• 한국주조공학회지
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• 제34권3호
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• pp.107-111
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• 2014

Permeability is the ability of a material to transmit fluid/gases. It is an important material property and it depends on mould parameters such as grain fineness number, clay, moisture, mulling time, and hardness. Modeling the relationships among these variable and interactions by mathematical models is complex. Hence a biologically inspired artificial neural-network technique with a back-propagation-learning algorithm was developed to estimate the permeability of green sand. The developed model was used to perform a sensitivity analysis to estimate permeability. The individual as well as the combined influence of mould parameters on permeability were simulated. The model was able to describe the complex relationships in the system. The optimum process window for maximum permeability was obtained as 8.75-10.5% clay and 3.9-9.5% moisture. The developed model is very useful in understanding various interactions between inputs and their effects on permeability.

• Journal of Biosystems Engineering
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• 제43권4호
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• pp.410-419
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• 2018

Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

• 한국환경과학회지
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• 제30권8호
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• pp.613-619
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• 2021

Soil water enters the atmosphere via evapotranspiration, where it transforms into atmospheric water vapor and plays important role in the surface-atmosphere energy exchange. Soil conditions have a direct influence on the effective rainfall, and initial soil moisture conditions are important for quantitatively evaluating the effective rainfall in a watershed. To examine the sensitivity of the initial saturation to hydrologic outflow, a two-dimensional distributed FLO-2D hydrologic model was applied to a small watershed. The initial saturation was set to 0.3, 0.5, and 0.7 and the obtained results were compared. The Green-ampt model was chosen to calculate the penetration loss. Depending on the initial soil moisture, the peak flow rate varied by up to 60%, and the total water volume in the watershed by approximately 40%.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.147-147
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• 2022

In January 2021 heavy flood affected South Kalimantan with causing many casualties. The heavy rainfall is predicted to be generated due to the ENSO (El Nino-Southern Oscillation). The weak La-Nina mode appeared to generate more convective cloud above the warmed ocean and result in extreme rainfall with high anomaly compared to past historical rainfall event. Subsequently, the antecedent soil moisture distribution showed to have an important role in generating the flood response. Saturated flow and infiltration excess mainly contributed to the runoff generation due to the high moisture capacity. The hydro-meteorological processes in this event were deeply analyzed using the coupled atmospheric model of Weather Research and Forecasting (WRF) and the hydrological model extension (WRF-Hydro). The sensitivity analysis of the flood response to the SST anomaly and the soil moisture capacity also compared. Result showed that although SST and soil moisture are the main contributors, soil moisture have more significant contribution to the runoff generation despite of anomaly rainfall occurred. Model performance was validated using the Global Precipitation Measurement (GPM) and Soil Moisture Operational Products System (SMOPS) and performed reasonably well. The model was able to capture the hydro-meteorological process of atmosphere and hydrological feedbacks in the extreme weather event.

• Computers and Concrete
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• 제33권4호
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• pp.409-423
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• 2024

Using an extensive database, a sensitivity analysis across fifteen machine learning (ML) classifiers was conducted to evaluate the impact of various data manipulation techniques, evaluation metrics, and explainability tools. The results of this sensitivity analysis reveal that the examined models can achieve an accuracy ranging from 72-93% in predicting the fire-induced spalling of concrete and denote the light gradient boosting machine, extreme gradient boosting, and random forest algorithms as the best-performing models. Among such models, the six key factors influencing spalling were maximum exposure temperature, heating rate, compressive strength of concrete, moisture content, silica fume content, and the quantity of polypropylene fiber. Our analysis also documents some conflicting results observed with the deep learning model. As such, this study highlights the necessity of selecting suitable models and carefully evaluating the presence of possible outcome biases.

• Geomechanics and Engineering
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• 제23권3호
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• pp.261-273
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• 2020

This paper presents an efficient method utilizing user-defined computer functional codes to determine the reliability of an embankment slope with spatially varying soil properties in real time. The soils' mechanical properties varied with the soil layers that had different degrees of compaction and moisture content levels. The Latin Hypercube Sampling (LHS) for the degree of compaction and Kriging simulation of moisture content variation were adopted and programmed to predict their spatial distributions, respectively, that were subsequently used to characterize the spatial distribution of the soil shear strengths. The shear strength parameters were then integrated into the Geostudio command file to determine the safety factor of the embankment slope. An explicit metamodal for the performance function, using the Kriging method, was established and coded to efficiently compute the failure probability of slope with varying moisture contents. Sensitivity analysis showed that the proposed method significantly reduced the computational time compared to Monte Carlo simulation. About 300 times LHS Geostudio computations were needed to optimize precision and efficiency in determining the failure probability. The results also revealed that an embankment slope is prone to high failure risk if the degree of compaction is low and the moisture content is high.

• 한국산학기술학회논문지
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• 제10권5호
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• pp.1109-1114
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• 2009

딥 클렌징이 피부타입에 따른 피부 유, 수분변화에 미치는 영향을 알아보고자, 건성 및 지성피부의 20명을 대상으로 스크럽그룹과 효소그룹으로 나누어 주 1회 8주 동안 총 8회 딥 클렌징 관리를 실시하였다. 8회 관리 후 스크럽 그룹은 지성피부에서, 효소는 건성피부에서 유분이 유의하게 변화하였고 두 그룹 모두 피부타입에 따른 수분변화는 나타나지 않았다. 주관적 느낌을 알아보고자 실시한 설문지 결과는 유분변화가 유의한 결과가 나왔고 수분 및 민감도에서는 큰 변화를 느끼지 못하는 것으로 나타났다.

• Journal of Welding and Joining
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• 제31권5호
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• pp.59-63
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• 2013

A bendable electronic module has been developed for a mobile application by using a low-cost roll-to-roll manufacturing process. In flexible embedded electronic module, a thin silicon chip was embedded in a polymer-based encapsulating adhesive between flexible copper clad polyimide layers. To confirm reliability and durability of prototype bendable module, the following tests were conducted: Moisture sensitivity level, thermal shock test, high temperature & high humidity storage test, and pressure cooker tester. Those experiments to induce failure of the module due to temperature variations and moisture are the experiment to verify the reliability. Failure criterion was 20% increase in bump resistance from the initial value. The mechanism of the increase of the bump resistance was analyzed by using non-destructive X-ray analysis and scanning acoustic microscopy. During the pressure cooker test (PCT), delamination occurred at the various interfaces of the bendable embedded modules. To investigate the failure mechanism, moisture diffusion analysis was conducted to the pressure cooker's test. The hygroscopic characteristics of the encapsulating polymeric materials were experimentally determined. Analysis results have shown moisture saturation process of flexible module under high temperature/high humidity and high atmosphere conditions. Based on these results, stress factor and failure mechanism/mode of bendable embedded electronic module were obtained.

• 한국토양비료학회지
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• 제30권4호
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• pp.314-327
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• 1997

점적 관개시 근권에서의 토양 수분 이동 현상을 2차원 원통 좌표를 이용하여 모델링 하였다. 엽면 증산, 다양한 형태의 지면 증발, 관개율의 증가로 인한 지면에서의 물 고임 현상등을 고려하였다. 모델은 유한 차분법을 이용한 수치해로 풀었다. 여러가지 비교의 결과로부터 본 연구에서 개발된 모델은 근권에서의 토양 수분 이동 현상을 잘 묘사한다고 볼 수 있었다. 모델의 민감도 분석을 통해서 몇가지 유익한 사실을 발견하였다. 토양 수분이 연직 방향으로 이동하는 속도가 더 큰 것으로 보아 자동 관개용 토양 수분 측정 센서를 설치할 경우, 관개점의 연직하방이 좋은 측점임을 알 수 있었다. 습윤대의 형태가 단지(pot) 모양으로 되는 것은 지면 증발로 인한것임을 알 수 있었다. 또한, 토양의 포화 수리 전도도가 습윤대의 확산에 큰 영향을 주는 것을 알 수 있었고, 관개 중단 후에도 연직 방향의 확산은 계속됨을 알 수 있었다.

• 대한토목학회논문집
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• 제28권4B호
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• pp.375-381
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• 2008

본 연구에서는 자체 개발한 물리적기반의 격자다층 분포형 홍수유출모형을 이용하여 남강댐유역을 대상으로 유출해석을 하고, 최적 매개변수 산정을 위하여 각 매개변수별 민감도 분석을 실시하였다. 그 중 유출량에 가장 큰 영향을 끼치는 유역의 초기 토양함수 상태 및 포화 투수계수를 중심으로 유출량에 미치는 영향의 정도를 파악하고자 하였다. 강우유출해석의 결과로부터 모형의 적합성을 평가하기 위하여 체적오차의 백분율(VER)과 첨두유량 오차의 백분율(QER)을 이용하여 모형을 평가하였으며, VER과 QER이 각각 16.7%, 6.7%로 나타나 매개변수 보정 전에 비해 약 6% 향상된 결과를 보였다. 매개변수 민감도 분석 결과, 개발된 분포형 모형에서 유출에 가장 큰 영향을 미치는 부분이 토양 조건 중에서 투수계수와 층 분할 비율이라는 것을 알 수 있었고, 분포형모형의 특성상 매개변수의 초기보정 없이도 유량의 크기와 첨두시간 모두 관측값과 비교적 잘 맞는 것을 확인할 수 있었다.