• 제목/요약/키워드: Non Linear Model

검색결과 2,046건 처리시간 0.028초

Mean pressure prediction for the case of 3D unsteady turbulent flow past isolated prismatic cylinder

  • Ramesh, V.;Vengadesan, S.;Narasimhan, J.L.
    • Wind and Structures
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    • 제9권5호
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    • pp.357-367
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    • 2006
  • Unsteady 3D Reynolds Averaged Navier-Stokes (URANS) solver is used to simulate the turbulent flow past an isolated prismatic cylinder at Re=37,400. The aspect ratio of height to base width of the body is 5. The turbulence closure is achieved through a non-linear $k-{\varepsilon}$ model. The applicability of this model to predict unsteady forces associated with this flow is examined. The study shows that the present URANS solver with standard wall functions predicts all the major unsteady phenomena showing closer agreement with experiment. This investigation concludes that URANS simulations with the non-linear $k-{\varepsilon}$ model as a turbulence closure provides a promising alternative to LES with view to study flows having complex features.

원자로내부구조물의 동적해석을 위한 비선형모델 (A Non-linear Model for Dynamic Analysis of Reactor Internals)

  • Myung-J.Jhun;Sang-G.Chang;Song, Heuy-G.
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1993년도 봄 학술발표회논문집
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    • pp.165-172
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    • 1993
  • A non-linear mathematical model has been developed for the dynamic analysis of the reactor internals. The model includes a lumped mass and stiffness with non-linear members such as gap-spring. As hydrodynamic couplings have also been considered in the model, the effect of fluid/structure interaction between internals components due to their immersion in a confining fluid can be studied for the dynamic response analysis. The reactor internals responses for seismic and pipe break excitations have been calculated for the case of with-and without-hydrodynamic couplings.

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Bayes Prediction Density in Linear Models

  • Kim, S.H.
    • Communications for Statistical Applications and Methods
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    • 제8권3호
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    • pp.797-803
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    • 2001
  • This paper obtained Bayes prediction density for the spatial linear model with non-informative prior. It showed the results that predictive inferences is completely unaffected by departures from the normality assumption in the direction of the elliptical family and the structure of prediction density is unchanged by more than one additional future observations.

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Power 모형을 이용한 비정상성 확률강수량 산정 (Estimates the Non-Stationary Probable Precipitation Using a Power Model)

  • 김광섭;이기춘;김병권
    • 한국농공학회논문집
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    • 제56권4호
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    • pp.29-39
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    • 2014
  • In this study, we performed a non-stationary frequency analysis using a power model and the model was applied for Seoul, Daegu, Daejeon, Mokpo sites in Korea to estimate the probable precipitation amount at the target years (2020, 2050, 2080). We used the annual maximum precipitation of 24 hours duration of precipitation using data from 1973 to 2009. We compared results to that of non-stationary analyses using the linear and logistic regression. The probable precipitation amounts using linear regression showed very large increase in the long term projection, while the logistic regression resulted in similar amounts for different target years because the logistic function converges before 2020. But the probable precipitation amount for the target years using a power model showed reasonable results suggesting that power model be able to reflect the increase of hydrologic extremes reasonably well.

문헌 단위 인용 네트워크 내 인용과 중심성 지수 간 관계 추정에 관한 연구 (Curve Estimation among Citation and Centrality Measures in Article-level Citation Networks)

  • 유소영
    • 정보관리학회지
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    • 제29권2호
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    • pp.193-204
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    • 2012
  • 이 연구에서는 인용 및 동시인용 문헌 네트워크에서의 중심성 지수를 사용한 추론 통계 적용의 첫 번째 단계로써 이들 간 관계의 선형성을 살펴보고자 하였다. 703개의 문헌 동시인용 네트워크를 활용하여 인용 빈도, 연결정도 중심성, 인접 중심성, 매개 중심성 간의 4가지 주요 관계의 패턴을 살펴본 결과, 모든 인용 및 중심성 간 관계가 선형모델보다는 비선형적 모델로 더 잘 설명될 수 있음을 통계적으로 확인되었다. 따라서 이들 간의 인과관계에 대한 다중회귀분석과 같은 추론 통계 분석의 기반이 되는 선형성을 확보하기 위해서는 논리적인 기준에 근거한 데이터 변환이나 실제값을 구간값으로 변환하는 과정이 필요하다고 할 수 있다.

Bayesian Estimation Procedure in Multiprocess Non-Linear Dynamic Normal Model

  • Sohn, Joong-Kweon;Kang, Sang-Gil
    • Communications for Statistical Applications and Methods
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    • 제3권1호
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    • pp.155-168
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    • 1996
  • In this paper we consider the multiprocess dynamic normal model with parameters having a time dependent non-linear structure. We develop and study the recursive estimation procedure for the proposed model with normality assumption. It turns out thst the proposed model has nice properties such as insensitivity to outliers and quick reaction to abrupt changes of pattern.

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Large Robust Designs for Generalized Linear Model

  • Kim, Young-Il;Kahng, Myung-Wook
    • Journal of the Korean Data and Information Science Society
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    • 제10권2호
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    • pp.289-298
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    • 1999
  • We consider a minimax approach to make a design robust to many types or uncertainty arising in reality when dealing with non-normal linear models. We try to build a design to protect against the worst case, i.e. to improve the "efficiency" of the worst situation that can happen. In this paper, we especially deal with the generalized linear model. It is a known fact that the generalized linear model is a universal approach, an extension of the normal linear regression model to cover other distributions. Therefore, the optimal design for the generalized linear model has very similar properties as the normal linear model except that it has some special characteristics. Uncertainties regarding the unknown parameters, link function, and the model structure are discussed. We show that the suggested approach is proven to be highly efficient and useful in practice. In the meantime, a computer algorithm is discussed and a conclusion follows.

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Significance of seabed interaction on fatigue assessment of steel catenary risers in the touchdown zone

  • Elosta, Hany;Huang, Shan;Incecik, Atilla
    • Structural Engineering and Mechanics
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    • 제57권3호
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    • pp.403-423
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    • 2016
  • The challenges involved with fatigue damage assessment of steel catenary riser (SCR) in the touchdown zone (TDZ) are primarily due to the non-linear behaviour of the SCR-seabed interaction, considerable uncertainty in SCR-seabed interaction modelling and geotechnical parameters. The issue of fatigue damage induced by the cyclic movements of the SCR with the seabed has acquired prominence with the touch down point (TDP) interaction in the TDZ. Therefore, the SCR-seabed response is critical for reliable estimation of fatigue life in the TDZ. Various design approaches pertaining to the lateral pipe-soil resistance model are discussed. These techniques have been applied in the finite element model that can be used to analyse the lateral SCR-seabed interaction under hydrodynamic loading. This study investigates the sensitivity of fatigue performance to geotechnical parameters through a parametric study. In this study, global analyses are performed to assess the influence of vertical linear seabed springs, the lateral seabed model and the non-linear seabed model, including trench evolution into seabed, seabed normalised stiffness, re-penetration offset parameter and soil suction resistance ratio, on the fatigue life of SCRs in the TDZ.

A Note on Linear Regression Model Using Non-Symmetric Triangular Fuzzy Number Coefficients

  • Hong, Dug-Hun;Kim, Kyung-Tae
    • Journal of the Korean Data and Information Science Society
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    • 제16권2호
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    • pp.445-449
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    • 2005
  • Yen et al. [Fuzzy Sets and Systems 106 (1999) 167-177] calculated the fuzzy membership function for the output to find the non-symmetric triangular fuzzy number coefficients of a linear regression model for all given input-output data sets. In this note, we show that the result they obtained in their paper is invalid.

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Efficient Prediction in the Semi-parametric Non-linear Mixed effect Model

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • 제28권2호
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    • pp.225-234
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    • 1999
  • We consider the following semi-parametric non-linear mixed effect regression model : y\ulcorner=f($\chi$\ulcorner;$\beta$)+$\sigma$$\mu$($\chi$\ulcorner)+$\sigma$$\varepsilon$\ulcorner,i=1,…,n,y*=f($\chi$;$\beta$)+$\sigma$$\mu$($\chi$) where y'=(y\ulcorner,…,y\ulcorner) is a vector of n observations, y* is an unobserved new random variable of interest, f($\chi$;$\beta$) represents fixed effect of known functional form containing unknown parameter vector $\beta$\ulcorner=($\beta$$_1$,…,$\beta$\ulcorner), $\mu$($\chi$) is a random function of mean zero and the known covariance function r(.,.), $\varepsilon$'=($\varepsilon$$_1$,…,$\varepsilon$\ulcorner) is the set of uncorrelated measurement errors with zero mean and unit variance and $\sigma$ is an unknown dispersion(scale) parameter. On the basis of finite-sample, small-dispersion asymptotic framework, we derive an absolute lower bound for the asymptotic mean squared errors of prediction(AMSEP) of the regular-consistent non-linear predictors of the new random variable of interest y*. Then we construct an optimal predictor of y* which attains the lower bound irrespective of types of distributions of random effect $\mu$(.) and measurement errors $\varepsilon$.

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