• 제목/요약/키워드: Probability Density function

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MEPDF를 이용한 와류 연소실 내부 예혼합 화염의 대 와동 모사 (Large Eddy Simulation of Turbulent Premixed Flame in a Swirled Combustor Using Multi-environment Probability Density Function approach)

  • 김남수;김용모
    • 한국연소학회지
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    • 제22권3호
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    • pp.29-34
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    • 2017
  • The multi-environment probability density function model has been applied to simulate a turbulent premixed flame in a swirl combustor. To realistically account for the unsteady flow motion inside the combustor, the formulations are derived for the large eddy simulation. The Flamelet generated manifolds is utilized to simplify a multi-dimensional composition space with reasonable accuracy. The sub grid scale mixing is modeled by the interaction by exchange with the mean mixing model. To validate the present approach, the simulation results are compared with experimental data in terms of mean velocity, temperature, and species mass fractions.

가상확률밀도함수를 사용하여 Max(N, T, D) 운5방침이 적용되는 조정가능한 M/G/1 대기모형의 busy period의 기대값 유도 (Derivation of the Expected Busy Period U sing its Pseudo Probability Density Function for a Controllable M/G/l Queueing Model Operating Under the Max (N, T, D) Policy)

  • 이한교;오현승
    • 산업경영시스템학회지
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    • 제31권4호
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    • pp.86-92
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    • 2008
  • The expected busy period for the controllable M/G/1 queueing model operating under the triadic Max (N, T, D) policy is derived by using a new concept so called "the pseudo probability density function." In order to justify the proposed approaches for the triadic policy, well-known expected busy periods for the dyadic policies are recovered from the obtained result as special cases.

손상패턴의 확률밀도함수에 따른 구조물 손상추정 (Structural Damage Assessment Using the Probability Distribution Model of Damage Patterns)

  • 조효남;이성칠;오달수;최윤석
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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    • pp.357-365
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    • 2003
  • The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

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수평 응축관내 2상유동양식의 판별에 관한 연구 (Identification of Two-phase Flow Patterns in a Horizontal Tubular Condenser)

  • 이상천;한용운;신현승;이형돈
    • 설비공학논문집
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    • 제5권1호
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    • pp.65-72
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    • 1993
  • An experiment has been carried out to identify flow patterns in a horizontal condensing flow with R-113. Characteristics of flow patterns were determined based upon a statistical analysis of differential pressure fluctuations at an orifice. The probability density function and power spectral density function of instantaneous pressure drop curves for various flow conditions were obtained. In comparison to the results of air-water flows, the flow patterns in a condensing flow such as annular, wavy, slug and plug could be identified. The experimental data determined by this technique were compared with the flow pattern maps suggested by other investigators. The result indicates that the statistical characteristics of differential pressure fluctuations at an orifice may be a useful tool for identifying flow patterns both in condensing flows and in adiabatic two-phase flows.

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Notes on the Ratio and the Right-Tail Probability in a Log-Laplace Distribution

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.1171-1177
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    • 2007
  • We consider estimation of the right-tail probability in a log-Laplace random variable, As we derive the density of ratio of two independent log-Laplace random variables, the k-th moment of the ratio is represented by a special mathematical function. and hence variance of the ratio can be represented by a psi-function.

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기상변수들의 확률밀도함수(PDF)에 따른 CalTOX모델을 이용한 BTEX 인체노출량 및 인체위해성 평가 연구 (Human Exposure to BTEX and Its Risk Assessment Using the CalTOX Model According to the Probability Density Function in Meteorological Input Data)

  • 김옥;송영호;최진하;박상현;박창용;이민우;이진헌
    • 한국환경보건학회지
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    • 제45권5호
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    • pp.497-510
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    • 2019
  • Objectives: The aim of this study was to secure the reliability of using the CalTOX model when evaluating LADD (or ADD) and Risk (or HQ) among local residents for the emission of BTEX (Benzene, Toluene, Ethylbenzene, Xylene) and by closely examining the difference in the confidence interval of the assessment outcomes according to the difference in the probability density function of input variables. Methods: The assessment was made by dividing it according to the method ($I^{\dagger}$) of inputting the probability density function in meteorological variables of the model with log-normal distribution and the method of inputting ($II^{\ddagger}$) after grasping the optimal probability density function using @Risk. A T-test was carried out in order to analyze the difference in confidence interval of the two assessment results. Results: It was evaluated to be 1.46E-03 mg/kg-d in LADD of Benzene, 1.96E-04 mg/kg-d in ADD of Toluene, 8.15E-05 mg/kg-d in ADD of Ethylbenzene, and 2.30E-04 mg/kg-d in ADD of Xylene. As for the predicted confidence interval in LADD and ADD, there was a significant difference between the $I^{\dagger}$ and $II^{\ddagger}$ methods in $LADD_{Inhalation}$ for Benzene, and in $ADD_{Inhalation}$ and ADD for Toluene and Xylene. It appeared to be 3.58E-05 for risk in Benzene, 3.78E-03 for HQ in Toluene, 1.48E-03 for HQ in Ethylbenzene, and 3.77E-03 for HQ in Xylene. As a result of the HQ in Toluene and Xylene, the difference in confidence interval between the $I^{\dagger}$ and $II^{\ddagger}$ methods was shown to be significant. Conclusions: The human risk assessment for BTEX was made by dividing it into the method ($I^{\dagger}$) of inputting the probability density function of meteorological variables for the CalTOX model with log-normal distribution, and the method of inputting ($II^{\ddagger}$) after grasping the optimal probability density function using @Risk. As a result, it was identified that Risk (or HQ) is the same, but that there is a significant difference in the confidence interval of Risk (or HQ) between the $I^{\dagger}$ and $II^{\ddagger}$ methods.

Tail Probability Approximations for the Ratio of the Independent Random Variables

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
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    • 제7권2호
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    • pp.189-201
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    • 1996
  • In this paper, we study the saddlepoint approximations for the ratio of independent random variables. In Section 2, we derive the saddlepoint approximation to the density. And in Section 3, we derive two approximation formulae for the tail probability, one by following Daniels'(1987) method and the other by following Lugannani and Rice's (1980). In Section 4, we represent some numerical examples which show that the errors are small even for small sample size.

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Maximization of Zero-Error Probability for Adaptive Channel Equalization

  • Kim, Nam-Yong;Jeong, Kyu-Hwa;Yang, Liuqing
    • Journal of Communications and Networks
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    • 제12권5호
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    • pp.459-465
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    • 2010
  • A new blind equalization algorithm that is based on maximizing the probability that the constant modulus errors concentrate near zero is proposed. The cost function of the proposed algorithm is to maximize the probability that the equalizer output power is equal to the constant modulus of the transmitted symbols. Two blind information-theoretic learning (ITL) algorithms based on constant modulus error signals are also introduced: One for minimizing the Euclidean probability density function distance and the other for minimizing the constant modulus error entropy. The relations between the algorithms and their characteristics are investigated, and their performance is compared and analyzed through simulations in multi-path channel environments. The proposed algorithm has a lower computational complexity and a faster convergence speed than the other ITL algorithms that are based on a constant modulus error. The error samples of the proposed blind algorithm exhibit more concentrated density functions and superior error rate performance in severe multi-path channel environments when compared with the other algorithms.

Nonlinear ship rolling motion subjected to noise excitation

  • Jamnongpipatkul, Arada;Su, Zhiyong;Falzarano, Jeffrey M.
    • Ocean Systems Engineering
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    • 제1권3호
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    • pp.249-261
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    • 2011
  • The stochastic nonlinear dynamic behavior and probability density function of ship rolling are studied using the nonlinear dynamical systems approach and probability theory. The probability density function of the rolling response is evaluated through solving the Fokker Planck Equation using the path integral method based on a Gauss-Legendre interpolation scheme. The time-dependent probability of ship rolling restricted to within the safe domain is provided and capsizing is investigated from the probability point of view. The random differential equation of ships' rolling motion is established considering the nonlinear damping, nonlinear restoring moment, white noise and colored noise wave excitation.

전차동체의 피탄각 결정을 위한 비대칭 방향확률분포 모델 (A Nonsymmetric Model of Directional Probability Variation [DPV] for Tanks)

  • 김의환;장원범;이대일
    • 한국국방경영분석학회지
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    • 제25권1호
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    • pp.55-74
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    • 1999
  • In this study, a nonsymmetric model of directional probability variation (dpv), which is fundamental and conforms well to various moving situations of attacking tanks, is obtained based on the Whittaker's theory. It is shown that it produces the same expression of the probability density function as the Whittaker's under the special moving condition of an attacking tank. Using the derived dpvs, the probability densities for the various cases of some examples are calculated numerically to verify the derived formulas, and compared with other existing symmetrical distributions widely used to grasp characteristics of them. As a result, it is noted that the plots of the probability density function for various cases selected exhibit very different and useful behavioral features. Applying the results with respect to the every tank in the computer simulation of engagement between two tank forces, it is expected that more reasonable shot distributions can be given comparing with other existing symmetrical ones. The derived dpvs may be utilized to decide shot distribution of other weapon systems through small modification.

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