• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.2
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• pp.37-49
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• 2024

To date, numerous empirical formulas have been proposed through hydraulic model experiments to predict the wave breaker index, including wave height and depth of wave breaking, due to the inherent complexity of generation mechanisms. Unfortunately, research on the characteristics of wave breaking and the prediction of the wave breaker index for gravel beaches has been limited. This study aims to forecast the wave breaker index for gravel beaches using representative linear-based machine learning techniques known for their high predictive performance in regression or classification problems across various research fields. Initially, the applicability of existing empirical formulas for wave breaker indices to gravel seabeds was assessed. Various linear-based machine learning algorithms were then employed to build prediction models, aiming to overcome the limitations of existing empirical formulas in predicting wave breaker indices for gravel seabeds. Among the developed machine learning models, a new calculation formula for easily computable wave breaker indices based on the model was proposed, demonstrating high predictive performance for wave height and depth of wave breaking on gravel beaches. The study validated the predictive capabilities of the proposed wave breaker indices through hydraulic model experiments and compared them with existing empirical formulas. Despite its simplicity as a polynomial, the newly proposed empirical formula for wave breaking indices in this study exhibited exceptional predictive performance for gravel beaches.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.3
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• pp.267-274
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• 2017

This study discusses the applicability of environmental friendly EVA based butyl rubber self-adhesive waterproof sheet designed to prevent corrosion of large scale pipes used in the water treatment facilities during th water treatment process. The experiments conducted tested the waterproofing sheet's adhesion strength on the steel surface of the pipes and checked for whether the material has the proper response properties against the various environmental conditions. In addition, it the sheet adhered to the steel pipe was to see if the adhesion hold against the water pressure due to the ingress of inflow water. Finally, the waterproofing sheet's adhesion strength was tested on a rusted steel surface to confirm whether the material has the necessary properties to secure stable adhesion strength and prevent corrosion of steel pipes at the same time during the process of installation or maintenance. As a result, the self-adhesive waterproof sheets showed that all attachments in the untreated, long term pressuring, immersion in chemical substance (hydrochloric acid, hypochlorous acid, sodium hydroxide), low temperature ($-20^{\circ}C$) conditions showed a adhesion performance of higher than 1.5N/mm, which is the performance standard of KS F 4934. Also, in the testing to check for the adhesion property against inverse water pressure, it was observed that the adhesion failure did not occur even up to $3.0N/mm^2$ pressure. Also, in the process of assessing the adhesion performance on rusted steel surface, specimens after 12 hours of corrosion treatment was shown to have 2.1N/mm, and specimens after 168 hours of corrosion treatment was shown to have 2.0N/mm adhesion strength performance.

• Journal of Korean Society of Steel Construction
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• v.29 no.2
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• pp.111-122
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• 2017

In this paper, the applicability of a 1900mm-deep concrete-filled U-shaped composite beam to composite ordinary moment frames (C-OMFs) was investigated based on existing test results from smaller-sized specimens and supplemental numerical studies since full-scale seismic testing of such a huge sized beam is practically impossible. The key issue was the web local buckling of concrete-filled U section under negative bending. Based on 13 existing test results compiled, the relationship between web slenderness and story drift capacity was obtained. From this relationship, a 1900mm-deep mega beam, fabricated with 25mm-thick plate was expected to experience the web local buckling at 2% story drift and eventually reach a story drift over 3%, thus much exceeding the requirements of C-OMFs. The limiting width to thickness ratio according to the 2010 AISC Specification was shown to be conservative for U section webs of this study. The test-validated supplemental nonlinear finite element analysis was also conducted to further investigate the effects of the horizontal stiffeners (used to tie two webs of a U section) on web local buckling and flexural strength. First, it is shown that the nominal plastic moment under negative bending can be developed without using the horizontal stiffeners, although the presence of the stiffeners can delay the occurrence of web local buckling and restrain its propagation. Considering all these, it is concluded that the 1900mm-deep concrete-filled U-shaped composite beam investigated can be conservatively applied to C-OMFs. Finally, some useful recommendations for the arrangement and design of the horizontal stiffeners are also recommended based on the numerical results.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.11-21
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• 2000

Tunnelling has been created as a great extent in view of less land space available because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities. In tunnelling, it is often faced that measures are obliged to be taken without confirmation for such abnormality as diverged movement of surrounding rock mass, growing crack of shotcrete and yielding of rockbolts. In this case, it is usually said that the judgments of experienced engineers for the selection of measure are importance and allowed us to get over the situations in many construction sites. But decrease of such experienced engineers need us to develop the new system to assist the selection of measures for the abnormality without any experiences of similar tunnelling sites. In this study, After a lot of tunnelling reinforcement methods were surveyed and the detail application were studied, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.861-874
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• 2012

To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 $km^2$) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.769-781
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• 2007

Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.

• Journal of the Korean Geotechnical Society
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• v.28 no.5
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• pp.41-54
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• 2012

The weathering process of rocks leads to the reduction of geotechnical bearing capacity. The weathering of granite is frequently used to refer to the degradation of geotechnical property in the design and construction of infra-structure. In this study, the range of values of CIA (chemical index of alteration) and the change of mineral compositions by weathering have been analysed with igneous rock, which covers 45.5% in South Korean territory. Several weathering indices were studied for various rocks found in Korea and significant relationships between different indices were delineated via statistical analysis. The applicability of CIA was found to be the most significant among all weathering indicies. The composition of illite, the secondary weathering residual, generally increases for the felsic rock, and swelling clay material is not included. The weathering of felsic rock will follow a sequential process, starting from bed rock, illite, and chlorite to kaoline. The mafic rock will show weathering process, from bed rock, smectite, and chlorite to kaoline. The intermediate rocks such as andesite and tuff will show similar weathering procedure and the composition of kaoline, chlorite, and smectite tends to increase more than that of illite when the mafic rock is dominated. This means the increase of rock material which has high CEC (cation exchange capacity) during secondary weathering process. However, the characteristics of a specific rock cannot be completely analyzed using merely CIA, since it is exclusively based on chemical composition and corresponding alteration. The CIA can be used to quantify the weathering process in a limited range, and further considerations such as rock composition, strength characteristics will be required to configure the comprehensive weathering impact on any specific region.

• Economic and Environmental Geology
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• v.51 no.4
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• pp.381-392
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• 2018

This study examines strategies and implementation plans for commercializing $CO_2$ capture and storage, which is an effective method to achieve the national goal of reducing greenhouse gas. In order to secure cost-efficient business model of $CO_2$ capture and storage, we propose four key strategies, including 1) urgent need to select a large-scale storage site and to estimate realistic storage capacity, 2) minimization of source-to-sink distance, 3) cost-effectiveness through technology innovation, and 4) policy implementation to secure public interest and to encourage private sector participation. Based on these strategies, the implementation plans must be designed for enabling $CO_2$ capture and storage to be commercialized until 2030. It is desirable to make those plans in which large-scale demonstration and subsequent commercial projects share a single storage site. In addition, the plans must be able to deliver step-wised targets and assessment processes to decide if the project will move to the next stage or not. The main target of stage 1 (2019 ~ 2021) is that the large-scale storage site will be selected and post-combustion capture technology will be upgraded and commercialized. The site selection, which is prerequisite to forward to the next stage, will be made through exploratory drilling and investigation for candidate sites. The commercial-scale applicability of the capture technology must be ensured at this stage. Stage 2 (2022 ~ 2025) aims design and construction of facility and infrastructure for successful large-scale demonstration (million tons of $CO_2$ per year), i.e., large-scale $CO_2$ capture, transportation, and storage. Based on the achievement of the demonstration project and the maturity of carbon market at the end of stage 2, it is necessary to decide whether to enter commercialization of $CO_2$ capture and storage. If the commercialization project is decided, it will be possible to capture and storage 4 million tons of $CO_2$ per year by the private sector in stage 3 (2026 ~ 2030). The existing facility, infrastructure, and capture plant will be upgraded and supplemented, which allows the commercialization project to be cost-effective.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.807-819
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• 2013

This study proposes a new methodology for future water balance projection considering climate change by assigning a weight to each scenario instead of inputting future streamflows based on GCMs into a water balance model directly. K-nearest neighbor algorithm was employed to assign weights and streamflows in non-flood period (October to the following June) was selected as the criterion for assigning weights. GCM-driven precipitation was input to TANK model to simulate future streamflow scenarios and Quantile Mapping was applied to correct bias between GCM hindcast and historical data. Based on these bias-corrected streamflows, different weights were assigned to each streamflow scenarios to calculate water shortage for the projection periods; 2020s (2010~2039), 2050s (2040~2069), and 2080s (2070~2099). As a result by applying the proposed methodology to project water shortage over the Korean Peninsula, average water shortage for 2020s is projected to increase to 10~32% comparing to the basis (1967~2003). In addition, according to getting decreased in streamflows in non-flood period gradually by 2080s, average water shortage for 2080s is projected to increase up to 97% (516.5 million $m^3/yr$) as maximum comparing to the basis. While the existing research on climate change gives radical increase in future water shortage, the results projected by the weighting method shows conservative change. This study has significance in the applicability of water balance projection regarding climate change, keeping the existing framework of national water resources planning and this lessens the confusion for decision-makers in water sectors.