Journal ArticleDOI
Robust and efficient methods for stochastic finite element analysis using Monte Carlo simulation
Reads0
Chats0
TLDR
In this paper, the weighted integral method and the Monte Carlo simulation are used together with innovative solution strategies based on the Preconditioned Conjugate Gradient method (PCG) to produce robust and efficient solutions for the stochastic finite element analysis of space frames.About:
This article is published in Computer Methods in Applied Mechanics and Engineering.The article was published on 1996-08-01. It has received 168 citations till now. The article focuses on the topics: Monte Carlo method & Dynamic Monte Carlo method.read more
Citations
More filters
Journal ArticleDOI
The stochastic finite element method: Past, present and future
TL;DR: A state-of-the-art review of past and recent developments in the SFEM area and indicating future directions as well as some open issues to be examined by the computational mechanics community in the future are provided.
Journal ArticleDOI
Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations
TL;DR: In this paper, the mathematical setting of stationary systems modelled by elliptic partial differential equations with stochastic coefficients (random fields) is investigated and stability with respect to stability.
Journal ArticleDOI
A generalized spectral decomposition technique to solve a class of linear stochastic partial differential equations
TL;DR: A new robust technique for solving stochastic partial differential equations that generalizes the classical spectral decomposition, namely the Karhunen-Loeve expansion, and enables the construction of a relevant reduced basis of deterministic functions which can be efficiently reused for subsequent resolutions.
Journal ArticleDOI
Stochastic modeling of uncertainties in computational structural dynamics—Recent theoretical advances
TL;DR: A short overview on stochastic modeling of uncertainties can be found in this paper, where the authors introduce the types of uncertainties, the variability of real systems, the type of probabilistic approaches, the representations for the stochastically models of uncertainties.
Journal ArticleDOI
Latin Hypercube Sampling for Stochastic Finite Element Analysis
Anders Olsson,Göran Sandberg +1 more
TL;DR: A Latin hypercube sampling method, including a reduction of spurious correlation in input data, is suggested for stochastic finite element analysis and offers the same general applicability as the standard Monte Carlo sampling method but is superior in computational efficiency.
References
More filters
Book
Stochastic Finite Elements: A Spectral Approach
Roger Ghanem,Pol D. Spanos +1 more
TL;DR: In this article, a representation of stochastic processes and response statistics are represented by finite element method and response representation, respectively, and numerical examples are provided for each of them.
Journal ArticleDOI
Random Fields: Analysis and Synthesis.
J. K. Ord,Erik H. Vanmarcke +1 more
TL;DR: The purpose of this book is to bring together existing and new methodologies of random field theory and indicate how they can be applied to these diverse areas where a "deterministic treatment is inefficient and conventional statistics insufficient."
Book
Random fields, analysis and synthesis
TL;DR: In this paper, the authors review the classical theory of multidimensional random processes and introduce basic probability concepts and methods in the random field context and give a concise amount of second-order analysis of homogeneous random fields in both the space-time domain and the wave number-frequency domain.
Journal ArticleDOI
Simulation of Stochastic Processes by Spectral Representation
Journal ArticleDOI
Probabilistic Modeling of Soil Profiles
TL;DR: In this paper, the authors proposed a technique of modeling the statistical character of soil profiles, which provides a format for quantifying the information gathered during site investigation and testing, about the subsurface conditions at a site.