A powerful tool in computational stochastic mechanics is the stochastic finite element
method (SFEM). SFEM is an extension of the classical deterministic FE approach to the …

Purpose This paper aims to provide a comprehensive review of uncertainty quantification
methods supported by evidence-based comparison studies. Uncertainties are widely …

Stationary systems modelled by elliptic partial differential equations—linear as well as
nonlinear—with stochastic coefficients (random fields) are considered. The mathematical …

Based on the Gegenbauer polynomial expansion theory and regularization method, an
analytical method is proposed to identify dynamic loads acting on stochastic structures …

A Latin hypercube sampling method, including a reduction of spurious correlation in input
data, is suggested for stochastic finite element analysis. This sampling procedure strongly …

We propose a new robust technique for solving a class of linear stochastic partial differential
equations. The solution is approximated by a series of terms, each of which being the …

This paper deals with a short overview on stochastic modeling of uncertainties. We introduce
the types of uncertainties, the variability of real systems, the types of probabilistic …

Stochastic Models of Uncertainties in Computational Mechanics: Front Matter Page 1
Lecture Notes in Mechanics 2 Stochastic Models of Uncertainties in Computational …

This paper focuses on the efficient solution of models defined in high dimensional spaces.
Those models involve numerous numerical challenges because of their associated curse of …

In this study, the quantitative effect of the random distribution of the soil material properties to
the probability density functions of the failure load and displacements is presented. A …