• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.125-132
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• 2019

This paper presents a seismic reliability analysis method for an offshore wind turbine with a twisted tripod support structure under earthquake loading. A three dimensional dynamic finite element model is proposed to consider the nonlinearity of the ground-pile interactions and the geometrical characteristics of the twisted tripod support structure where out-of-plane displacement occurs even under in-plane lateral loadings. For the evaluation of seismic reliability, the failure probability was calculated for the maximum horizontal displacement of the pile head, which is calculated from time history analysis using artificial earthquakes for the design return periods. The application of the subset simulation method using the Markov Chain Monte Carlo(MCMC) sampling is proposed for efficient reliability analysis considering the limit state equation evaluation by the nonlinear time history analysis. The proposed method can be applied to the reliability evaluation and design criteria development of the offshore wind turbine with twisted tripod support structure in which two dimensional models and static analysis can not produce accurate results.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.87-92
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• 2019

In this paper, we have verified a low-voltage EM(elasto-magnetic) sensing technique for tensile force management of PSC(prestressed concrete) internal tendon in order to apply the technique to actual construction sites where stable power supply is difficult. From observation of past domestic and overseas PSC structural accident cases, it was found that PS tension is very important to maintain structural stability. In this paper, we have tried to measure the tensile force from a magnetic hysteresis curve through EM sensors according to voltage value by using relation between magnetostriction and stress of ferromagnetic material based on elastic-magnetic theory. For this purpose, EM sensor of double cylindrical coil type was fabricated and tensile force test equipment for PS tendon using hydraulic tensioning device was constructed. The experiment was conducted to confirm relationship between changes of permeability and tensile force from the measurement results of the maximum / minimum voltage amount. The change of magnetic hysteresis curve with magnitude of tensile force was also measured by reducing amount of voltage step by step. As a result, the slope of estimation equation in accordance with magnitude of magnetic field decreases with the voltage reduction. But it was confirmed a similar pattern of change of magnetic permeability for the magnetic hysteresis loop. So, in this study, it is considered that it is possible to manage the tensions of PSC internal tendon using EM sensing technique in low-voltage state.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.487-500
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• 2022

This study aims to examine visitors' usage intention of the mobile AR(Augmented reality) application for tourism in Korea. For this purpose, the study analyzed how three attributes of AR tourguide app such as interactivity, vividness, and novelty have influenced on the tourist in terms of three realms of their flow, their experience (education, entertainment, esthetics, and escapism), and their usage intention for the future. It conducted an online survey from 20 to 30 year-old 291 participants and used a structural equation modeling. Survey findings show that first, novelty has a positive influence on the state of flow in AR application after vividness; Interactivity does not any significant effect on the tourists' flow. Second, when tourists explore the flow in the AR tourguide app, it affects all realms of experience economy of education, entertainment, esthetics, and escapism. Third, when using AR tour guide app in the context of historical heritage site, the two dimensions of entertainment and education influence the usage intention but the other two of esthetics and escapism does not. This study has presented a theoretical contribution that it focuses on historical sites as one type of tourist attractions and suggests a new modeling integrating AR attributes, flow, experience, and usage intention. In addition, it can be used to become a practical reference for revising an user-oriented AR application and customer-tailored AR tourism.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.829-838
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• 2022

This study conducts Hypervelocity Impact(HVI) simulations considering space objects with various shapes and different impact angles. A commercial nonlinear structural dynamics analysis code, LS-DYNA, is used for the present simulation study. The Smoothed Particle Hydrodynamic(SPH) method is applied to represent the impact phenomena with hypervelocity. Mie-Grüneisen Equation of State and Johnson-Cook material model are used to consider nonlinear structural behaviors of metallic materials. The space objects with various shapes are modeled as a sphere, cube, cylinder, and cone, respectively. The space structure is modeled as a thin plate(200 mm×200 mm×2 mm). HVI simulations are conducted when space objects with various shapes with 4.119 km/s collide with the space structures, and the impact phenomena such as a debris cloud are analyzed considering the space objects with various shapes having the same mass at the different impact angles of 0°, 30° and 45° between the space object and space structure. Although space objects have the same kinetic energy, different debris clouds are generated due to different shapes. In addition, it is investigated that the size of the debris cloud is decreased by impact angles.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.33-41
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• 2023

As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.495-504
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• 2008

Evapotranspiration (ET) is an important state variable while simulating daily streamflow in hydrological models. In the estimation of ET, for example, when using FAO Penman Monteith equation, the LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAI from MODIS satellite data is available, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. Four years (2001-2004) of MODIS LAI was prepared for the evaluation of Penman Monteith ET in the continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungju watershed ($6661.3km^2$) located in the upstream of Han river basin. For four years (2001-2004) dam inflow data and meteorological data, the model was calibrated and verified using MODIS LAI data. The average Nash-Sutcliffe model efficiency was 0.66. The 4 years watershed average Penman Monteith ETs of deciduous, coniferous, and mixed forest were 639.1, 422.4, and 631.6 mm for average MODIS LAI values of 3.64, 3.50, and 3.63 respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.45-52
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• 2009

In conventional structural design, deterministic optimization which satisfies codified constraints is performed to ensure safety and maximize economical efficiency. However, uncertainties are inevitable due to the stochastic nature of structural materials and applied loads. Thus, deterministic optimization without considering these uncertainties could lead to unreliable design. Recently, there has been much research in reliability-based design optimization (RBDO) taking into consideration both the reliability and optimization. RBDO involves the evaluation of probabilistic constraint that can be estimated using the RIA (Reliability Index Approach) and the PMA(Performance Measure Approach). It is generally known that PMA is more stable and efficient than RIA. Despite the significant advancement in PMA, RBDO still requires large computation time for large-scale applications. In this paper, A new reliability-based design optimization (RBDO) method is presented to achieve the more stable and efficient algorithm. The idea of the new method is to integrate a response surface method (RSM) with PMA. For the approximation of a limit state equation, the moving least squares (MLS) method is used. Through a mathematical example and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1266-1278
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• 2021

Objective: We aimed to compare the aortic valve area (AVA) calculated using fast high-resolution three-dimensional (3D) magnetic resonance (MR) image acquisition with that of the conventional two-dimensional (2D) cine MR technique. Materials and Methods: We included 139 consecutive patients (mean age ± standard deviation [SD], 68.5 ± 9.4 years) with aortic valvular stenosis (AS) and 21 asymptomatic controls (52.3 ± 14.2 years). High-resolution T2-prepared 3D steady-state free precession (SSFP) images (2.0 mm slice thickness, 10 contiguous slices) for 3D planimetry (3DP) were acquired with a single breath hold during mid-systole. 2D SSFP cine MR images (6.0 mm slice thickness) for 2D planimetry (2DP) were also obtained at three aortic valve levels. The calculations for the effective AVA based on the MR images were compared with the transthoracic echocardiographic (TTE) measurements using the continuity equation. Results: The mean AVA ± SD derived by 3DP, 2DP, and TTE in the AS group were 0.81 ± 0.26 cm², 0.82 ± 0.34 cm², and 0.80 ± 0.26 cm², respectively (p = 0.366). The intra-observer agreement was higher for 3DP than 2DP in one observer: intraclass correlation coefficient (ICC) of 0.95 (95% confidence interval [CI], 0.94-0.97) and 0.87 (95% CI, 0.82-0.91), respectively, for observer 1 and 0.97 (95% CI, 0.96-0.98) and 0.98 (95% CI, 0.97-0.99), respectively, for observer 2. Inter-observer agreement was similar between 3DP and 2DP, with the ICC of 0.92 (95% CI, 0.89-0.94) and 0.91 (95% CI, 0.88-0.93), respectively. 3DP-derived AVA showed a slightly higher agreement with AVA measured by TTE than the 2DP-derived AVA, with the ICC of 0.87 (95% CI, 0.82-0.91) vs. 0.85 (95% CI, 0.79-0.89). Conclusion: High-resolution 3D MR image acquisition, with single-breath-hold SSFP sequences, gave AVA measurement with low observer variability that correlated highly with those obtained by TTE.