• Title/Summary/Keyword: perturbation based stochastic finite element method

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Perturbation Based Stochastic Finite Element Analysis of the Structural Systems with Composite Sections under Earthquake Forces

  • Cavdar, Ozlem;Bayraktar, Alemdar;Cavdar, Ahmet;Adanur, Suleyman
    • Steel and Composite Structures
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    • v.8 no.2
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    • pp.129-144
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    • 2008
  • This paper demonstrates an application of the perturbation based stochastic finite element method (SFEM) for predicting the performance of structural systems made of composite sections with random material properties. The composite member consists of materials in contact each of which can surround a finite number of inclusions. The perturbation based stochastic finite element analysis can provide probabilistic behavior of a structure, only the first two moments of random variables need to be known, and should therefore be suitable as an alternative to Monte Carlo simulation (MCS) for realizing structural analysis. A summary of stiffness matrix formulation of composite systems and perturbation based stochastic finite element dynamic analysis formulation of structural systems made of composite sections is given. Two numerical examples are presented to illustrate the method. During stochastic analysis, displacements and sectional forces of composite systems are obtained from perturbation and Monte Carlo methods by changing elastic modulus as random variable. The results imply that perturbation based SFEM method gives close results to MCS method and it can be used instead of MCS method, especially, if computational cost is taken into consideration.

Reliability-based stochastic finite element using the explicit probability density function

  • Rezan Chobdarian;Azad Yazdani;Hooshang Dabbagh;Mohammad-Rashid Salimi
    • Structural Engineering and Mechanics
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    • v.86 no.3
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    • pp.349-359
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    • 2023
  • This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

A Study on the Stochastic Finite Element Method for Dynamic Problem of Nonlinear Continuum

  • Wang, Qing;Bae, Dong-Myung
    • Journal of Ship and Ocean Technology
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    • v.12 no.2
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    • pp.1-15
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    • 2008
  • The main idea of this paper introduce stochastic structural parameters and random dynamic excitation directly into the dynamic functional variational formulations, and developed the nonlinear dynamic analysis of a stochastic variational principle and the corresponding stochastic finite element method via the weighted residual method and the small parameter perturbation technique. An interpolation method was adopted, which is based on representing the random field in terms of an interpolation rule involving a set of deterministic shape functions. Direct integration Wilson-${\theta}$ Method was adopted to solve finite element equations. Numerical examples are compared with Monte-Carlo simulation method to show that the approaches proposed herein are accurate and effective for the nonlinear dynamic analysis of structures with random parameters.

Stochastic finite element analysis of structural systems with partially restrained connections subjected to seismic loads

  • Cavdar, Ozlem;Bayraktar, Alemdar;Cavdar, Ahmet;Kartal, Murat Emre
    • Steel and Composite Structures
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    • v.9 no.6
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    • pp.499-518
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    • 2009
  • The present paper investigates the stochastic seismic responses of steel structure systems with Partially Restrained (PR) connections by using Perturbation based Stochastic Finite Element (PSFEM) method. A stiffness matrix formulation of steel systems with PR connections and PSFEM and MCS formulations of structural systems are given. Based on the formulations, a computer program in FORTRAN language has been developed, and stochastic seismic analyses of steel frame and bridge systems have been performed for different types of connections. The connection parameters, material and geometrical properties are assumed to be random variables in the analyses. The Kocaeli earthquake occurred in 1999 is considered as a ground motion. The connection parameters, material and geometrical properties are considered to be random variables. The efficiency and accuracy of the proposed SFEM algorithm are validated by comparison with results of Monte Carlo simulation (MCS) method.

A Study on the Stochastic Finite Element Method Based on Variational Approach (변분법을 이용한 확률론적 유한요소법에 관한 연구)

  • Bae, Dong-Myung;Kim, Kyung-Yull
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.32 no.4
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    • pp.432-446
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    • 1996
  • A stochastic Hamilton variational principle(SHVP) is formulated for dynamic problems of linear continuum. The SHVP allows incorporation of probabilistic distributions into the finite element analysis. The formulation is simplified by transformation of correlated random variables to a set of uncorrelated random variables through a standard eigenproblem. A procedure based on the Fourier analysis and synthesis is presented for eliminating secularities from the perturbation approach. In addition to, a method to analyse stochastic design sensitivity for structural dynamics is present. A combination of the adjoint variable approach and the second order perturbation method is used in the finite element codes. An alternative form of the constraint functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The algorithms developed can readily be adapted to existing deterministic finite element codes. The numerical results for stochastic analysis by proceeding approach of cantilever, 2D-frame and 3D-frame illustrates in this paper.

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Structural Optimization Using Stochastic Finite Element Second-Order Perturbation Method (확률 유한요소 이차섭동법을 사용한 구조물 최적설계)

  • 임오강;이병우
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.8
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    • pp.1822-1831
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    • 1995
  • A general formulation of the design optimization problem with the random parameters is presented here. The formulation is based on the stochastic finite element second-order perturbation method ; it takes into full account of the stress and displacement constraints together with the rates of change of the random variables. A method of direct differentiation for calculating the sensitivity coefficients in regard to the governing equation and the second-order perturbed equation is derived. A gradient-based nonlinear programming technique is used to solve the problem. The numerical results are specifically noted, where the stiffness parameter and external load are treated as random variables.

Stochastic finite element method homogenization of heat conduction problem in fiber composites

  • Kaminski, Marcin
    • Structural Engineering and Mechanics
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    • v.11 no.4
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    • pp.373-392
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    • 2001
  • The main idea behind the paper is to present two alternative methods of homogenization of the heat conduction problem in composite materials, where the heat conductivity coefficients are assumed to be random variables. These two methods are the Monte-Carlo simulation (MCS) technique and the second order perturbation second probabilistic moment method, with its computational implementation known as the Stochastic Finite Element Method (SFEM). From the mathematical point of view, the deterministic homogenization method, being extended to probabilistic spaces, is based on the effective modules approach. Numerical results obtained in the paper allow to compare MCS against the SFEM and, on the other hand, to verify the sensitivity of effective heat conductivity probabilistic moments to the reinforcement ratio. These computational studies are provided in the range of up to fourth order probabilistic moments of effective conductivity coefficient and compared with probabilistic characteristics of the Voigt-Reuss bounds.

Stochastic bending characteristics of finite element modeled Nano-composite plates

  • Chavan, Shivaji G.;Lal, Achchhe
    • Steel and Composite Structures
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    • v.26 no.1
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    • pp.1-15
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    • 2018
  • This study reported, the effect of random variation in system properties on bending response of single wall carbon nanotube reinforced composite (SWCNTRC) plates subjected to transverse uniform loading is examined. System parameters such as the SWCNT armchair, material properties, plate thickness and volume fraction of SWCNT are modelled as basic random variables. The basic formulation is based on higher order shear deformation theory to model the system behaviour of the SWCNTRC composite plate. A C0 finite element method in conjunction with the first order perturbation technique procedure developed earlier by the authors for the plate subjected to lateral loading is employed to obtain the mean and variance of the transverse deflection of the plate. The performance of the stochastic SWCNTRC composite model is demonstrated through a comparison of mean transverse central deflection with those results available in the literature and standard deviation of the deflection with an independent First Order perturbation Technique (FOPT), Second Order perturbation Technique (SOPT) and Monte Carlo simulation.

Application of the first-order perturbation method to optimal structural design

  • Lee, Byung Woo;Lim, O Kaung
    • Structural Engineering and Mechanics
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    • v.4 no.4
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    • pp.425-436
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    • 1996
  • An application of the perturbation method to optimum structural design with random parameters is presented. It is formulated on the basis of the first-order stochastic finite element perturbation method. It also takes into full account the stress, displacement and eigenvalue constraints, together with the rates of change of the random variables. A method for calculating the sensitivity coefficients in regard to the governing equation and the first-order perturbed equation has been derived, by using a direct differentiation approach. A gradient-based nonlinear programming technique is used to solve the problem. The numerical results are specifically noted, where the stiffness parameter and external load are treated as random variables.

Structural Optimization Using Stochastic Finite Element Method (확률 유한요소법을 사용한 구조물 최적설계)

  • 임오강;이병우
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.8
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    • pp.1920-1929
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    • 1994
  • The stochastic finite element method(SFEM) based structural optimal design is presented. Random system response including uncertainties for the design variable is calculated with first order perturbation method. A method for calculating the sensitivity coefficients is developed using the equilibrium equation and first-order perturbed equation. Numerical results are presented for a truss, frame and plate structures with displacement and stress constraints. The sensitivity calculation proposed here is compared with finite difference method. A nonlinear programming technique is used to solve the problem. The procedure is easily incorporated with existing deterministic structural optimization.