• International Journal of Naval Architecture and Ocean Engineering
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• 제7권2호
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• pp.227-243
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• 2015

In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear parameters of soil models was investigated by Dynamic Embedment Factor (DEF) concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.

• 한국수자원학회논문집
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• 제35권4호
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• pp.385-395
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• 2002

하천에서의 수질변동을 예측하기 위해 FOEA(First-Order Error-Analysis)와 Monte Carlo 모의를 적용한 추계학적 모형을 개발하였다. 영향메트릭스(Influential matrix)를 이용한 민감도 분석을 실시하여 주요 반응계수를 결정하였고, BFGS(Broyden-Fletcher-Goldfarb-Shanno) 최적화 기법을 사용하여 주요 반응계수 값을 산정하였다. 본 모형을 확정론적 수질해석과 동일한 실제 하도구간에 적용하여 추계학적 수질해석을 실시하였고, 그 결과는 확정론적 해석결과와 잘 일치하였다. 유량과 수질, 반응계수 등에 포함된 불확실도가 하류단의 불확실도에 끼치는 영향을 산정하기 위해 상류단과 지류의 유량 및 수질에 대한 불확실도, 그리고 반응계수의 불확실도에 대한 분석과정이 모형에 포함되었다. 모의수행 결과로부터 각 변수들이 가지고 있는 불확실도가 총 불확실도에 끼치는 영향에 대한 기여도를 산정 할 수 있었다.

• 한국환경과학회지
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• 제15권2호
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• 한국자동차공학회논문집
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• 제10권1호
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• pp.59-66
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• 2002

This paper presents the process of the needle lift estimation ova common-rail injector fur HSDI(High Speed Direct Injection) diesel engines. A nonlinear mathematical model of dynamic behaviors of common-rail injector is established at first. Based on the mathematical model of the common-rail injector, the methodology of estimating the injector needle lift is introduced. A sliding mode observer is applied to overcome the model uncertainties. The common-rail injector model and the needle lift estimator are verified by simulations and experiments. The simulation and experimental results indicate that the model outputs are in a good agreement with experimental data, and the proposed nonlinear sliding observer can effectively estimate the needle lift.

• 한국정보통신학회논문지
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• 제3권4호
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• pp.895-905
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• 1999

This paper identifies a linear time-invariant mathematical model of each stand of a five-stand tandem cold mill to design a robust $H_\infty$ thickness controller by applying input and output data sets to N4SID (Numerical algorithms for Subspace State Space System Identification) method. The input-output data sets describe interstand interference in the process of tandem cold rolling and are obtained from a nonlinear simulator of the tandem cold mill. In result, it is shown that the identified model well approximates the nonlinear model than a Taylor linearized model. Furthermore, uncertainties including roll eccentricity and incoming strip variation are quantitatively analyzed from the plot of maximum singular values.

• 한국농공학회논문집
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• 제51권6호
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• pp.11-16
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• 2009

This study is to suggest the SWAT model as inputs for the estimation of CN (Curve number) if we do not have hourly rainfall and runoff data in the ungaged watershed. The daily CNs were estimated by using SWAT model for Chungju dam watershed and the CNs by hourly rainfall and runoff data in the same period with daily CN estimation were also estimated. Then the daily and hourly CNs were compared each other. The CNs by SWAT model were larger than the actual CNs. 7.4% larger in AMC-I, 1.2% in AMC-II, and 6.3% in AMC-III respectively. If we consider various uncertainties in the estimation of CN, the error of 6.8% could be acceptable for the application in the field.

• 대한조선학회 특별논문집
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• 대한조선학회 2005년도 특별논문집
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• pp.206-210
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• 2005

As design trends has changed to have flexible aft hull structure, increased power output and stiffer shafting system, owners and classification societies have more concerned about shaft alignment. In the shaft alignment analysis, there are many uncertainties which are related in propeller generated force, bearing stiffness, crank shaft model and etc. in this study, it is focused on the effect of crankshaft model by comparing between equivalent model and actual crankshaft model.

• 제어로봇시스템학회논문지
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• 제9권7호
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• pp.547-555
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• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• Wind and Structures
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• 제15권1호
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• pp.43-64
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• 2012

Many potential small wind turbine locations are near obstacles such as buildings and shelterbelts, which can have a significant, detrimental effect on the local wind climate. A neural network-based model has been developed which predicts mean wind speed and turbulence intensity at points in an obstacle's region of influence, relative to unsheltered conditions. The neural network was trained using measurements collected in the wakes of 18 scale building models exposed to a simulated rural atmospheric boundary layer in a wind tunnel. The model obstacles covered a range of heights, widths, depths, and roof pitches typical of rural buildings. A field experiment was conducted using three unique full scale obstacles to validate model predictions and wind tunnel measurements. The accuracy of the neural network model varies with the quantity predicted and position in the obstacle wake. In general, predictions of mean velocity deficit in the far wake region are most accurate. The overall estimated mean uncertainties associated with model predictions of normalized mean wind speed and turbulence intensity are 4.9% and 12.8%, respectively.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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• pp.211-214
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• 2002

In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.