• Title/Summary/Keyword: conditional mean

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Characteristization of Spray Combustion and Turbulent Flame Structures in a Typical Diesel Engine Condition (디젤 엔진 운전 조건에서 분무 연소 과정과 난류 화염 구조 특성에 대한 해석)

  • Lee, Young-J.;Huh, Kang-Y.
    • Journal of the Korean Society of Combustion
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    • v.14 no.3
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    • pp.29-36
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    • 2009
  • Simulation is performed to analyze the characteristics of turbulent spray combustion in a diesel engine condition. An extended Conditional Moment Closure (CMC) model is employed to resolve coupling between chemistry and turbulence. Relevant time and length scales and dimensionless numbers are estimated at the tip and the mid spray region during spray development and combustion. The liquid volume fractions are small enough to support validity of droplets assumed as point sources in two-phase flow. The mean scalar dissipation rates (SDR) are lower than the extinction limit to show flame stability throughout the combustion period. The Kolmogorov scales remain relatively constant, while the integral scales increase with decay of turbulence. The chemical time scale decreases abruptly to a small value as ignition occurs with subsequent heat release. The Da and Ka show opposite trends due to variation in the chemical time scale. More work is in progress to identify the spray combustion regimes.

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Flamelet and CMC Modeling for the Turbulent Recirculating Nonpremixed Flames (Flamelet 및 CMC 모델을 이용한 재순환 비예혼합 난류 화염장의 해석)

  • Kim, Gun-Hong;Kang, Sung-Mo;Kim, Yong-Mo;Kim, Seong-Ku
    • 한국연소학회:학술대회논문집
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    • 2004.06a
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    • pp.75-82
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    • 2004
  • The conditional moment closure(CMC) model has been implemented in context with the unstructured-grid finite-volume method which efficiently handle the physically and geometrically complex turbulent reacting flows. The validation cases include a turbulent nonpremixed $CO/H_2/N_2$ Jet flame and a turbulent nonpremixed $H_2/CO$ flame stabilized on an axisymmetric bluff-body burner. In terms of mean flame field, minor species and NO formation, numerical results has the overall agreement with expermental data. The detailed discussion has been made for the turbulence-chemistry interaction and NOx formation characteristics as well as the comparative performance for CMC and flamelet model.

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Coupled Simulation of Common Rail Fuel Injection and Combustion Characteristics in a HSDI Diesel Engine (HSDI 디젤엔진의 연료분사계와 연소현상을 연계한 수치해석)

  • Lee, Suk-Young;Huh, Kang-Yul
    • Journal of the Korean Society of Combustion
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    • v.15 no.1
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    • pp.1-11
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    • 2010
  • In this study, the coupled simulation of fuel injection model and three-dimensional KIVA-3V code was tried to develop an algorism for predicting the effects of varying fuel injection parameter on the characteristics of fuel injection and emissions. The numerical simulations were performed using STAR-CD code in order to calculate the intake air flow, and the combustion characteristics is examined by KIVA-3V code linked with the conditional moment closure(CMC) model to predict mean turbulent reaction rate. Parametric investigation with respect to twelve relevant injection parameters shows that appropriate modification of control chamber orifice diameter, needle valve spring constant and nozzle chamber orifice diameter can significantly reduce NOx and soot emissions. Consequently, it is needed to optimize the fuel injection system to reduce the specific emissions such as NOx and soot.

Estimation for the Exponential ARMA Model (지수혼합 시계열 모형의 추정)

  • Won Kyung Kim;In Kyu Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.239-248
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    • 1994
  • The Yule-Walker estimator and the approximate conditional least squares estimator of the parameter of the EARMA(1, 1) model are obtained. These two estimators are compared by simulation study. It is shown that the approximate conditional least squares estimator is better in the sense of the mean square error than the Yul-Walker estimator.

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Goodness-of-fit test for mean and variance functions

  • Jung, Sin-Ho;Lee, Kee-Won
    • Journal of the Korean Statistical Society
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    • v.26 no.2
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    • pp.199-210
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    • 1997
  • Using regression methods based on quasi-likelihood equation, one only needs to specify the conditional mean and variance functions for the response variable in the analysis. In this paper, an omnibus lack-of-fit test is proposed to test the validity of these two functions. Our test is consistent against the alternative under which either the mean or the variance is not the one specified in the null hypothesis. The large-sample null distribution of our test statistics can be approximated through simulations. Extensive numerical studies are performed to demonstrate that the new test preserves the prescribed type I error probability. Power comparisons are conducted to show the advantage of the new proposal.

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A Stay Time Optimization Model Emergency Medical Center (EMC) (응급의료센터 체류시간 최적화)

  • Kim, Eun-Joo;Lim, Ji-Young;Ryu, Jeong-Soon;Cho, Sun-Hee;Bae, Na-Ri;Kim, Sang-Suk
    • Journal of Home Health Care Nursing
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    • v.18 no.2
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    • pp.81-87
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    • 2011
  • Purpose: The aim of this study was to estimate optimization model of stay time in EMC. Methods: Data were collected at an EMC in a hospital using medical records from June to August in 2007. The sample size was 8,378. The data were structured by stay time for doctor visit, decision making, and discharge from EMC. Descriptive statistics were used to find out general characteristics of patients. Average mean and quantile regression models were adopted to estimate optimized stay time in EMC. Results: The stay times in EMC were highly skewed and non-normal distributions. Therefore, average mean as an indicator of optimal stay time was not appropriate. The total stay time using conditional quantile regression model was estimated about 110 min, that was about 166 min shorter than estimated time using average mean. Conclusion: According to these results, we recommend to use a conditional quantile regression model to estimate optimal stay time in EMC. We suggest that this results will be used to develop a guideline to manage stay time more effectively in EMC.

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A Method for Selecting Ground Motions Considering Target Response Spectrum Mean, Variance and Correlation - I Algorithm (응답 스펙트럼의 평균과 분산, 상관관계를 모두 고려한 지반운동 선정 방법 - I 알고리즘)

  • Han, Sang Whan;Ha, Seong Jin;Cho, Sun Wook
    • Journal of the Earthquake Engineering Society of Korea
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    • v.20 no.1
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    • pp.55-62
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    • 2016
  • It is important to select an accurate set of ground motions when conducting linear and nonlinear response history analyses of structures. This study proposes a method for selecting ground motions from a ground motion library with response spectra that match the target response spectrum mean, variance and correlation structures. This study also has addressed the determination of an appropriate value for the weight factor of a correlation structure. The proposed method is conceptually simple and straightforward, and does not involve a simulation algorithm. In this method, a desired number of ground motions are sequentially selected from first to last. The proposed method can be also used for selecting ground motions with response spectra that match the conditional spectrum. The accuracy and efficiency of the proposed procedure are verified with numerical examples.

Optimal selection of detection threshold for tracking systems (추적 시스템을 위한 최적 검출 문턱값 선택)

  • 정영헌
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.1155-1158
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    • 1999
  • In this paper, we consider the optimal control of detection threshold to minimize the conditional mean-square state estimation error for the probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the closed-form optimal detection threshold. This results are very useful for real-time implemenation.

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Nonparametric Stock Price Prediction (비모수 주가예측 모형)

  • Choi, Sung-Sup;Park, Joo-Hean
    • The Korean Journal of Financial Management
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    • v.12 no.2
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    • pp.221-237
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    • 1995
  • When we apply parametric models to the movement of stock prices, we don't know whether they are really correct specifications. In the paper, any prior conditional mean structure is not assumed. By applying the nonparametric model, we see if it better performs (than the random walk model) in terms of out-of-sample prediction. An interesting finding is that the random walk model is still the best. There doesn't seem to exist any form of nonlinearity (not to mention linearity) in stock prices that can be exploitable in terms of point prediction.

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ROC Curve for Multivariate Random Variables

  • Hong, Chong Sun
    • Communications for Statistical Applications and Methods
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    • v.20 no.3
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    • pp.169-174
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    • 2013
  • The ROC curve is drawn with two conditional cumulative distribution functions (or survival functions) of the univariate random variable. In this work, we consider joint cumulative distribution functions of k random variables, and suggest a ROC curve for multivariate random variables. With regard to the values on the line, which passes through two mean vectors of dichotomous states, a joint cumulative distribution function can be regarded as a function of the univariate variable. After this function is modified to satisfy the properties of the cumulative distribution function, a ROC curve might be derived; moreover, some illustrative examples are demonstrated.