• 한국지반공학회논문집
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• 제25권12호
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• pp.13-25
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• 2009

본 연구에서는 확률론적 해석에 지반의 공간적 변동성을 고려하기 위한 해석 절차를 제시하였다. 제안된 방법은 한계평형법을 이용하는 결정론적 해석방법을 지반정수의 불확실성과 공간적 변동성을 고려할 수 있도록 확률론적 사면안정 해석으로 확장한다. 개발된 방법은 랜덤유한요소해석법과 같이 미리 임계파괴면을 가정하지 않으면서도 계산시간을 단축할 수 있다는 장점이 있다. 지정된 입력 확률분포함수와 자기상관함수를 따르는 2차원의 랜덤필드를 생성하기 위하여 Karhunen-Lo$\grave{e}$ve 전개법을 사용하였으며, 생성된 랜덤필드를 이용하여 확률론적 응답을 얻기 위해 Monte Carlo 시뮬레이션을 수행하였다. 개발된 해석기법의 적용성을 검토하고 지반정수의 공간적 변화가 확률론적 안정해석에 미치는 영향을 검토하기 위해 예제해석을 수행하였으며, 해석결과는 제안된 방법이 지반물성의 공간적 변동성에 따른 다양한 사면파괴 형태를 확률론적 사면안정 해석에 효과적으로 고려할 수 있음을 보여준다.

• Earthquakes and Structures
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• 제13권2호
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• pp.193-200
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• 2017

To overcome the difficulty of performing multi-point response spectrum analysis for engineering structures under spatially varying ground motions (SVGM) using the general finite element code such as ANSYS, an approach has been developed by improving the modelling of the input ground motions in the spectral analysis. Based on the stochastic vibration analyses, the cross-power spectral density (c-PSD) matrix is adopted to model the stationary SVGM. The design response spectra are converted into the corresponding PSD model with appropriate coherency functions and apparent wave velocities. Then elements of c-PSD matrix are summarized in the row and the PSD matrix is transformed into the response spectra for a general spectral analysis. A long-span high-pier bridge under multiple support excitations is analyzed using the proposed approach considering the incoherence, wave-passage and site-response effects. The proposed approach is deemed to be an efficient numerical method that can be used for seismic analysis of large engineering structures under SVGM.

• Coupled systems mechanics
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• 제7권3호
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• pp.269-280
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• 2018

Post-earthquake damages investigation in past and recent earthquakes has illustrated that the ground motion spatial variation plays an important role in the structural response of long span bridges. For the structural control of seismic-induced vibrations of cable-stayed bridges, it is extremely important to include the effects of the ground motion spatial variation in the analysis for design of an effective control system. The feasibility and efficiency of different vibration control strategies for the cable-stayed bridge under multiple support excitations have been examined to enhance a structure's ability to withstand earthquake excitations. Comparison of the response due to non-uniform input ground motion with that due to uniform input demonstrates the importance of accounting for spatial variability of excitations. The performance of the optimized designed control systems for uniform input excitations gets worse dramatically over almost all of the evaluation criteria under multiple-support excitations.

• Earthquakes and Structures
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• 제3권6호
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• pp.869-887
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• 2012

Ground motion scaling techniques are actively debated in the earthquake engineering community. Considerations such as what amplitude, over what period range and to what target spectrum are amongst the questions of practical importance. In this paper, the effect of various ground motion scaling approaches are explored using three reinforced concrete prototypical building models of 8, 12 and 20 stories designed to respond nonlinearly under a design level earthquake event in the seismically active Southern California region. Twenty-one recorded earthquake motions are selected using a probabilistic seismic hazard analysis and subsequently scaled using four different strategies. These motions are subsequently compared to spectrally compatible motions. The nonlinear response of a planar frameidealized building is evaluated in terms of plasticity distribution, floor level acceleration and uncorrelated acceleration amplification ratio distributions; and interstory drift distributions. The most pronounced response variability observed in association with the scaling method is the extent of higher mode participation in the nonlinear demands.

• 한국작물학회지
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• 제50권4호
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• pp.221-237
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• 2005

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.

• 한국작물학회지
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• 제50권4호
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• pp.247-255
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• 2005

ice yield and plant growth response to nitrogen (N) fertilizer may vary within a field, probably due to spatially variable soil conditions. An experiment designed for studying the response of rice yield to different rates of N in combination with variable soil conditions was carried out at a field where spatial variation in soil properties, plant growth, and yield across the field was documented from our previous studies for two years. The field with area of 6,600 m2 was divided into six strips running east-west so that variable soil conditions could be included in each strip. Each strip was subjected to different N application level (six levels from 0 to 165kg/ha), and schematically divided into 12 grids $(10m \times10m\;for\;each\;grid)$ for sampling and measurement of plant growth and rice grain yield. Most of plant growth parameters and rice yield showed high variations even at the same N fertilizer level due to the spatially variable soil condition. However, the maximum plant growth and yield response to N fertilizer rate that was analyzed using boundary line analysis followed the Mitcherlich equation (negative exponential function), approaching a maximum value with increasing N fertilizer rate. Assuming the obtainable maximum rice yield is constrained by a limiting soil property, the following model to predict rice grain yield was obtained: $Y=10765{1-0.4704^*EXP(-0.0117^*FN)}^*MIN(I-{clay},\;I_{om},\;I_{cec},\;I_{TN},\; I_{Si})$ where FN is N fertilizer rate (kg/ha), I is index for subscripted soil properties, and MIN is an operator for selecting the minimum value. The observed and predicted yield was well fitted to 1:1 line (Y=X) with determination coefficient of 0.564. As this result was obtained in a very limited condition and did not explain the yield variability so high, this result may not be applied to practical N management. However, this approach has potential for quantifying the grain yield response to N fertilizer rate under variable soil conditions and formulating the site-specific N prescription for the management of spatial yield variability in a field if sufficient data set is acquired for boundary line analysis.

• International Journal of Quality Innovation
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• 제1권1호
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• pp.32-37
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• 2000

In an industrial process, the proper objective is to find the optimal operating conditions with minimum process variability around the target. Vining and Myers(1990) suggest to use the separate model for the mean response and the process varian linear predictor ${\tau}_i={\log}\;{\sigma}^2_i$ is unknown and should be estimated. Noting that the variance of $\hat{{\tau}_i}$ is heterogeneous, another appropriate D-optimality criterion $D_3$ based on the method of generalized least squares is proposed in this paper.

• 품질경영학회지
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• 제25권2호
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• pp.28-46
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• 1997

This paper considers robust design strategies for off-line quality control, with the use of experimental design and response surface methodology, in situations where all products have multiple quality characteristics. These strategies can be developed using the desirability concept of desirability functions to determine the settings of the design factors, not only to get the average performances on target but also to minimize variability around the target values.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.355-355
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• 2018

Natural hydrology systems, including high flow and low flow events, are important for aquatic ecosystem health and are essential for controlling the structure and function of ecological processes in river ecosystems. Ecosystem responses to flow changes have been studied in a variety of ways, but little attention has been given to how episodic typhoons and atmospheric circulation patterns can change these hydrologic regime-ecological response relationships. In this diagnostic study, we use an empirical approach to investigate the salient features of interactions between atmospheric circulation, climate, and runoff in the five major Korean river basins.

• Restorative Dentistry and Endodontics
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• 제44권1호
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• pp.11.1-11.8
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• 2019

In the previous sections, simple linear regression (SLR) 1 and 2, we developed a SLR model and evaluated its predictability. To obtain the best fitted line the intercept and slope were calculated by using the least square method. Predictability of the model was assessed by the proportion of the explained variability among the total variation of the response variable. In this session, we will discuss four basic assumptions of regression models for justification of the estimated regression model and residual analysis to check them.