• Title/Summary/Keyword: probability density

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Probability density evolution analysis on dynamic response and reliability estimation of wind-excited transmission towers

  • Zhang, Lin-Lin;Li, Jie
    • Wind and Structures
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    • v.10 no.1
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    • pp.45-60
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    • 2007
  • Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.

Temperature distribution analysis of steel box-girder based on long-term monitoring data

  • Wang, Hao;Zhu, Qingxin;Zou, Zhongqin;Xing, Chenxi;Feng, Dongming;Tao, Tianyou
    • Smart Structures and Systems
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    • v.25 no.5
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    • pp.593-604
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    • 2020
  • Temperature may have more significant influences on structural responses than operational loads or structural damage. Therefore, a comprehensive understanding of temperature distributions has great significance for proper design and maintenance of bridges. In this study, the temperature distribution of the steel box girder is systematically investigated based on the structural health monitoring system (SHMS) of the Sutong Cable-stayed Bridge. Specifically, the characteristics of the temperature and temperature difference between different measurement points are studied based on field temperature measurements. Accordingly, the probability density distributions of the temperature and temperature difference are calculated statistically, which are further described by the general formulas. The results indicate that: (1) the temperature and temperature difference exhibit distinct seasonal characteristics and strong periodicity, and the temperature and temperature difference among different measurement points are strongly correlated, respectively; (2) the probability density of the temperature difference distribution presents strong non-Gaussian characteristics; (3) the probability density function of temperature can be described by the weighted sum of four Normal distributions. Meanwhile, the temperature difference can be described by the weighted sum of Weibull distribution and Normal distribution.

Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Levy white-noise

  • Di Paola, Mario;Pirrotta, Antonina;Zingales, Massimiliano
    • Structural Engineering and Mechanics
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    • v.28 no.4
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    • pp.373-386
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    • 2008
  • In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

  • Lee, Jong Kyeom;Kim, Tae Yun;Kim, Hyun Su;Chai, Jang-Bom;Lee, Jin Woo
    • Nuclear Engineering and Technology
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    • v.48 no.5
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    • pp.1280-1290
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    • 2016
  • This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

A Study on the Prediction of Fatigue Life by use of Probability Density Function (확률밀도함수를 이용한 피로균열 발생수명 예측에 관한 연구)

  • 김종호
    • Journal of Advanced Marine Engineering and Technology
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    • v.23 no.4
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    • pp.453-461
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    • 1999
  • The estimation of fatigue life at the design stage is very important in order to arrive at feasible and cost effective solutions considering the total lifetime of the structure and machinery compo-nents. In this study the practical procedure of prediction of fatigue life by use of cumulative damage factors based on Miner-Palmgren hypothesis and probability density function is shown with a $135,000m^3$ LNG tank being used as an example. In particular the parameters of Weibull distribution taht determine the stress spectrum are dis-cussed. At the end some of uncertainties associated with fatigue life prediction are discussed. The main results obtained from this study are as follows: 1. The practical procedure of prediction of fatigue life by use of cumulative damage factors expressed in combination of probability density function and S-N data is proposed. 2. The calculated fatigue life is influenced by the shape parameter and stress block. The conser-vative fatigue design can be achieved when using higher value of shape parameter and the stress blocks divded into more stress blocks.

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Optimal Volume Estimation for Non-point Source Control Retention Considering Spatio-Temporal Variation of Land Surface (지표면의 시공간적 변화를 고려한 비점오염원 저감 저류지 최적용량산정)

  • Choi, Daegyu;Kim, Jin Kwan;Lee, Jae Kwan;Kim, Sangdan
    • Journal of Korean Society on Water Environment
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    • v.27 no.1
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    • pp.9-18
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    • 2011
  • In this study the optimal volume for non-point source control retention is estimated considering spatio-temporal variation of land surface. The 3-parameter mixed exponential probability density function is used to represent the statistical properties of rainfall events, and NRCS-CN method is applied as rainfall-runoff transformation. The catchment drainage area is divided into individual $30m{\times}30m$ cells, and runoff curve number is estimated at each cell. Using the derived probability density function theory, the stormwater probability density function at each cell is derived from the rainfall probability density function and NRCS-CN rainfall-runoff transformation. Considering the antecedent soil moisture condition at each cell and the spatial variation of CN value at the whole catchment drainage area, the ensemble stormwater capture curve is established to estimate the optimal volume for an non-point source control retention. The comparison between spatio-temporally varied land surface and constant land surface is presented as a case study for a urban drainage area.

Statistical comparison of morphological dilation with its equivalent linear shift-invariant system:case of memoryless uniform soruces (무기억 균일 신호원에 대한 수리 형태론적인 불림과 등가 시스템의 통계적 비교)

  • 김주명;최상신;최태영
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.2
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    • pp.79-93
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    • 1997
  • This paper presents a linear shift-invariant system euqivalent to morphological dilation for a memoryless uniform source in the sense of the power spectral density function, and comares it with dialtion. This equivalent LSI system is found through spectral decomposition and, for dilation and with windwo size L, it is shown to be a finite impulse response filter composed of L-1 delays, L multipliers and three adders. Th ecoefficients of the equivalent systems are tabulated. The comparisons of dilation and its equivalent LSI system show that probability density functions of the output sequences of the two systems are quite different. In particular, the probability density functon from dilation of an independent and identically distributed uniform source over the unit interval (0, 1) shows heavy probability in around 1, while that from the equivalent LSI system shows probability concentration around themean vlaue and symmetricity about it. This difference is due to the fact that dilation is a non-linear process while the equivalent system is linear and shift-ivariant. In the case that dikation is fabored over LSI filters in subjective perforance tests, one of the factors can be traced to this difference in the probability distribution.

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Modeling Scheme for Calculating Encounter Probability Versus Minefleld Density (지뢰지대 밀도별 접촉확률 산정 모델링 방안)

  • Baek, Doo-Hyeon;Lee, Sang-Heon
    • Journal of the military operations research society of Korea
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    • v.35 no.2
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    • pp.77-86
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    • 2009
  • The encounter probability graph is measured by the chance(in percent) that a vehicle, blindly moving through a minefield, will detonate a mine. The encounter probability graph versus minefield density is presented in ROK and US Army field manual but this graph is baseless because these data had not been presented as those of live mobility or wargame. In this paper, we verified this graph building procedure model as using computer program. The result values of program are almost like those of graph. Therefore this model for our to suggest have validation, verification that a modeling demand and we convince that this model will be useful for calculating encounter probability of multiple vehicles.

Joint Optimization Algorithm Based on DCA for Three-tier Caching in Heterogeneous Cellular Networks

  • Zhang, Jun;Zhu, Qi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2650-2667
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    • 2021
  • In this paper, we derive the expression of the cache hitting probability with random caching policy and propose the joint optimization algorithm based on difference of convex algorithm (DCA) in the three-tier caching heterogeneous cellular network assisted by macro base stations, helpers and users. Under the constraint of the caching capacity of caching devices, we establish the optimization problem to maximize the cache hitting probability of the network. In order to solve this problem, a convex function is introduced to convert the nonconvex problem to a difference of convex (DC) problem and then we utilize DCA to obtain the optimal caching probability of macro base stations, helpers and users for each content respectively. Simulation results show that when the density of caching devices is relatively low, popular contents should be cached to achieve a good performance. However, when the density of caching devices is relatively high, each content ought to be cached evenly. The algorithm proposed in this paper can achieve the higher cache hitting probability with the same density.

OPTIMAL APPROXIMATION BY ONE GAUSSIAN FUNCTION TO PROBABILITY DENSITY FUNCTIONS

  • Gwang Il Kim;Seung Yeon Cho;Doobae Jun
    • East Asian mathematical journal
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    • v.39 no.5
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    • pp.537-547
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    • 2023
  • In this paper, we introduce the optimal approximation by a Gaussian function for a probability density function. We show that the approximation can be obtained by solving a non-linear system of parameters of Gaussian function. Then, to understand the non-normality of the empirical distributions observed in financial markets, we consider the nearly Gaussian function that consists of an optimally approximated Gaussian function and a small periodically oscillating density function. We show that, depending on the parameters of the oscillation, the nearly Gaussian functions can have fairly thick heavy tails.