• Title/Summary/Keyword: Probability density distribution

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Probabilistic Fatigue Crack Growth Analysis under Random Loading (불규칙 하중하의 확률론적 피로균열 성장 해석)

  • Song, Sam-Hong;Chang, Doo-Soo
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.1
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    • pp.192-200
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    • 1994
  • The methodology of a simple probabilistic fatigue crack under random loading is proposed. Using the crack closure concept, the crack opening stress is assumed to be constant during random loading. The loading history was analyzed to determine the probability density functions, probability distribution functions and other related parameters for the probabilistic fatigue crack growth analysis. Fatigue crack growth using the exisiting available data was predicted by the proposed probabilistic analysis and compared with experimental data.

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Matter Density Distribution Reconstruction of Local Universe with Deep Learning

  • Hong, Sungwook E.;Kim, Juhan;Jeong, Donghui;Hwang, Ho Seong
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.53.4-53.4
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    • 2019
  • We reconstruct the underlying dark matter (DM) density distribution of the local universe within 20Mpc/h cubic box by using the galaxy position and peculiar velocity. About 1,000 subboxes in the Illustris-TNG cosmological simulation are used to train the relation between DM density distribution and galaxy properties by using UNet-like convolutional neural network (CNN). The estimated DM density distributions have a good agreement with their truth values in terms of pixel-to-pixel correlation, the probability distribution of DM density, and matter power spectrum. We apply the trained CNN architecture to the galaxy properties from the Cosmicflows-3 catalogue to reconstruct the DM density distribution of the local universe. The reconstructed DM density distribution can be used to understand the evolution and fate of our local environment.

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Application of Probability Density Function in SFEM and Corresponding Limit Value (추계론적 유한요소해석에서의 확률밀도함수 사용과 수렴치)

  • Noh Hyuk-Chun
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2006.04a
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    • pp.857-864
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    • 2006
  • Due to the difficulties in numerical generation of random fields that satisfy not only the probabilistic distribution but the spectral characteristics as well. it is relatively hard to find an exact response variability of a structural response with a specific random field which has its features in the spatial and spectral domains. In this study. focusing on the fact that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for in-plane and plate bending structures. In this procedure, the probability density function is used directly resulting in a semi-exact solution for the random field in the state of random variable. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density functions.

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Wind energy assessment at complex terrain using mixture probability distribution (혼합확률분포를 이용한 복잡지형의 풍력자원 평가)

  • Song, Ho-Sung;Kwon, Soon-Duck
    • Journal of the Korean Solar Energy Society
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    • v.33 no.2
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    • pp.18-27
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    • 2013
  • This paper presents a method for assessing the wind energy potential at complex terrain using probability distribution. And the proper probability models of the parameters estimating the wind energy are presented. Finally a mixture-Weibull determined by numerical methods procedure are proposed to assess the probability distribution of the energy potential at a site. The developed method is applied to the Kwanjungchun Bridge and compared with wind records which the neighboring weather station.

Phase Doppler Measurements and Probability Density Functions in Liquid Fuel Spray (연료분무의 위상도플러 측정과 확률밀도함수의 도출)

  • 구자예
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.4
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    • pp.1039-1049
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    • 1994
  • The intermitternt and transient fuel spray have been investigated from the simultaneous measurement of droplet sizes and velocities by using Phase/Doppler Particle Analyzer(PDPA). Measurement have been done on the spray axis and at the edge of the spray near nozzle at various gas-to-liquid density ratios(.rho./sub g//.rho./sub l/) that ranges from those found in free atmospheric jets to conditions typical of diesel engines. Probability density distributions of the droplet size and velocity were obtained from raw data and mathematical probability density functions which can fit the experimental distribations were extracted using the principle of maximum likelihood. In the near nozzle region on the spray axis, droplet sizes ranged from the lower limit of the measurement system to the order of nozzle diameter for all (.rho./sub g/ /.rho./sub l/) and droplet sizes tended to be small on the spray edge. At the edge of spray, average droplet velocity peaked during needle opening and needle closing. The rms intensity is greatly incresed as the radial distance from the nozzle is increased. The probability density function which can best fit the physical breakage process such as breakup of fuel drops is exponecially decreasing log-hypebolic function with 4 parameters.

Estimation of Probability Density Function of Tidal Elevation Data (조위자료의 확률밀도함수 추정)

  • Hong Yeon Cho;Jeong Shin Taek;Oh Young Min
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.16 no.3
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    • pp.152-161
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    • 2004
  • Double-peak normal distribution function was suggested as the probability density function of the tidal elevation data in Korean coastal zone. Frequency distribution analysis was carried out using hourly tidal elevation data of the ten tidal gauging stations, i.e., Incheon, Kunsan, Mokpo, Cheju, Yeosu, Masan, Gadeokdo, Pusan, Pohang, and Sokcho which were served through the Internet Homepage by the National Ocean Research Institute. Based on the RMS error and $R^2$ value comparison analysis, it was found that this suggested function as the probability density function of the tidal elevation data was found to be more appropriate than the normal distribution function. The parameters of the double-peak function were estimated optimally using Levenberg-Marquardt method which was modified from the Newton method. The estimated parameters were highly correlated with the non-tidal constants of the tidal gauging stations.

On Tail Probabilities of Continuous Probability Distributions with Heavy Tails (두꺼운 꼬리를 갖는 연속 확률분포들의 꼬리 확률에 관하여)

  • Yun, Seokhoon
    • The Korean Journal of Applied Statistics
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    • v.26 no.5
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    • pp.759-766
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    • 2013
  • The paper examines several classes of probability distributions with heavy tails. An (asymptotic) expression for tail probability needs to be known to understand which class a given probability distribution belongs to. It is usually not easy to get expressions for tail probabilities since most absolutely continuous probability distributions are specified by probability density functions and not by distribution functions. The paper proposes a method to obtain asymptotic expressions for tail probabilities using only probability density functions. Some examples are given to illustrate the proposed method.

Probability-Based Active Control Using Structure Energy (구조물의 에너지를 이용한 확률에 기초한 능동제어)

  • Min, Kyung-Won;Hwang, Jae-Seung;Lee, Sang-Hyun;Lan Chung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.47-55
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    • 2003
  • This paper Presents active control algorithm using probability density function of structural energy. It is assumed that the structural energy under excitation has Rayleigh probability distribution. This assumption is based on the fact that Rayleigh distribution satisfies the condition that the structural energy is always positive and the occurrence probability of minimum energy is zero. The magnitude of control force is determined by the probability that the structural energy exceeds the specified target critical energy, and the sign of control force is determined by Lyapunov controller design method. Proposed control algorithm shows much reduction of peak responses under seismic excitation compared to LQR controller, and it can consider control force limit in the controller design. Also, chattering problem which sometimes occurs in Lyapunov controller can be avoided.

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Application of probabilistic method to determination of aerodynamic force coefficients on tall buildings

  • Yong Chul Kim;Shuyang Cao
    • Wind and Structures
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    • v.36 no.4
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    • pp.249-261
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    • 2023
  • Aerodynamic force coefficients are generally prescribed by an ensemble average of ten and/or twenty 10-minute samples. However, this makes it difficult to identify the exact probability distribution and exceedance probability of the prescribed values. In this study, 12,600 10-minute samples on three tall buildings were measured, and the probability distributions were first identified and the aerodynamic force coefficients corresponding to the specific non-exceedance probabilities (cumulative probabilities) of wind load were then evaluated. It was found that the probability distributions of the mean and fluctuating aerodynamic force coefficients followed a normal distribution. The ratios of aerodynamic force coefficients corresponding to the specific non-exceedance probabilities (Cf,Non) to the ensemble average of 12,600 samples (Cf,Ens), which was defined as an adjusting factor (Cf,Non/Cf,Ens), were less than 2%. The effect of coefficient of variation of wind speed on the adjusting factor is larger than that of the annual non-exceedance probability of wind load. The non-exceedance probabilities of the aerodynamic force coefficient is between PC,nonex = 50% and 60% regardless of force components and aspect ratios. The adjusting factors from the Gumbel distribution were larger than those from the normal distribution.

ON CHARACTERIZATIONS OF THE NORMAL DISTRIBUTION BY INDEPENDENCE PROPERTY

  • LEE, MIN-YOUNG
    • Journal of applied mathematics & informatics
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    • v.35 no.3_4
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    • pp.261-265
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    • 2017
  • Let X and Y be independent identically distributed nondegenerate random variables with common absolutely continuous probability distribution function F(x) and the corresponding probability density function f(x) and $E(X^2)$<${\infty}$. Put Z = max(X, Y) and W = min(X, Y). In this paper, it is proved that Z - W and Z + W or$(X-Y)^2$ and X + Y are independent if and only if X and Y have normal distribution.