Response variability of laminate composite plates due to spatially random material parameter

Noh, Hyuk-Chun; Park, Taehyo

doi:10.1016/j.cma.2011.03.020

Cited by 30 publications

(7 citation statements)

References 18 publications

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“…First, the random fields E 1 ; G 12 and G 23 were assumed to be Gaussian fields. However, studies in the composite literature [6,26,27,43] show that these properties exhibit significant non-Gaussian characteristics. Moreover, the material properties E 2 ; m 12 which have been shown to have spatial fluctuations [27] have been assumed to be deterministic.…”

Section: Pc Based Ssfem Formalism As Available In Composite Literaturementioning

confidence: 97%

A data driven polynomial chaos based approach for stochastic analysis of CFRP laminated composite plates

Sasikumar

Venketeswaran

Suresh

et al. 2015

Composite Structures

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Section: Pc Based Ssfem Formalism As Available In Composite Literaturementioning

confidence: 97%

A data driven polynomial chaos based approach for stochastic analysis of CFRP laminated composite plates

Sasikumar

Venketeswaran

Suresh

et al. 2015

Composite Structures

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“…Chen and Soares (2008) [13] proposed a spectral stochastic FEM to study laminated composite plates assuming the elastic and shear moduli as Gaussian random fields. Noh and Park (2011) [91] investigated the response variability of laminate composite plates induced by the spatial randomness of Poisson's ratio that was assumed to follow Gaussian distribution. Noh (2011) [90] also studied the plate response variability due to triple random parameters, i.e.…”

Section: Structural Materials In Civil Engineeringmentioning

confidence: 99%

Advances in Gaussian random field generation: a review

Liu

Sun

et al. 2019

Comput Geosci

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Gaussian (normal) distribution is a basic continuous probability distribution in statistics, it plays a substantial role in scientific and engineering problems that related to stochastic phenomena. This paper aims to review state of the art of Gaussian random field generation methods, their applications in scientific and engineering issues of interest, and open-source software/packages for Gaussian random field generation. To this end, first we briefly introduce basic mathematical concepts and theories in Gaussian random field, then seven commonly-used Gaussian random field generation methods are systematically presented. The basic idea, mathematical framework of each generation method are introduced in detail and comparisons of these methods are summarized. Then representative applications of Gaussian random field in various areas, especially of engineering interest in recent two decades, are reviewed. For readers' convenience, four representative example codes are provided, and several relevant up-to-date open-source software and packages that freely available from the Internet are introduced.

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“…For finite element implementation, it is necessary to discretize such fields into random vector representations. Various methods developed for the discretization of random fields such as Karhunen-Loève expansion [7], nodal point method [8], midpoint method [9], the integration point method [8], a local averaging method [10], a weighted integral method [11,12]. Hyuk Chun Noh [13] developed an SFEM using the weighted integral approach to determine the response variability of in-plane and plate structures with multiple uncertain elastic moduli and Poisson's ratio.…”

Section: Introductionmentioning

confidence: 99%

A static analysis of nonuniform column by stochastic finite element method using weighted integration approach

Hien

2020

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In general, the fluctuation of the elastic modulus of materials is crucial in structural analysis. This paper develops a stochastic finite element method (SFEM) for analyzing a nonuniform column considering the random process in elastic modulus. This random process of elastic modulus is assumed as a one-dimensional Gaussian random field. The weighted integration method is used to discretize the random field and establish the stochastic finite element formulation to compute the first and second moments of displacement fields. The results of the proposed approach are validated with those of the previous study. The response variability of displacement of column and effect of the parameter of the random field is investigated in detail.

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Response variability of laminate composite plates due to spatially random material parameter

Cited by 30 publications

References 18 publications

A data driven polynomial chaos based approach for stochastic analysis of CFRP laminated composite plates

A data driven polynomial chaos based approach for stochastic analysis of CFRP laminated composite plates

Advances in Gaussian random field generation: a review

A static analysis of nonuniform column by stochastic finite element method using weighted integration approach

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