• Title/Summary/Keyword: Dispersion Mean

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EFFECT OF FLOW UNSTEADINESS ON DISPERSION IN NON-NEWTONIAN FLUID IN AN ANNULUS

  • NAGARANI, P.;SEBASTIAN, B.T.
    • Journal of applied mathematics & informatics
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    • v.35 no.3_4
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    • pp.241-260
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    • 2017
  • An analysis is made to study the solute transport in a Casson fluid flow through an annulus in presence of oscillatory flow field and determine how this flow influence the solute dispersion along the annular region. Axial dispersion coefficient and the mean concentration expressions are calculated using the generalized dispersion model. Dispersion coefficient in oscillatory flow is found to be a function of frequency parameter, Schmidt number, and the pressure fluctuation component besides its dependency on yield stress of the fluid, annular gap and time in the case of steady flow. Due to the oscillatory nature of the flow, the dispersion coefficient changes cyclically and the amplitude and magnitude of the dispersion increases initially with time and reaches a non - transient state after a certain critical time. This critical value varies with frequency parameter and independent of the other parameters. It is found that the presence of inner cylinder and increase in the size of the inner cylinder inhibits the dispersion process. This model may be used in understanding the dispersion phenomenon in cardiovascular flows and in particular in catheterized arteries.

Impact of Heterogeneous Dispersion Parameter on the Expected Crash Frequency (이질적 과분산계수가 기대 교통사고건수 추정에 미치는 영향)

  • Shin, Kangwon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.9
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    • pp.5585-5593
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    • 2014
  • This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.

An experimental study on the correlation of hydraulic mean radius and hydrodispersive parameters in rockfill porous media (자갈 다공성매질에서 수리평균반경과 수리분산 매개변수의 상관성에 관한 실험적 연구)

  • Han, Ilyeong;Lee, Jaejoung;Kim, Gyoo Bum
    • Journal of Korea Water Resources Association
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    • v.54 no.11
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    • pp.863-873
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    • 2021
  • The mechanical dispersion which dominates solute transport in porous media is caused by the difference in flow velocity within pores. Longitudinal dispersion coefficient and longitudinal dispersivity that are hydro-dispersive parameters of advection-dispersion equation can only be obtained by experiment. Hydraulic mean radius that represents the amount and intensity of flowing water within pores can be obtained by the formula using the factors for physical properties. A slug injection test was conducted and a power type empirical formula for obtaining a longitudinal dispersivity using a hydraulic mean radius in rockfill porous media was derived. It is possible to obtain the longitudinal dispersivity depending on transport distance because it contains a formula for a scale constant, and expected to be applicable to waterways filled with homogeneous gravel and small flow rate.

Extended Quasi-likelihood Estimation in Overdispersed Models

  • Kim, Choong-Rak;Lee, Kee-Won;Chung, Youn-Shik;Park, Kook-Lyeol
    • Journal of the Korean Statistical Society
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    • v.21 no.2
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    • pp.187-200
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    • 1992
  • Samples are often found to be too heterogeneous to be explained by a one-parameter family of models in the sense that the implicit mean-variance relationship in such a family is violated by the data. This phenomenon is often called over-dispersion. The most frequently used method in dealing with over-dispersion is to mix a one-parameter family creating a two parameter marginal mixture family for the data. In this paper, we investigate performance of estimators such as maximum likelihood estimator, method of moment estimator, and maximum quasi-likelihood estimator in negative binomial and beta-binomial distribution. Simulations are done for various mean parameter and dispersion parameter in both distributions, and we conclude that the moment estimators are very superior in the sense of bias and asymptotic relative efficiency.

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Fluid Particle Dispersion in a Turbulent Channel Flow (난류 채널 유동에서의 유체 입자 분산)

  • Choi Jung-Il;Lee Changhoon
    • Proceedings of the KSME Conference
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    • 2002.08a
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    • pp.803-806
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    • 2002
  • The dispersion of Lagrangian fluid particles in a turbulent channel flow is studied by a direct numerical simulation. Four points Hermite interpolation in the homogeneous direction and Chebyshev polynomials in the inhomogeneous direction is adopted by assesing the acceleration of fluid particles. In order to characterize the inhomogeneous Lagrangian statistics, accurate single particle Lagrangian statistics are obtained along the wall normal direction. Integral time scales of Lagrangian velocity can be normalized by Eulerian mean shear stresses.

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A Study on Sensitivity of Pollutant Dispersion to Inflow Wind Speed and Turbulent Schmidt Number in a Street Canyon (도시 협곡에서 유입류 풍속과 난류 슈미트수에 대한 대기오염물질 확산의 민감도 연구)

  • Wang, Jang-Woon;Kim, Jae-Jin
    • Atmosphere
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    • v.25 no.4
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    • pp.659-667
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    • 2015
  • In this study, sensitivity of inflow wind speed and turbulent Schmidt number to pollutant dispersion in an urban street canyon is investigated, by comparing CFD-simulated results to wind-tunnel results. For this, we changed systematically inflow wind speed at the street-canyon height ($1.5{\sim}10.0m\;s^{-1}$ with the increment of $0.5m\;s^{-1}$) and turbulent Schmidt number (0.2~1.3 with interval of 0.1). Also, we performed numerical experiments under the conditions that turbulent Schmidt numbers selected with the magnitude of mean kinetic energy at each grid point were assigned in the street canyon. With the increase of the inflow wind speed, the model underestimated (overestimated) pollutant concentration in the upwind (downwind) side of the street canyon because of the increase of pollutant advection. This implies that, for more realistic reproduction of pollutant dispersion in urban street canyons, large (small) turbulent Schmidt number should be assigned for week (strong) inflow condition. In the cases of selectively assigned turbulent Schmidt number, mean bias remarkably decreased (maximum 60%) compared to the cases of constant turbulent Schmidt number assigned. At week (strong) inflow wind speed, root mean square error decreases as the area where turbulent Schmidt number is selectively assigned becomes large (small).

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

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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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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Discrimination of Out-of-Control Condition Using AIC in (x, s) Control Chart

  • Takemoto, Yasuhiko;Arizono, Ikuo;Satoh, Takanori
    • Industrial Engineering and Management Systems
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    • v.12 no.2
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    • pp.112-117
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    • 2013
  • The $\overline{x}$ control chart for the process mean and either the R or s control chart for the process dispersion have been used together to monitor the manufacturing processes. However, it has been pointed out that this procedure is flawed by a fault that makes it difficult to capture the behavior of process condition visually by considering the relationship between the shift in the process mean and the change in the process dispersion because the respective characteristics are monitored by an individual control chart in parallel. Then, the ($\overline{x}$, s) control chart has been proposed to enable the process managers to monitor the changes in the process mean, process dispersion, or both. On the one hand, identifying which process parameters are responsible for out-of-control condition of process is one of the important issues in the process management. It is especially important in the ($\overline{x}$, s) control chart where some parameters are monitored at a single plane. The previous literature has proposed the multiple decision method based on the statistical hypothesis tests to identify the parameters responsible for out-of-control condition. In this paper, we propose how to identify parameters responsible for out-of-control condition using the information criterion. Then, the effectiveness of proposed method is shown through some numerical experiments.

The Mutual Information for Bit-Linear Linear-Dispersion Codes (BLLD 부호의 Mutual Information)

  • Jin, Xiang-Lan;Yang, Jae-Dong;Song, Kyoung-Young;No, Jong-Seon;Shin, Dong-Joon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.10A
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    • pp.958-964
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    • 2007
  • In this paper, we derive the relationship between the bit error probability (BEP) of maximum a posteriori (MAP) bit detection and the bit minimum mean square error (MMSE), that is, the BEP is greater than a quarter of the bit USE and less than a half of the bit MMSE. By using this result, the lower and upper bounds of the derivative of the mutual information are derived from the BEP and the lower and upper bounds are easily obtained in the multiple-input multiple-output (MIMO) communication systems with the bit-linear linear-dispersion (BLLD) codes in the Gaussian channel.

A Study on Odor Dispersion Prediction of Waste Treatment Facilities Using CFD (CFD를 이용한 쓰레기 처리시설의 악취확산 예측에 관한 연구)

  • Kyung, Seo-Kyung;Kim, Kong-Sook;Kim, Byung-Seon
    • 한국태양에너지학회:학술대회논문집
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    • 2009.11a
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    • pp.342-349
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    • 2009
  • The purpose of this study is to estimate efficiently an odor dispersion from waste treatment facility for a crematory and a neighborhood facility, then propose planning, a location of an opening or the arrangement of the trees. Hence, offer a comfortable environment for a resident. For this, first the research data about estimating odor dispersion from waste treatment facility and odor are analyzed, then research an ingredient, characteristic, a direct effect for human and a method of measurement. Second, with on-site survey, check odorimetry and the source of odor dispersion, then apply this to the boundary condition of CFD simulation. Third, analyse by the hour for the 2008 standard weather data of Cheon-an, then apply summer data that odor dispersion is active, winter data relatively slow and an annual mean velocity and wind to the simulation. Even if a crematory and neighborhood facility located on south and north from waste treatment facility are at the low rate, the south and north wind will be applied to the simulation. Fourth, with CFD simulation result, predict an odor dispersion, then propose a solution which is considered an odor dispersion, a location of an opening and the arrangement of the trees. Consequently, this study will have an effect on an environment of a resident.

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