• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1261-1272
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• 2018

It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.

• Korean Journal of Ecology and Environment
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• v.52 no.3
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• pp.202-209
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• 2019

The primary productivity and production rate of photosynthetic pigment of periphyton and phytoplankton were estimated using a $^{13}C$ stable labeling technique in May 2011, in the waterfront of Lake Paldang. Primary productivity of periphyton ($28.15mgC\;m^{-2}\;d^{-1}$) was higher than phytoplankton production ($0.14mgC\;m^{-2}\;d^{-1}$). The net production rates of photosynthetic pigments(Chl a and Fucoxanthin) of periphyton were $2.53ngC\;m^{-2}\;d^{-1}$ and $0.12ngC\;m^{-2}\;d^{-1}$, respectively. On the other hand, the net production rate of pigments on phytoplankton (Chl a : $0.023ngC\;m^{-2}\;d^{-1}$, Fucoxanthin: $0.002ngC\;m^{-2}\;d^{-1}$) was lower than that of periphyton. Specific production rates of individual pigments of phytoplankton to the total primary productivity indicate the predominance of diatom (Fucoxanthin) species in phytoplankton assemblage in Lake Paldang. The net individual production rate of pigments by $^{13}C$ tracer was a useful tool to estimate the contribution of each phytoplankton class for total primary productivity, and it is possible to calculate the seasonal contribution of each phytoplankton class to the total primary productivity in the aquatic ecosystems. This study is the first report on photosynthetic pigment production rates of periphyton and phytoplankton.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.383-390
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• 2020

Since the dynamic behaviors of liquid storage tanks on flexible soil are significantly influenced by the fluid-structure-soil interaction (FSSI), its effects must be rigorously considered for accurate earthquake analysis and seismic design of the storage system. In this study, dynamic analysis is performed for a rectangular liquid storage tank on flexible soil, and its dynamic characteristics are examined by rigorously considering the effects of FSSI. The hydrodynamic force and the interaction force between the structure and soil are evaluated using the finite-element approach. In the evaluations, mid-point integrated finite elements and viscous dampers are considered for energy radiation into the infinite soil. The effective earthquake force is then obtained from free-field analysis. It is thus demonstrated that the earthquake responses of the rectangular liquid storage tank on flexible soil are significantly influenced by the FSSI.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.113-120
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• 2021

The wave-propagation phenomenon in an infinite medium has been used to describe the physics in many fields of engineering and natural science. Analytical or numerical methods have been developed to obtain solutions to problems related to the wave-propagation phenomenon. Energy radiation into infinite regions must be accurately considered for accurate solutions to these problems; hence, various numerical and mechanical models as well as boundary conditions have been developed. This paper proposes a new boundary condition that can be applied to scalar-wave or horizontally-polarized shear-wave (or SH-wave) propagation problems in layered waveguides. A governing equation is obtained for the SH waves by applying finite-element discretization in the vertical direction of the waveguide and subsequently modified to derive the boundary condition for the infinite region of the waveguide. Using the orthogonality of the eigenmodes for the SH waves in a layered waveguide, the new boundary condition is shown to be equivalent to the existing root-finding absorbing boundary condition; further, the accuracy is shown to increase with the degree of the new boundary condition, and its stability can be proven. The accuracy and stability are then demonstrated by applying the proposed boundary condition to wave-propagation problems in layered waveguides.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.141-152
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• 2022

As interest increases related to the development of eco-friendly energy, the offshore wind turbine market is growing at an increasing rate every year. In line with this, the demand for an installation vessel with large scaled capacity is also increasing rapidly. The wind turbine installation vessel (WTIV) is a fixed penetration of the spudcan in the sea-bed to install the wind turbine. At this time, a review of the spudcan is an important issue regarding structural safety in the entire structure system. In the study, we analyzed the current procedure suggested by classification of societies and new procedures reflect the new loading scenarios based on reasonable operating conditions; which is also verified through FE-analysis. The current procedure shows that the maximum stress is less than the allowable criteria because it does not consider the effect of the sea-bed slope, the leg bending moment, and the spudcan shape. However, results of some load conditions as defined by the new procedure confirm that it is necessary to reinforce the structure to required levels under actual pre-load conditions. Therefore, the new procedure considers additional actual operating conditions and the possible problems were verified through detailed FE-analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.394-401
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• 2021

The construction of new renewable energy facilities is steadily increasing every year. In particular, the offshore wind farm market, which has abundant development scalability and a high production coefficient, is growing rapidly. The southwest sea has the highest possible offshore wind power potential, and related projects are to be promoted. This study presents a basic design procedure by the EUROCODE and considers structural safety in the development of an effective of shore wind foundation in the clay layer. In a previous study, the wind power generator of 5MW class was the main target, but the 8MW of wind turbine generator, which meets the technical trend of the wind turbine market in the Southwest sea, was selected as the standard model. Furthermore, a foundation that fulfills the geological conditions of the Southwest sea was developed. The structural safety of this foundation was verified using finite element method. Moreover, structural safety was secured by proper reinforcement from the initial design. Based on the results of this study, structural safety check for various types of foundations is possible in the future. Additionally, specialized structural design and evaluation guidance were also established.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.209-227
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• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

• Environmental and Resource Economics Review
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• v.31 no.1
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• pp.113-139
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• 2022

The iron and steel industry is a manufacturing industry with the largest greenhouse gases emissions and has a great ripple effect on the national economy as a core material industry. This study internationally compared the decoupling patterns of greenhouse gases emissions in the iron and steel industry from 1990 to 2019, focusing on Korea, Japan, and Germany. In particular, unlike previous studies that considered only fuel combustion emissions, this study considered all fuel combustion emissions, industrial process emissions, and indirect emissions from the use of electricity and heat. As a result of the analysis, Korea is interpreted as expansive coupling, Japan as decoupling, and Germany as unclear. Therefore, the decoupling path that the Korean iron and steel industry should take should not be in Germany, but in the form of seeking a decoupling method similar to Japan or more effective than Japan. In addition, this study considered the characteristics of the iron and steel industry as much as possible and presented the causes of the decoupling analysis results and implications for the Korean iron and steel industry through comparison with Japan and Germany. In particular, four factors were suggested as factors which has promoted decoupling in Japan: high value-added of Japanese iron and steel products, development of energy efficiency technology in the Japanese iron and steel industry, strategic M&A of the Japanese iron and steel industry, and maintaining competitiveness according to the closed distribution structure of Japanese iron and steel products. The Korean iron and steel industry should also use the case of Japan as a benchmark to further increase added value through quality uprade and product diversification of iron and steel products, while at the same time making efforts to fundamentally reduce greenhouse gas emissions through the development of new technologies.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.