the experimental results based on 3D-BPM.
The flow pattern at the inlet of the catalyst layer in a selective catalytic reduction (SCR) system is one of the key parameters influencing the performance of the denitrification process. In the curved diffusing parts between the ammonia injection grids and the catalyst layers, guide vanes are installed to improve flow uniformity. In the present study, a numerical simulation has been performed to investigate the effect of the geometrical configuration of the guide vanes on the aerodynamic characteristics of a denitrification facility. This application has been made to the existing SCR process in a large-scaled coal-fired power plant. The flow domain to be solved covers the whole region of the flow passages from the exit of the ammonia injection gun to the exit of the catalyst layers. ANSYS-Fluent was used to calculate the three-dimensional steady viscous flow fields with the proper turbulence model fitted to the flow characteristics. The root mean square of velocity and the pressure drop inside the flow passages were chosen as the key performance parameters. Four types of guides vanes were proposed to improve the flow quality compared to the current configuration. The numerical results showed that the type 4 configuration was the most effective at improving the aerodynamic performance in terms of flow uniformity and pressure loss.
Kim, Seong-Gyun;Ryu, Geon Hwa;Kim, Young-Gon;Moon, Chae-Joo
The Journal of the Korea institute of electronic communication sciences
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v.17
no.2
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pp.265-278
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2022
The global energy paradigm is rapidly changing by centering on carbon neutrality, and wind energy is positioning itself as a leader in renewable energy-based power sources. The success of onshore and offshore wind energy projects focuses on securing the economic feasibility of the project, which depends on securing high-quality wind resources and optimal arrangement of wind turbines. In the process of constructing the wind farm, the optimal arrangement method of wind turbines considering the main wind direction is important, and this is related to minimizing the wake effect caused by the fluid passing through the structure located on the windward side. The accuracy of the predictability of the wake effect is determined by the wake model and modeling technique that can properly simulate it. Therefore, in this paper, using WindSim, a commercial CFD model, the wake diffusion pattern is analyzed through the sensitivity study of each wake model of the proposed onshore wind farm located in the mountainous complex terrain in South Korea, and it is intended to be used as basic research data for wind energy projects in complex terrain in the future.
J. Romero-Barrientos;F. Molina;J.I. Marquez Damian;M. Zambra;P. Aguilera;F. Lopez-Usquiano;S. Parra
Nuclear Engineering and Technology
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v.55
no.5
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pp.1593-1603
/
2023
In deterministic and Monte Carlo transport codes, b-delayed emission is included using a group structure where all of the precursors are grouped together in 6 groups or families, but given the increase in computational power, nowadays there is no reason to keep this structure. Furthermore, there have been recent efforts to compile and evaluate all the available b-delayed neutron emission data and to measure new and improved data on individual precursors. In order to be able to perform a transient Monte Carlo simulation, data from individual precursors needs to be implemented in a transport code. This work is the first step towards the development of a tool to explore the effect of individual precursors in a fissile system. In concrete, individual precursor data is included by expanding the capabilities of the open source Monte Carlo code OpenMC. In the modified code - named Time Dependent OpenMC or OpenMC(TD)- time dependency related to β-delayed neutron emission was handled by using forced decay of precursors and combing of the particle population. The data for continuous energy neutron cross-sections was taken from JEFF-3.1.1 library. Regarding the data needed to include the individual precursors, cumulative yields were taken from JEFF-3.1.1 and delayed neutron emission probabilities and delayed neutron spectra were taken from ENDF-B/VIII.0. OpenMC(TD) was tested in a monoenergetic system, an energy dependent unmoderated system where the precursors were taken individually or in a group structure, and in a light-water moderated energy dependent system, using 6-groups, 50 and 40 individual precursors. Neutron flux as a function of time was obtained for each of the systems studied. These results show the potential of OpenMC(TD) as a tool to study the impact of individual precursor data on fissile systems, thus motivating further research to simulate more complex fissile systems.
Jun-Taek, Lim;Michael;Nam-Kyun, Im;Kwang-Cheol, Seo
Journal of the Korean Society of Marine Environment & Safety
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v.29
no.6
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pp.672-680
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2023
Weight is a critical factor in the ship design process given that it has a substantial impact on the hydrodynamic performance of ships. Typically, ships are optimally designed for specific conditions with a fixed draft and displacement. However, in reality, weight and draft can vary within a certain range owing to operational activities, such as fuel consumption, ballast adjustments, and loading conditions . Therefore, we investigated how resistance changes under three different loading conditions, namely overload, design-load, and lightship, for small craft, using both model experiments and numerical simulations. Additionally, we examined the sensitivity of weight changes to resistance to enhance the performance of ships, ultimately reducing power requirements in support of the International Maritime Organization's (IMO) goal of reducing CO2 emissions by 50% by 2050. We found that weight changes have a more significant impact at low Froude Numbers. Operating under overload conditions, which correspond to a 5% increase in draft and an 11.1% increase in displacement, can lead to a relatively substantial increase in total resistance, up to 15.97% and 14.31% in towing tests and CFD simulations, respectively.
Lee, Hak Geon;Yun, Chang Ho;Park, Jong Won;Lee, Yong Woo
Journal of Internet Computing and Services
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v.15
no.3
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pp.45-52
/
2014
The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.
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