• 한국산림과학회지
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• 제103권1호
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• pp.98-104
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• 2014

본 연구는 산지소유역에서 예측한 토사유실량 모형과 실측한 토사유실량을 비교함으로써 예측모형의 적용성 여부를 검토하였다. 또한, 정량적인 토사량 산정을 위하여 72개의 조사지점별로 각각의 영향인자를 산정하여 토사유실량 모형의 정확도를 높이고자 하였다. 토사유실량 산정에 영향을 주는 인자로는 LS 인자가 영향성이 가장 높은 것으로 나타났다. RUSLE, MUSLE 모형과 실측된 토사유실량의 총량을 비교한 결과, 두 모형은 실측치에 비하여 다소 높은 값을 보였으며, RUSLE 모형이 실측치와 근사한 값을 나타내었다. 조사 지점별 값의 비교에서는 MUSLE 값의 변동계수가 더 낮았으나, 값의 차이가 크지 않았다. 따라서 산지소유역에서의 RUSLE와 MUSLE 모형을 이용한 토사유실량의 예측은 적합한 것으로 보여진다. 또한, 산지소유역에서 토사유실량 예측 정도를 높이기 위해서는 강우사상에 대한 데이터 수집과 기존 토사유실 예측 모형에 사용되는 인자의 보완 및 개선에 대한 연구가 요구된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.529-534
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• 2009

Climate models, both global and regional, have increased in sophistication and are being run at increasingly higher resolutions. The Land Surface Models (LSMs) coupled to these climate models have evolved from simple bucket models to sophisticated Soil-Vegetation-Atmosphere Transfer (SVAT) schemes needed to support complex linkages and processes. However, some underpinnings of terrestrial hydrologic parameterizations so crucial in the predictions of surface water and energy fluxes cause model errors that often manifest as non-linear drifts in the dynamic response of land surface processes. This requires the improved parameterizations of key processes for the terrestrial hydrologic scheme to improve the model predictability in surface water and energy fluxes. The Common Land Model (CLM), one of state-of-the-art LSMs, is the land component of the Community Climate System Model (CCSM). However, CLM also has energy and water biases resulting from deficiencies in some parameterizations related to hydrological processes. This research presents the implementation of a selected set of parameterizations and their effects on the runoff prediction. The modifications consist of new parameterizations for soil hydraulic conductivity, water table depth, frozen soil, soil water availability, and topographically controlled baseflow. The results from a set of offline simulations are compared with observed data to assess the performance of the new model. It is expected that the advanced terrestrial hydrologic scheme coupled to the current CLM can improve model predictability for better prediction of runoff that has a large impact on the surface water and energy balance crucial to climate variability and change studies.

• 한국지반공학회논문집
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• 제20권7호
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• pp.171-181
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• 2004

본 연구는 불포화 상태 전 범위에 대한 사질토의 인장강도 모델화 가능성을 조사하기 위해 실시 되었다. 새로 개발된 직접인장시험기법을 이용하여 인장시험이 실시되었다. 측정된 결과는 Rumpf 및 Schubert가 동일크기의 이상적인 구에 대해 개발한 이론적인 인장강도 모델들에 의한 예측 값과 비교 되었다. 이를 위해 석션-포화실험을 통해 얻어진 흙-수분특성곡선을 이용하여 이론모델에 있어 중요한 요소인 불포화상태(pendular, funicular, capillary) 구분 및 음의 간극수압 값을 산정하는데 사용하였다. Pendular 상태에서 불포화모래의 비선형 거동이 Rumpf의 모델에 의해 적절이 묘사되었다. Funicular 및 capillary상태의 경우, 함수비가 증가함에 따라 인장강도가 증가하다 최고 값이 도달한 후 다시 감소하는 실험 측정치의 경향도 Schubert의 모델에 의해 적절히 묘사되었다. 본 비교 연구는 이상적인 단일 크기의 입자에 대해 개발된 이론적인 모델이 다양한 크기를 갖는 불포화 사질토의 인장강도를 예측할 수 있다는 가능성을 뒷받침해준다.

• Geomechanics and Engineering
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• 제20권3호
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• pp.191-205
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• 2020

Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.

• 한국농공학회논문집
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• 제55권4호
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• pp.1-11
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• 2013

Unsaturated hydraulic conductivity function is one of key parameters to solve the flow phenomena in problems of landslide. Prediction models for hydraulic conductivity function related to soil-water retention curve equations in many geotechnical applications have been still used instead of direct measurement of the hydraulic conductivity function since prediction models from soil-water retention curve equations are attractive for their fast and easy use and low cost. However, many researchers found that prediction models for the hydraulic conductivity function can not predict the hydraulic conductivity exactly in comparison with experimental outputs. This research introduced an inverse analysis to evaluate the hydraulic conductivity function corresponding to experimental output from the flow pump system. Optimisation process was carried out to obtain the hydraulic conductivity function. This research showed that the inverse analysis with flow pump system was suitable to assess the hydraulic conductivity in unsaturated soil, and the prediction models for the hydraulic conductivity were led to the significant discrepancy from actual experimental outputs.

• 한국산림과학회지
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• 제90권1호
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• pp.133-138
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• 2001

토양의 산중화 반응 결과로 나타나는 염기성 양이온의 유실과 Al의 가동성 증가는 산림 쇠퇴징후가 나타난 대기오염 지역의 공통된 특징이다. 따라서 산림토양의 산성화 민감도를 결정짓는 산중화 반응을 보다 용이하게 평가하기 위하여 토양산성도 인자를 이용한 산중화 반응 예측모형을 개발하였다. 조사대상지인 남산, 강화, 울산, 홍천의 토양산성도는 동일 지역순으로 높았으며(P<0.05), 이는 토양칼럼 실험에서 추가 산유입($16.7mmol_c/kg$)에 대한 지역별 총 산중화능($ANC_H$)과 상반된 결과였다. 모든 지역에서 염기치환과 Al 용해가 주된 산중화 기작이었으며, 총 산중화능이 낮은 지역일수록 염기치환 산중화능은 낮은 반면 Al 용해 산중화능이 높게 발휘되었다. 황산이온 흡착에 의한 산중화능은 대조지역인 홍천에서 가장 높았으나 산중화율은 6.4%로 매우 낮은 수준이었다. 토양산성도 인자를 이용하여 토양산중화 반응을 예측하기 위한 단순회귀모형과 다중회귀모형의 수정결정계수는 각각 0.52(P<0.04)와 0.89(P<0.01) 이상으로 이들 회귀모형이 토양산성화 민감도와 관련된 산중화 반응을 예측하는데 보다 용이하게 활용될 것으로 판단되었다.

• International Journal of Concrete Structures and Materials
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• 제8권3호
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• pp.239-249
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• 2014

In this paper, the analysis of a numerical study of pile-soil interaction subjected to axial and lateral loads is presented. An analysis of the composite pile-soil system was performed using the finite difference (FD) software LPILE. Two three dimensional, finite element (FE) models of pile-soil interaction have been developed using Abaqus/Cae and SAP2000 to study the effect of lateral loading on pile embedded in clay. A lateral displacement of 2 cm was applied to the top of the pile, which is embedded into the concrete pile cap, while maintaining a zero slope in a guided fixation. A comparison between the bending moments and lateral displacements along the depth of the pile obtained from the FD solutions and FE was performed. A parametric study was conducted to study the effect of crucial design parameters such as the soil's modulus of elasticity, radius of the soil surrounding the pile in Abaqus/Cae, and the number of springs in SAP2000. A close correlation is found between the results obtained by the FE models and the FD solution. The results indicated that increasing the amount of clay surrounding the piles reduces the induced bending moments and lateral displacements in the piles and hence increases its capacity to resist lateral loading.

• 한국농공학회논문집
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• 제53권4호
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• pp.21-27
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• 2011

Soil stress distribution under loading is one of the important problems in civil engineering. Many models have been proposed to interpret the stress distribution in soil and most models assume that the soil is homogeneous and isotropic. Therefore, the actual stress distribution may be different. In addition, With the increase of the top load, soil stress does not increase linearly. In this study, vertical stress changes in sandy soil according to top load increase were measured through experiments. Experimental results, vertical soil stress due to top load increase showed an initial nonlinear behavior and when the load increases to some extent, vertical soil stress showed a linear behavior. ${\alpha}$ value obtained by existing theories always 1.00. But, ${\alpha}$ value by experiment was observed from 0.91 to 1.22 and ${\alpha}$ value was increased with increasing distance from the loading plate.

• Structural Engineering and Mechanics
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• 제88권3호
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• pp.273-285
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• 2023

This study examines how the interaction between soil and a wind turbine's supporting system affects the optimal design. The supporting system resting on an elastic soil foundation consists of a steel conical tower and a concrete circular raft foundation, and it is subjected to wind loads. The material cost of the supporting system is aimed to be minimized employing various metaheuristic optimization algorithms including teaching-learning based optimization (TLBO). To include the influence of the soil in the optimization process, modified Vlasov and Gazetas elastic soil models are integrated into the optimization algorithms using the application programing interface (API) feature of the structural analysis program providing two-way data flow. As far as the optimal designs are considered, the best minimum cost design is achieved for the TLBO algorithm, and the modified Vlasov model makes the design economical compared with the simple Gazetas and infinitely rigid soil models. Especially, the optimum design dimensions of the raft foundation extremely reduce when the Vlasov realistic soil reactions are included in the optimum analysis. Additionally, as the designated design wind speed is decreased, the beneficial impact of soil interaction on the optimum material cost diminishes.

• 한국토양비료학회지
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• 제40권5호
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• pp.429-434
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• 2007

This study was conducted to estimate site productivity of Quercus acutissima and Quercus mongolica by four forest climatic zones. We used site environmental variables (28 geographical and pedological factors) and site index as a site productivity indicator from nation-wide 23,315 stands. Based on multiple regression analysis between site index and major environmental variables, the best-fit multivaliate models were made by each species and forest climatic zone. Most of site index prediction models by species were regressed with seven to eight factors, including altitude, relief, soil depth, and soil moisture etc. For those models, three evaluation statistics such as mean difference, standard deviation of difference, and standard error of difference were applied to the test data set for the validation of the results. According to the evaluation statistics, it was found that the models by climatic zones and species fitted well to the test data set with relatively low bias and variation. Also having above middle of site index range, total area of productive sites for the two Quercus spp. estimated by those models would be about 6% of total forest area. Northern temperate forest zone and central temperate forest zone had more productive area than southern temperate forest zone and warm temperate forest zone. As a result, it was concluded that the regressive prediction with site environmental variables by climatic zones and species had enough estimation capability of forest site productivity.