• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.106-112
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• 2011

This study developed preliminary assessment methodology for priority listing of soil and groundwater contamination sources, considering source characteristics, local environments and risk receptors. Source characteristics were evaluated by scoring relative risk of contamination sources. Local environments were evaluated by scoring annual rainfall, hydraulic conductivity of aquifer, and annual groundwater use. Risk receptors were evaluated by scoring local population, direct distance to surface water, direct distance to drinking-water wells. Scores of each parameter were allocated by analysing distribution of parameter values obtained from government databases. Distributed scores of source characteristics local environments: risk receptors were 12 : 12 : 12. The preliminary assessment scored 0 to 36 for each soil and groundwater sources. Inventory of soil and groundwater sources consisted of 7 categories. This study applied the preliminary assessment methodology to Manan-Gu, Anyang City, Korea. The number of car repair and washing facility was the largest in the contamination source inventory. Petroleum storage facilities showed the highest assessment score. The preliminary assessment methodology also indicated that Anyang-Dong was the priority section among Anyang-Dong, Suksu-Dong, Bakdal-Dong. This study is the first trial for relative ranking soil and groundwater contamination sources by considering source and local characteristics. Therefore, further researches and revision of the preliminary assessment methodology need to be pursued for various applications.

• Ocean Systems Engineering
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• v.6 no.1
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• pp.99-115
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• 2016

In meeting the technical needs for deepwater conditions and overcoming the shortfalls of single-layer pipes for deepwater applications, pipe-in-pipe (PIP) systems have been developed. While, for PIP pipelines directly laid on the seabed or with partial embedment, one of the primary service risks is lateral buckling. The critical axial force is a key factor governing the global lateral buckling response that has been paid much more attention. It is influenced by global imperfections, submerged weight, stiffness, pipe-soil interaction characteristics, et al. In this study, Finite Element Models for imperfect PIP systems are established on the basis of 3D beam element and tube-to-tube element in Abaqus. A parameter study was conducted to investigate the effects of these parameters on the critical axial force and post-buckling forms. These parameters include structural parameters such as imperfections, clearance, and bulkhead spacing, pipe/soil interaction parameter, for instance, axial and lateral friction properties between pipeline and seabed, and load parameter submerged weight. Python as a programming language is been used to realize parametric modeling in Abaqus. Some conclusions are obtained which can provide a guide for the design of PIP pipelines.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.563-565
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• 2005

In this study, a algorithm to estimate Equivalent earth resistivity and Earth parameter using Artificial Neural Network(ANN) was proposed. Structures of the soil are grouped by using SOM algorithm before estimation. Earth parameter and Equivalent earth resistivity are obtained by using BP algorithm. The effectiveness of the proposed algorithm was verified. In the case study. afterwards, the algorithm proposed in this study will be used in more applications and gained more reliability.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.1
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• pp.82-90
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• 2007

In order to analyse the strength problems for an unsaturated soil, it is required to examine closely the characteristics of the parameters of shear strength which was changed with the metric suction and void ratio. To this ends, a triaxial compression test was conducted on the three samples-granular soil, cohesive soil and silty soil. The specimen was made by pressing the static pressure on the mold filled soil and was controled the void ratio with the different compaction ratio. And the test was performed by using the modified apparatus of the triaxial compression tester. The range of matric suction was 0-90 kPa.The measured results for the deviator stress and parameters of shear strength were analysed with the void ratio and the compaction ratio, and they were examined closely the characteristics of the strength for an unsaturated soil.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.191-194
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• 2003

The purpose of this paper was to derive soil-water characteristic curve equation for unsaturated soil. To this end, a series of suction measured test was conducted on the selected 4 kinds of soil which is located in Korea, used the modified pressure plate apparatus. From the test results, it was proved that characteristic curve changes according to grain size distribution, size of void and fine grained soil contents. Residual degree of saturation(Sr) was decreased with void ratio and changed with fine grained soil contents, parameter ${\lambda}$ and hr was increased with void ratio. Soil-water characteristic curve equation based on the test result was suggested by void ratio or grain size distribution.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.5
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• pp.76-86
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• 2007

For the purpose of ground improvement by means of soil flushing systems. Incorporated technique with prefabricated vertical drains have been used for dewatering from fine-grained soils. The laboratory model tests were performed by using the flushing tracer solutions for silty soils and recorded the tracer concentration changes with the elapsed time and flow rates. A mathematical model for prediction of contaminant transport using the PVD technology has been developed. The clean-up times for the predictions on both soil condition indicate more of a sensitivity to the dispersivity parameter than to the extracted flow rate and vertical velocity parameters. Based on the results of the analyses, numerical analysis indicate that the most important factor to the in-situ soil remediation in prefabricated vertical drain system is the effective diameter of contaminated soil.

• Journal of Environmental Science International
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• v.6 no.6
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• pp.697-709
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• 1997

Sequencing Batch Reactor(SBR) experiments for organics and nutrients removal have been conducted to find an optimum anaerobic/anoxic/aerobic cycling time and evaluate the applicability of oxidation-reduction potential(ORP) as a process control parameter. In this study, a 61 bench-scale plant was used and fed with night-soil wastewater in K city which contained TCODcr : 10, 680 mg/l, TBm : 6, 893 mg/l, $NH_4^+-N$ : 1, 609 mg/l, $PO_4^{3-}-P$ : 602 mg/l on average. The cycling time In SBRs was adjusted at 12 hours and 24 hours, and then certainly included anaerobic, aerobic and inoxic conditions. Also, for each cycling time, we performed 3 series of experiment simultaneously which was set up 10 days, 20 days and 30 days as SRT From the experimental results, the optimum cycling time for biological nutrient removal with nlght-soil wastewater was respctively 3hrs, 5hrs, 3hrs(anaerobic-aerobic-anoxic), Nitrogen removal efficiency was 77.9%, 77.9%, 81.7% for each SRT, respectively. When external carbon source was fed in the anoxic phase, ORP-bending point indicating nitrate break point appeared clearly and nitrogen removal efficiency increased as 96.5%, 97.1%, 98.9%. Phosphate removal efficiency was 59.8%, 64.571, 68.6% for each SRT. Also, we finded the applicability of ORP as a process control parameter in SBRs.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.173-182
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• 2005

The Performance of U-tube ground heat exchanger for geothermal heat Pump systems depends on the thermal properties of the soil, as well as grout or backfill materials in the borehole. In-situ tests provide a means of estimating some of these properties. In this study, in-situ thermal response tests were completed on two vertical boreholes, 130 m deep with 62 mm diameter high density polyethylene U-tubes. The tests were conducted by adding a monitored amount of heat to water over a $17\~18$ hour period for each vertical boreholes. By monitoring the water temperatures entering and exiting the loop and heat load, overall thermal conductivity values of grout/soil formation were determined. Two parameter estimation models for evaluation of thermal response test data were compared when applied on the same temperature response data. One model is based on line-source theory and the other is a numerical one-dimensional finite difference model. The average thermal conductivity deviation between measured data and these models is of the magnitude $1\%$ to $5\%$.

• Advances in environmental research
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• v.4 no.3
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• pp.197-210
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• 2015

Hexavalent chromium [Cr (VI)] adsorption on lateritic soil and lateritic soil blended with black cotton (BC) soil, marine clay and bentonite clay were studied in the laboratory using batch adsorption techniques. In the present investigation the natural laterite soil was blended with 10%, 20% and 30% BC soil, marine clay and bentonite clay separately. The interactions on test soils have been studied with respect to the linear, Freundlich and Langmuir isotherms. The linear isotherm parameter, Freundlich and Langmuir isotherm parameters were determined from the batch adsorption tests. The adsorption of Cr (VI) on natural laterite soil and blended laterite soil was determined using double beam spectrophotometer. The distribution coefficients obtained were 1.251, 1.359 and 2.622 L/kg for lateritic soil blended with 10%, 20% and 30% BC soil; 5.396, 12.973 and 48.641 L/kg for lateritic soil blended with marine clay and 5.093, 8.148 and 12.179 L/kg for lateritic soil blended with bentonite clay respectively. The experimental data fitted well to the Langmuir model as observed from the higher value of correlation coefficient. Soil pH and iron content in soil(s) has greater influence on Cr (VI) adsorption. From the study it is concluded that laterite soil can be blended with clayey soils for removing Cr (VI) by adsorption.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.