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EN
Knowledge of the distribution quantiles of precipitation maximum amounts is required in many fields concerning engineering design or hydrological risk assessment. When the number of observation years is small, it is not possible to fit the probability distribution function to maximum values and to calculate quantiles. This paper presents a procedure for calculating the quantiles of the probability distribution of daily precipitation maximums over a year using stochastic convergence of distributions. The distribution series of random variables, defined based on the cut-off sample with the elimination of the smallest values, made it possible to determine the quantiles for times series of order α of the distribution. These values were approximated by a function from the exponential class and then extrapolated to obtain quantiles for the distribution of maxima. The resulting quantile estimates, for short time series, were corrected using the kurtosis of the data used for estimation, which leads to a very large error reduction.
4
Content available remote 2-D and 3-D analysis of stochastic, elastic soil medium
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EN
The paper presents a stochastic description of a three-dimensional soil medium and its modelling under strain conditions. The main aim of the paper of the paper is to work out a computational model enabling incorporation of three-dimensional variability of soil properties into the plane strain state analysis. It is assumed that the soil medium is statitically homogeneous and its mechanical behaviours is governed by the linear elasticity theory. It is also assumed that elastic parameters can be modelled as the multidimensional random fields. The strip foundation on a soil layer in the 3-D and the 2-D strain states is analysed. Stochastic 2-D and 3-D finite element methods, based on the Monte Carlo technique, were used. The analysis performed enables determination of the standard deviatios of components of the stress tensor and the displacement vector for the 3-D state, based on the solution for the 2-D plane strain state. Transfer functions between both states are determined.
PL
Artykuł jest kontynuacją pracy [1]. Przedstawiono w nim problemy optymalizacyjne z zakresu inżynierii chemicznej i procesowej rozwiązane przy użyciu metod stochastycznych opisanych w [1]. Były to nieliniowe problemy zawierające tylko zmienne ciągłe lub też zarówno zmienne dyskretne i ciągłe. We wszystkich przypadkach uzyskano wyniki uważane w literaturze za rozwiązanie globalnie optymalne.
EN
The paper presented is a continuation of the work [1]. In this part, optimization problems typical for chemical and process engineering, solved by stochastic methods described in [1] are presented. The nonlinear problems comprising only continuous or both discrete and continuous variables have been treated. In all cases, the results obtained are considered in professional literature as globally optimum solutions.
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