• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.339-347
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• 2008

The penetration of the probe produces the excess pore pressure due to the disturbance. The objective of this study is to evaluate the disturbance zone by using the dissipation of the excess pore water pressure, which was generated due to the penetration of the penetrometer with different size. The CPT, DMT and FVP (Field Velocity Probe) are adopted for in-situ tests. The tests are carried out in the construction site of north container pier of Busan new port, Korea where is accelerating the consolidation settlement using plastic board drains (PBD) and surcharges by crushed gravels. The coefficient of consolidation $(C_h)$ and soil properties are deduced by the laboratory test. The in-site tests are performed after the predrilling the surcharge zone at the point of 90% degree of consolidation. To minimize the penetration effect, the horizontal distance between penetration tests is 3m, the change of the pore pressure is monitored at the fixed depth of 24m. The coefficient of consolidation $(C_h)$ and the $t_{50}s$ are calculated based on the laboratory test and the in-situ data, respectively. The equvalent radi based on the $t_{50}$ shows that the FVP and the DMT produce the smallest and the greatest equivalent radi, respectively.

• 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 Geosynthetics Society
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• v.23 no.3
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• pp.15-22
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• 2024

Predicting ground settlement during the improvement of soft ground and the construction of a structure is an crucial factor. Numerous studies have been conducted, and many prediction equations have been proposed to estimate settlement. Settlement can be calculated using the compression index of clay. In this study, data on water content, void ratio, liquid limit, plastic limit, and compression index from the Busan New Port area were collected to construct a dataset. Correlation analysis was conducted among the collected data. Machine learning algorithms, including Random Forest, Neural Network, Linear Regression, Ada Boost, and Gradient Boosting, were applied using the Orange mining program to propose compression index prediction models. The models' results were evaluated by comparing RMSE and MAPE values, which indicate error rates, and R² values, which signify the models' significance. As a result, water content showed the highest correlation, while the plastic limit showed a somewhat lower correlation than other characteristics. Among the compared models, the AdaBoost model demonstrated the best performance. As a result of comparing each model, the AdaBoost model had the lowest error rate and a large coefficient of determination.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.6
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• pp.785-795
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• 2018

The International Maritime Organization (IMO) has recognized the risk of hull fouling and announced '2011 Guidelines for the control and management of ship's biofouling to minimize the transfer of invasive aquatic species'and is planning international regulations to enforce them in the future. In this study, to effectively respond to future international regulation, we introduce the case of leading countries related to management of hull fouling and also investigate environmental risk assessment techniques for in-water cleaning. Australia and New Zealand, the leading countries in hull fouling management, have established hull fouling regulations through biological and chemical risk assessment based on in-water cleaning scenarios. Most European countries without their government regulation have been found to perform in-water cleaning in accordance with the IMO's hull fouling regulations. In the Republic of Korea, there is no domestic law for hull fouling organisms, and only approximately 17 species of marine ecological disturbance organisms, are designated and managed under the Marine Ecosystem Law. Since in-water cleaning is accompanied by diffusion of alien species and release of chemical substances into aquatic environments, results from biological as well as chemical risk assessment are performed separately, and then evaluation of in-water cleaning permission is judged by combining these two results. Biological risk assessment created 40 codes of in-water cleaning scenarios, and calculated Risk Priority Number (RPN) scores based on key factors that affect intrusion of alien species during in-water cleaning. Chemical risk assessment was performed using the MAMPEC (Marine Antifoulant Model to Predict Environmental Concentrations), to determine PEC and PNEC values based on copper concentration released during in-water cleaning. Finally, if the PEC/PNEC ratio is >1, it means that chemical risk is high. Based on the assumption that the R/V EARDO ship performs in-water cleaning at Busan's Gamcheon Port, biological risk was estimated to be low due to the RPN value was <10,000, but the PEC/PNEC ratio was higher than 1, it was evaluated as impossible for in-water cleaning. Therefore, it will be necessary for the Republic of Korea to develop the in-water cleaning technology by referring to the case of leading countries and to establish domestic law of ship's hull fouling management, suitable for domestic harbors.