Numerical assessment of disorder effects in metal foam core sandwich beams based on a local homogenization procedure

The present study is concerned with a numerical procedure for prediction of uncertainty effects in sandwich structures with disordered cores. The approach is based on probability distributions of different material properties and their spatial correlation which are the results of the multiple homogenization analysis of testing volume elements. In order to illustrate the essential difference in the results of material uncertainties between computations using random fields and a deterministic approach both methods are applied to a single edge clamped sandwich beam with a metal foam core which is loaded by a force at the free end. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Local probabilistic homogenization schemes for assessment of material uncertainties in solid foams

The present study is concerned with a numerical scheme for prediction of the effective properties of solid foams considering their uncertainty. The approach is based on an analysis of a large-scale, statistically representative volume element which is subdivided into small-scale testing volume elements. Application of a standard homogenization scheme to the testing volume elements together with a stochastic evaluation yields a complete probabilistic characterization of the material which may be used for a random field definition of the material behaviour in a macroscopic effective field analysis of foam structures. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

有趣的随机变量和的分布算法

根据实际问题.提出计算随机变量和的分布的两种方法,即多项式相乘法和概率母函数法.     

Simple estimation on effective transport properties of a random composite material with cylindrical fibres

Improved bounds for effective transport properties of a random non-percolated composite with cylindrical fibres are developed by means of the security-spheres approach. The key point of the method is to obtain a solution for a regular composite that can be valid for all values of the volume fractions and properties of the components. For this aim we use the asymptotic homogenization method; a cell problem is solved by a modified version of the boundary shape perturbation technique.      

Simple estimation on effective transport properties of a random composite material with cylindrical fibres

Improved bounds for effective transport properties of a random non-percolated composite with cylindrical fibres are developed by means of the security-spheres approach. The key point of the method is to obtain a solution for a regular composite that can be valid for all values of the volume fractions and properties of the components. For this aim we use the asymptotic homogenization method; a cell problem is solved by a modified version of the boundary shape perturbation technique.     

FE2-Simulations in Elasto-Plasticity using Statistically Similar Representative Volume Elements

In the field of direct homogenization methods large representative volume elements (RVE's) cause a high computational cost, which is indicated by a large number of history variables allocating a large amount of memory. Additionally, a high computation time is necessary to solve the systems of equations on the micro-scale as well as on the macro-scale. In this contribution we focus on random microstructures consisting of a continuous matrix phase with a high number of embedded inclusions with arbitrary morphology. We present a method for the construction of statistically similar representative volume elements (SSRVE's) which are characterized by a much less complexity than usual RVE's in order to obtain an efficient simulation tool. The basic goal of the underlying procedure is to find a SSRVE, where some selected statistical measures describing the inclusion morphology are as close as possible to the ones of the original arbitrary microstructure. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Numerical analysis of uncertainties in the effective material behaviour of disordered structural foams

The present contribution is concerned with a numerical analysis of the uncertainties in the structural response of threedimensional structural foams with partially open cells. The effective thermo mechanical material response is determined by means of an energy based homogenization procedure. Stochastic effects in the geometry and topology of the microstructure are treated by means of a repeated analysis of small-scale representative volume elements with prescribed relative density and prescribed cell size distribution. The results are evaluated by stochastic methods. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Singularity of distributions of random variables given by distributions of elements of the corresponding continued fraction

The structure of the distribution of a random variable for which elements of the corresponding elementary continued fraction are independent random variables is completely studied. We prove that the distribution is pure and the absolute continuity is impossible, give a criterion of singularity, and study the properties of the spectrum. For the distribution of a random variable for which elements of the corresponding continued fraction form a uniform Markov chain, we describe the spectrum, obtain formulas for the distribution function and density, give a criterion of the Cantor property, and prove that an absolutely continuous component is absent.     

A Characterization of Joint Distribution of Two-Valued Random Variables and Its Applications

We obtain an explicit representation for joint distribution of two-valued random variables with given marginals and for a copula corresponding to such random variables. The results are applied to prove a characterization of r-independent two-valued random variables in terms of their mixed first moments. The characterization is used to obtain an exact estimate for the number of almost independent random variables that can be defined on a discrete probability space and necessary conditions for a sequence of r-independent random variables to be stationary.     

A note on runs of geometrically distributed random variables

Recently, Grabner et al. [Combinatorics of geometrically distributed random variables: run statistics, Theoret. Comput. Sci. 297 (2003) 261-270] and Louchard and Prodinger [Ascending runs of sequences of geometrically distributed random variables: a probabilistic analysis, Theoret. Comput. Sci. 304 (2003) 59-86] considered the run statistics of geometrically distributed independent random variables. They investigated the asymptotic properties of the number of runs and the longest run using the corresponding probability generating functions and a Markov chain approach. In this note, we reconsider the asymptotic properties of such statistics using another approach. Our approach of finding the asymptotic distributions is based on the construction of runs in a sequence of m-dependent random variables. This approach enables us to find the asymptotic distributions of many run statistics via the theorems established for m-dependent sequence of random variables. We also provide the asymptotic distribution of the total number of non-decreasing runs and the longest non-decreasing run.     

Local stochastic analysis of the effective material response of disordered two-dimensional model foams

The objective of the present study is a numerical analysis of disorder effects in solid structural foams caused by their random irregular micro structure. Using a strain energy based concept, the effective material response is computed in a probabilistic homogenization based on the analysis of a large scale statistically representative volume element. The stochastic information about the scatter in the material response on the lowest possible level is generated by a subsequent division of the representative volume element in substructures consisting of a single cell wall intersection and parts of the adjacent cell walls. For each of the substructures a homogenization analysis is performed. The results for the local effective stress and strain components are evaluated by means of stochastic methods. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A practical non-parametric copula algorithm for system reliability with correlations

System reliability analysis involving correlated random variables is challenging because the failure probability cannot be uniquely determined under the given probability information. This paper proposes a system reliability evaluation method based on non-parametric copulas. The approximated joint probability distribution satisfying the constraints specified by correlations has the maximal relative entropy with respect to the joint probability distribution of independent random variables. Thus the reliability evaluation is unbiased from the perspective of information theory. The estimation of the non-parametric copula parameters from Pearson linear correlation, Spearman rank correlation, and Kendall rank correlation are provided, respectively. The approximated maximum entropy distribution is then integrated with the first and second order system reliability method. Four examples are adopted to illustrate the accuracy and efficiency of the proposed method. It is found that traditional system reliability method encodes excessive dependence information for correlated random variables and the estimated failure probability can be significantly biased.     

Circular law, extreme singular values and potential theory

Consider the empirical spectral distribution of complex random n×n matrix whose entries are independent and identically distributed random variables with mean zero and variance 1/n. In this paper, via applying potential theory in the complex plane and analyzing extreme singular values, we prove that this distribution converges, with probability one, to the uniform distribution over the unit disk in the complex plane, i.e. the well known circular law, under the finite fourth moment assumption on matrix elements.     

Continuity and Stability of a Quadratic Mixed-Integer Stochastic Program

For the two-stage quadratic stochastic program where the second-stage problem is a general mixed-integer quadratic program with a random linear term in the objective function and random right-hand sides in constraints, we study continuity properties of the second-stage optimal value as a function of both the first-stage policy and the random parameter vector. We also present sufficient conditions for lower or upper semicontinuity, continuity, and Lipschitz continuity of the second-stage problem's optimal value function and the upper semicontinuity of the optimal solution set mapping with respect to the first-stage variables and/or the random parameter vector. These results then enable us to establish conclusions on the stability of optimal value and optimal solutions when the underlying probability distribution is perturbed with respect to the weak convergence of probability measures.     

Iterated probability distributions and extremes with random sample size

In this paper the possible nondegenerated limit distributions for the n-fold mapping of a given probability distribution are considered. If the mapping used for the iteration procedure is a probability generating function of a positive integer-valued random variable then the results can be applied to the max-stability of distributions of random variables with random sample size.     

一类非离散非连续的随机变量的概率分布

本文定义了一类非离散非连续的随机变量的概率分布,使其概率分布与离散型和连续型随机变量的概率分布表示保持一致,并举例求出考研中涉及过的该类型的随机变量的概率分布.     

Fluctuations in the homogenization of semilinear equations with random potentials

We study the stochastic homogenization and obtain a random fluctuation theory for semilinear elliptic equations with a rapidly varying random potential. To first order, the effective potential is the average potential and the nonlinearity is not affected by the randomness. We then study the limiting distribution of the properly scaled homogenization error (random fluctuations) in the space of square integrable functions, and prove that the limit is a Gaussian distribution characterized by homogenized solution, the Green’s function of the linearized equation around the homogenized solution, and by the integral of the correlation function of the random potential. These results enlarge the scope of the framework that we have developed for linear equations to the class of semilinear equations.     

Micromechanical material models for polymer composites through advanced numerical simulation techniques

The paper deals with the determination of macroscopic material properties of polymer composites by meso-mechanical numerical modeling. Focus is laid on the methodology how to build up appropriate representative volume elements (RVE) to describe the microstructure of spherical-particles and fibers reinforced composites and how to apply appropriate 3D boundary conditions. The work includes the comparison of the effective material parameters calculated through numerical homogenization of our FE-models with existing analytical formulations as well as with experimental data. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Scan Statistic Tail Probability Assessment Based on Process Covariance and Window Size

A scan statistic is examined for the purpose of testing the existence of a global peak in a random process with dependent variables of any distribution. The scan statistic tail probability is obtained based on the covariance of the moving sums process, thereby accounting for the spatial nature of the data as well as the size of the searching window. Exact formulas linking this covariance to the window size and the correlation coefficient are developed under general, common and auto covariance structures of the variables in the original process. The implementation and applicability of the formulas are demonstrated on multiple processes of t-statistics, treating also the case of unknown covariance. A sensitivity analysis provides further insight into the variant interaction of the tail probability with the influence parameters. An R code for the tail probability computation and the data analysis is offered within the supplementary material.     

Statistical convergence of a sequence of random variables and limit theorems

In this paper the ideas of three types of statistical convergence of a sequence of random variables, namely, statistical convergence in probability, statistical convergence in mean of order r and statistical convergence in distribution are introduced and the interrelation among them is investigated. Also their certain basic properties are studied.