• International Journal of Highway Engineering
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• v.10 no.4
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• pp.213-224
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• 2008

Flexible pavement responses to vehicular loading, such as critical stresses and strains, in each pavement layer, could be predicted by the multilayered elastic analysis. However, multilayered elastic theory suffers from major drawbacks including spatial dimension of a numerical model, material properties considered in the analysis, boundary conditions, and ill-presentation of tire-pavement contact shape and stresses. To overcome these shortcomings, three-dimensional finite element (3D FE) models are developed and numerical analyses are conducted to calculate pavement responses to moving load in this study. This paper introduces a methodology for an effective 3D FE to simulate flexible pavement structure. It also discusses the mesh development and boundary condition analysis. Sensitivity analyses of flexible pavement response to loading are conducted. The infinite boundary conditions and time-dependent history of calculated pavement responses are considered in the analysis. This study found that the outcome of 3D FE implicit dynamic analysis of flexible pavement that utilizes appropriate boundary conditions, continuous moving load, viscoelastic hot-mix asphalt model is comparable to field measurements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.8
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• pp.99-104
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• 2005

The major role of a spacecraft structure is to keep and support the spacecraft safely in all the launch environment, on-orbit condition and during ground-transportation and handling. In a satellite development, a structural and thermal model (STM) is developed for two goals ; demonstration of a structural and a thermal stability. In the structure point of view, STM is used to verify the static/dynamic characteristics of structure in the initial stage of development. In this paper, the structure design/analysis of high resolution LEO earth observation satellite STM is described. Also, a low level sine vibration test is performed and compared to the results of finite element analysis.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.6
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• pp.350-360
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• 2016

In order to investigate characteristics of waves and currents varying in space in the Haeundae coast in winter, numerical simulations by using a 2-D spectral wave model(SWAN) and 2-DH hydrodynamic model(Delft3D) were carried out in this study. The results of numerical simulations were validated with the field data collected at several different locations in the study area in February, 2014. From the numerical simulations, it was found that waves and currents were significantly influenced in terms of direction and magnitude by bottom topography characterized by straggling rock crops covered with sea grasses. The coupling of SWAN and Delft3D models also revealed that alongshore currents directing from the east to the west were developed in the nearshore, due to the influence of larger waves with the main incident direction from the east.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.555-563
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• 2011

The goal of image calibration is to find a relation between image and world coordinates. Conventional image calibration uses physical camera model that is able to reflect camera's optical properties between image and world coordinates. In this paper, we try to calibrate images distortion using performance criterion-based polynomial model which assumes that the relation between image and world coordinates can be identified by polynomial equation and its order and parameters are able to be estimated with image and object coordinate values and performance criterion. In order to overcome existing limitations of the conventional image calibration model, namely, over-fitting feature, the performance criterion-based polynomial model is proposed. The efficiency of proposed method can be verified with 2D images that were taken by laser scan camera.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.881-891
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• 2020

In recent years, large-scale development of coastal areas has caused the loss of many lives and extensive property damage in coastal areas, due to wave overtopping caused by high-wave invasion and strong typhoons. However, coastal inundation studies considering the characteristics of domestic coastal areas are insufficient. This study is a methodology study that aimed to reproduce inundation of surge and wave complex elements by applying the ADCSWAN (ADCIRC+SWAN) and FLOW-3D models. In this study, the boundary data (sea level, wave) of the FLOW-3D model was extracted using the ADCSWAN (ADCIRC+SWAN) model and applied as the input value of the FLOW-3D model and a reproduction was created of the Flooding due to surge and overtopping in Busan Marine City when the typhoon Chaba passed. In addition, the existing overtopping empirical equation and the overtopping calculated by the FLOW-3D model were compared, and for coastal inundation, a qualitative verification was performed using the Inundation Trace Map of Land and Geospatial Informatrix Corporation, and the effectiveness of this study was reviewed.

• Composites Research
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• v.34 no.2
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• pp.115-122
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• 2021

SMC(Sheet molding compound) composite is mainly used for forming of vehicle's body. Considering the car accident, it is essential to research the impact behavior and characteristics of materials. It is difficult to identify them because the impact process is completed in a short time. Therefore, the impact damage analysis using FE(finite element) model is required for the impact behavior. The impact damage analysis requires the parameters for the damage model of SMC composite. In this paper, ANN(artificial neural network) technique is applied to obtain the parameters for the damage model of SMC composite. The surrogate model by ANN was constructed with the result in LS-DYNA. By comparing the absorption energy in drop weight test with the result of ANN model, the optimized parameters were obtained. The acquired parameters were validated by comparing the results of the experiment, the FE model and the ANN model.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.131-138
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• 2022

Git's commit message is closely related to the project life cycle, and by this characteristic, it can greatly contribute to cost reduction and improvement of work efficiency by identifying risk factors and project status of project operation activities. Among these related fields, there are many studies that classify commit messages as types of software maintenance, and the maximum accuracy among the studies is 87%. In this paper, the purpose of using a solution using the commit classification model is to design and implement a complex classification model that combines several models to increase the accuracy of the previously published models and increase the reliability of the model. In this paper, a dataset was constructed by extracting automated labeling and source changes and trained using the DistillBERT model. As a result of verification, reliability was secured by obtaining an F1 score of 95%, which is 8% higher than the maximum of 87% reported in previous studies. Using the results of this study, it is expected that the reliability of the model will be increased and it will be possible to apply it to solutions such as software and project management.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.333-340
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• 2023

Efficient prediction of corporate bankruptcy is an important part of making appropriate lending decisions for financial institutions and reducing loan default rates. In many studies, classification models using artificial intelligence technology have been used. In the financial industry, even if the performance of the new predictive models is excellent, it should be accompanied by an intuitive explanation of the basis on which the result was determined. Recently, the US, EU, and South Korea have commonly presented the right to request explanations of algorithms, so transparency in the use of AI in the financial sector must be secured. In this paper, an artificial intelligence-based interpretable classification prediction model was proposed using corporate bankruptcy data that was open to the outside world. First, data preprocessing, 5-fold cross-validation, etc. were performed, and classification performance was compared through optimization of 10 supervised learning classification models such as logistic regression, SVM, XGBoost, and LightGBM. As a result, LightGBM was confirmed as the best performance model, and SHAP, an explainable artificial intelligence technique, was applied to provide a post-explanation of the bankruptcy prediction process.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1577-1589
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• 2023

Recently, the necessity of predicting changes for monitoring ocean is widely recognized. In this study, we performed a time series prediction of remote-sensing reflectance (Rrs), which can indicate changes in the ocean, using Geostationary Ocean Color Imager (GOCI) data. Using GOCI-I data, we trained a multi-scale Convolutional Long-Short-Term-Memory (ConvLSTM) which is proposed in this study. Validation was conducted using GOCI-II data acquired at different periods from GOCI-I. We compared model performance with the existing ConvLSTM models. The results showed that the proposed model, which considers both spatial and temporal features, outperformed other models in predicting temporal trends of Rrs. We checked the temporal trends of Rrs learned by the model through long-term prediction results. Consequently, we anticipate that it would be available in periodic change detection.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.386-392
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• 2024

This paper constructs a precise dynamics model using flightlab, a specialized program for rotor modeling and performance analysis, to simulate urban air mobility (UAM). flightlab is well-suited for detailed modeling of UAM, particularly requiring detailed aerodynamic characteristics under high-altitude and urban wind conditions. The study focuses on implementing and analyzing a lift-cruise UAM model with distributed propulsion using flightlab. The lift-cruise model integrates motors for vertical take-off and fixed-wing flight. Given the limited specific examples of such UAM models in flightlab and challenges in evaluating with conventional fixed-wing or drone models, this research implements and verifies the lift-cruise model using matlab, comparing its performance against flightlab results to validate the modeling approach. This research aims to explore the potential of flightlab for detailed UAM modeling and contribute to technological advancements in future urban transportation.