• Journal of the Korean earth science society
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• v.40 no.1
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• pp.56-67
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• 2019

In this study, we analyzed the intensity attenuation for M 6.0, 6.5, and 7.0 earthquakes using the broadband strong ground motion simulation platform based on the physical seismic modeling developed by the US Southern California Earthquake Center (SCEC). The location of the earthquake was assumed to be near the epicenter of the 2016 M 5.8 Gyeongju earthquake, but two of the representative US regional models provided by the SCEC strong ground motion simulation platform were used for the propagation model. One is the Central and Eastern United States (CEUS) model representing the intraplate region, and the other is the LA Basin model representing the interplate region. Five modeling methodologies are presented in the version 16.5 of the simulation platform, and Song and Exsim models were used in this study. In the analysis, we found that different intensity attenuation patterns can be observed with the same magnitude of earthquakes, especially depending on the region (CEUS vs LA Basin). Given the same magnitude and distance, the instrumental intensity in the CEUS region (intraplate) could be larger by a unit of 2 than that in the LA Basin region (interplate). Given the difference of intensity attenuation patterns observed in the study, it is important to know the regional intensity attenuation characteristics to understand the accurate level of seismic hazard imposed in the Korean Peninsula. This study also shows the level of the uncertainty of intensity attenuation if region specific attenuation characteristics are not considered.

• Journal of Korea Water Resources Association
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• v.38 no.1
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• pp.1-9
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• 2005

The study shows the possible use of the index flood frequency curves for an estimation of flood quantiles at ungauged locations. Flood frequency analysis were made for the annual maximum flood data series at 9 available stations in the Han river basin. From the flood frquency curve at each station the mean annual flood of 2.33-year return period was determined and the ratios of the flood magnitude of various return period to the mean annual flood at each station were averaged throughout the Han river basin, resulting mean flood ratios of different return periods. A correlation analysis was made between the mean annual flood and physiographic parameters of the watersheds i.e, the watershed area and mean river channel slope, resulting an empirical multiple linear regression equation over the whole Han river basin. For unguaged watershed the flood of a specified return period could be estimated by multiplying the mead flood ratio corresponding the return period with the mean annual flood computed by the empirical formula developed in terms of the watershed area and river channel slope. To verify the applicability of the methodology developed in the present study the floods of various return periods determined for the watershed in the river channel improvement plan formulation by the Ministry of Construction and Transportation(MOCT) were compared with those estimated by the present method. The result proved a resonable agreement up to the watershed area of approximately 2,000k $m^2$. It is suggested that the practice of design flood estimation based on the rainfall-runoff analysis might have to be reevaluated because it involves too much uncertainties in the hydrologic data and rainfall-runoff model calibration.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.165-178
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• 2011

A gigantic ship is constructed by assembling various types of ship blocks, each block being made by cutting and piecing the steel-plates together. The steel-plate piling process as the initial stage of ship construction sorts and manages the steel-plates according to the ship blocks that the steel-plates are used to make. The steel-plate piling process poses some problems such as process delay due to piling errors, safety vulnerability due to the handling of extra heavy-weight objects, and the uncertainty of work plan due to lack of information management in the pile spaces. We constructed a steel-plate piling process system based on the context-aware computing to resolve such problems. We built simulation system that can simulate the piling process and then established a smart space within the system by using tags, sensors and a real-time location system in order to collect context information. Workers receive an appropriate or intelligent service from the system.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.479-484
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• 2007

For calculation of wave field for design of coastal and port structures, generally the wind fields from inland observation record or the predicted waves from deep water wave transformation model are being used. However, for the first case, as we should revise the wave data adopting correcting parameters depending on the distance from the coast and location, it is difficult to extract water waves from wind field. Furthermore, for the second case, because of the calculation which executed under very large grid sizes in the wide domain, the simulation(wave transformation) implied uncertainty in the near shore area and shallow region. So it's difficult to obtain exact data from the simulation. Thus, in this study the calculation of wave field on shallow water is accomplished using the observed data of typhoon 'Maemi' in the Korea Eastern South sea. Moreover, for the accuracy of the calculated wave field, we compared and studied the observed data of wave height and direction on the vicinity of the Ulsan waters. It is proved that the results of this study is more accurate than the existing method with showing ${\pm}1.3%$ difference between observed and calculated wave height distribution in Ulsan waters

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.80-90
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• 2005

Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.699-708
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• 2005

It becomes easy and generalized to track the cellular phone users and vehicles according to the Progress of wireless telecommunication, the spread of network, and the miniaturization of terminal devices. It has been constantly studied to provide location based services to furnish suitable services depending on the positions of customers. Various vehicle tracking and management systems are developed to utilize and manage the vehicle locations to relieve the congestion of traffic and to smooth transportation. However the designed previous work can not evaluated in real world, because most of previous work is only designed not implemented and it is developed for simple model to handle a point, a line, a polygon object. Therefore, we design a moving object query language and implement a vehicle management system to search the positions and trajectories of vehicles and to analyze the cost of transportation effectively. The designed query language based on a SQL can be utilized to get the trajectories between two specific places, the departure time, the arrival time of vehicles, and the predicted uncertainty positions, etc. In addition, the proposed moving object query language for managing transportation vehicles is useful to analyze the cost of trajectories in a variety of moving object management system containing transportation.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.77-85
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• 2020

Currently, life-cycle cost analysis methods are introduced to maintain large infrastructure facilities in Korea. However, there are not many cases in which maintenance models are applied that reflect conditions such as the location of a facility and its surroundings. In order to establish an appropriate maintenance strategy, a cost prediction, deterioration model, and a decision model reflecting uncertainty should be established. In this study, an economic analysis model was developed for long-term cost planning and management based on user decisions based on maintenance methods and judgment criteria for painting specifications applied to power generation structures. The performance of the paintwork was assessed through the paint deterioration test for the application of the economic analysis model, and the results of the economic analysis according to the applied paint specifications (Urethan, polysiloxane, fluorine) were verified by applying the proposed economic analysis model. In this study, it is believed that the selection of the repair cycle and evaluation methods applied with the development model rather than the performance of the painting can be expected to be used as basic data for the maintenance cycle, even if it is not limited to the painting.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.249-259
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• 2018

More than half of annual rainfall occurs in summer season in Korea due to its climate condition and geographical location. A frequency analysis is mostly adopted for designing hydraulic structure under the such concentrated rainfall condition. Among the various distributions, univariate Gumbel distribution has been routinely used for rainfall frequency analysis in Korea. However, the distributional changes in extreme rainfall have been globally observed including Korea. More specifically, the univariate Gumbel distribution based rainfall frequency analysis is often fail to describe multimodal behaviors which are mainly influenced by distinct climate conditions during the wet season. In this context, we purposed a Gumbel mixture distribution based rainfall frequency analysis with a Bayesian framework, and further the results were compared to that of the univariate. It was found that the proposed model showed better performance in describing underlying distributions, leading to the lower Bayesian information criterion (BIC) values. The mixed Gumbel distribution was more robust for describing the upper tail of the distribution which playes a crucial role in estimating more reliable estimates of design rainfall uncertainty occurred by peak of upper tail than single Gumbel distribution. Therefore, it can be concluded that the mixed Gumbel distribution is more compatible for extreme frequency analysis rainfall data with two or more peaks on its distribution.