• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.8
• /
• pp.1071-1076
• /
• 2020

The importance of network separation is due to the use of the Internet with existing business PCs, resulting in an internal information leakage event, and an environment configured to allow servers to access the Internet, which causes service failures with malicious code. In order to overcome this problem, it is necessary to use network virtualization to separate networks and network interconnection systems. Therefore, in this study, the construction area was constructed into the network area for the Internet and the server farm area for the virtualization system, and then classified and constructed into the security system area and the data link system area between networks. In order to prove the excellence of the proposed method, a network separation construction study using network virtualization was conducted based on the basis of VM Density's conservative estimates of program loads and LOBs.

• Journal of Radiation Protection and Research
• /
• v.47 no.1
• /
• pp.50-57
• /
• 2022

Background: There are several proton therapy facilities in operation or planned in Taiwan, and these facilities are anticipated to not only treat cancer but also provide beam services to the industry or academia. The simplified approach based on the Monte Carlo-based data sets (source terms and attenuation lengths) with the point-source line-of-sight approximation is friendly in the design stage of the proton therapy facilities because it is intuitive and easy to use. The purpose of this study is to expand the Monte Carlo-based data sets to allow the simplified approach to cover the application of proton beams more widely. Materials and Methods: In this work, the MCNP6 Monte Carlo code was used in three simulations to achieve the purpose, including the neutron yield calculation, Monte Carlo-based data sets generation, and dose assessment in simple cases to demonstrate the effectiveness of the generated data sets. Results and Discussion: The consistent comparison of the simplified approach and Monte Carlo simulation results show the effectiveness and advantage of applying the data set to a quick shielding design and conservative dose assessment for proton therapy facilities. Conclusion: This study has expanded the existing Monte Carlo-based data set to allow the simplified approach method to be used for dose assessment or shielding design for beam services in proton therapy facilities. It should be noted that the default model of the MCNP6 is no longer the Bertini model but the CEM (cascade-exciton model), therefore, the results of the simplified approach will be more conservative when it was used to do the double confirmation of the final shielding design.

• Journal of the Korean earth science society
• /
• v.43 no.5
• /
• pp.579-590
• /
• 2022

In this study, we aimed to develop a Python-based outer-ring galaxy analysis algorithm according to the data science process. We assumed that the potential users are citizen scientists, including students and teachers. In the actual classification studies using real data of galaxies, a specialized software called IRAF is used, thereby limiting the general public's access to the software. Therefore, an image analysis algorithm was developed for the outer-ring galaxies as targets, which were compared with those of the previous research. The results of this study were compared with those of studies conducted using IRAF to verify the performance of the newly developed image analysis algorithm. Among the 69 outer-ring galaxies in the first test, 50 cases (72.5%) showed high agreement with the previous research. The remaining 19 cases (27.5%) showed differences that were caused by the presence of bright stars overlapped in the line of sight or weak brightness in the inner galaxy. To increase the usability of the finished product that has undergone a supplementary process, all used data, algorithms, Python code files, and user manuals were loaded in GitHub and made available as shared educational materials.

• Journal of Radiation Protection and Research
• /
• v.46 no.2
• /
• pp.58-65
• /
• 2021

Background: The evaluation of skyshine distribution, release of airborne radioactive nuclides, and soil activation and groundwater migration were required for radiological assessment of the impact on the environment surrounding In-Flight (IF)-system facility of the RAON (Rare isotope Accelerator complex for ON-line experiment) accelerator complex. Materials and Methods: Monte Carlo simulation by MCNPX code was used for evaluation of skyshine and activation analysis for air and soil. The concentration model was applied in the estimation of the groundwater migration of radionuclides in soil. Results and Discussion: The skyshine dose rates at 1 km from the facility were evaluated as 1.62 × 10^-3 μSv·hr^-1. The annual releases of ³H and ¹⁴C were calculated as 9.62 × 10^-5 mg and 1.19 × 10^-1 mg, respectively. The concentrations of ³H and ²²Na in drinking water were estimated as 1.22 × 10^-1 Bq·cm^-3 and 8.25 × 10^-3 Bq·cm^-3, respectively. Conclusion: Radiological assessment of environmental impact on the IF-facility of RAON was performed through evaluation of skyshine dose distribution, evaluation of annual emission of long-lived radionuclides in the air and estimation of soil activation and groundwater migration of radionuclides. As a result, much lower exposure than the limit value for the public, 1 mSv·yr^-1, is expected during operation of the IF-facility.

• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.2
• /
• pp.94-107
• /
• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of KIBIM
• /
• v.12 no.4
• /
• pp.19-31
• /
• 2022

With the development of 3D-based CAD (Computer Aided Design), attempts at freeform building design have expanded to small and medium-sized buildings in Korea. However, a standardized system for continuous utilization of shape data and BIM conversion process implemented with 3D-based NURBS is still immature. Without accurate review and management throughout the Freeform building project, interference between members occurs and the cost of the project increases. This is very detrimental to the project. To solve this problem, we proposed a continuous utilization process of 3D shape information based on BIM parameters. Our process includes algorithms such as Auto Split, Panel Optimization, Excel extraction based on shape information, BIM modeling through Adaptive Component, and BIM model utilization method using ID Code. The optimal cutting reference point was calculated and the optimal material specification was derived using the Panel Optimization algorithm. With the Adaptive Component design methodology, a BIM model conforming to the standard cross-section details and specifications was uniformly established. The automatic BIM conversion algorithm of shape data through Excel extraction created a BIM model without omission of data based on the optimized panel cutting reference point and cutting line. Finally, we analyzed how to use the BIM model built for automatic conversion. As a result of the analysis, in addition to the BIM utilization plan in the general construction stage such as visualization, interference review, quantity calculation, and construction simulation, an individual management plan for the unit panel was derived through ID data input. This study suggested an improvement process by linking the existing research on atypical panel optimization and the study of parameter-based BIM information management method. And it showed that it can solve the problems of existing Freeform building project.

• Composites Research
• /
• v.35 no.5
• /
• pp.340-346
• /
• 2022

In this study, an optimal structural design of composite helicopter blades is performed using the genetic algorithm-based optimizer PSGA (Particle Swarm assisted Genetic Algorithm). The blade sections consist of the skin, spar, form, and balancing weight. The sectional geometries are generated using the B-spline curves while an opensource code Gmsh is used to discretize each material domain which is then analyzed by a finite element sectional analysis program Ksec2d. The HART II blade formed based on either C- or D-spar configuration is exploited to verify the cross-sectional design framework. A numerical simulation shows that each spar model reduces the blade mass by 7.39% and 6.65%, respectively, as compared with the baseline HART II blade case, while the shear center locations being remain close (within 5% chord) to the quarter chord line for both cases. The effectiveness of the present optimal structural design framework is demonstrated, which can readily be applied for the structural design of composite helicopter blades.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.213-221
• /
• 2022

Intelligent Character Recognition System for Account Payable (ICRS AP) Automation represents the process of capturing text from scanned invoices and extracting the key fields from invoices and storing the captured fields into properly structured document format. ICRS plays a very critical role in invoice data streamlining, we are interested in data like Vendor Name, Purchase Order Number, Due Date, Total Amount, Payee Name, etc. As companies attempt to cut costs and upgrade their processes, accounts payable (A/P) is an example of a paper-intensive procedure. Invoice processing is a possible candidate for digitization. Most of the companies dealing with an enormous number of invoices, these manual invoice matching procedures start to show their limitations. Receiving a paper invoice and matching it to a purchase order (PO) and general ledger (GL) code can be difficult for businesses. Lack of automation leads to more serious company issues such as accruals for financial close, excessive labor costs, and a lack of insight into corporate expenditures. The proposed system offers tighter control on their invoice processing to make a better and more appropriate decision. AP automation solutions provide tighter controls, quicker clearances, smart payments, and real-time access to transactional data, allowing financial managers to make better and wiser decisions for the bottom line of their organizations. An Intelligent Character Recognition System for AP Automation is a process of extricating fields like Vendor Name, Purchase Order Number, Due Date, Total Amount, Payee Name, etc. based on their x-axis and y-axis position coordinates.

• Structural Engineering and Mechanics
• /
• v.85 no.6
• /
• pp.793-808
• /
• 2023

Türkiye is located in a region where destructive earthquakes are frequently experienced due to its geological characteristics and geographical location. Therefore, considering the possibility of a devastating earthquake at any time, determining the reinforced concrete (RC) building seismic safety, constructed before or after the current seismic buildings code, is one of the most important issues to be completed firstly. For this purpose, rapid assessment methods developed to quickly determine the seismic safety of buildings are available in the literature. Comparison of the principles of Principles of the Determination of Risky Structures-2019, Column and Wall Index Method, P25 Scoring Method and Improved Discriminant Analysis Method, which are among these methods, have been aimed within the scope of this study. Within the scope of this paper, a total of 43 buildings in the Yalova/Çınarcık region of Türkiye that the damage level was determined by street observation method immediately after the 1999 Kocaeli (Izmit) Earthquake; 15 buildings with heavy damage and 28 buildings with moderate damage were examined by rapid assessment methods. Although the risk detection difference was not separated as a clear line in any of the methods used, the results obtained from the rapid assessment methods are evaluated as being compatible with the detected after earthquake structural seismic behavior of the buildings. The PDRS-2019 and column and wall index method gave the most approximate results. In the results obtained from the analyzes; structural features such as number of floors, frame continuity, soft/weak story irregularity, effective shear strength area, existence of heavy overhangs in plan, type of structural system have been found to be significantly effective on the earthquake behavior of buildings.

• Nuclear Engineering and Technology
• /
• v.55 no.2
• /
• pp.696-706
• /
• 2023

Consequences of an anticipated Beyond Design Basis Accident (BDBA) Long-Term Station Blackout (LTSBO) event with complete loss of grid power in the VVER-1200 reactor of Rooppur Nuclear Power Plant (NPP) of Unit-1 are assessed using the RASCAL 4.3 code. This study estimated the released radionuclides, received public radiological dose, and ground surface concentration considering 3 accident scenarios of International Nuclear and Radiological Event Scale (INES) level 7 and two meteorological conditions. Atmospheric transport, dispersion, and deposition processes of released radionuclides are simulated using a straight-line trajectory Gaussian plume model for short distances and a Gaussian puff model for long distances. Total Effective Dose Equivalent (TEDE) to the public within 40 km and radionuclides contribution for three-dose pathways of inhalation, cloudshine, and groundshine owing to airborne releases are evaluated considering with and without passive safety Emergency Core Cooling System (ECCS) in dry (winter) and wet (monsoon) seasons. Source term and their release rates are varied with the functional duration of passive safety ECCS. In three accident scenarios, the TEDE of 10 mSv and above are confined to 8 km and 2 km for the wet and dry seasons, respectively in the downwind direction. The groundshine dose is the most dominating in the wet season while the inhalation dose is in the dry season. Total received doses and surface concentration in the wet season near the plant are higher than those in the dry season due to the deposition effect of rain on the radioactive substances.