2012•Advanced materials researchOpen access

A New Method to Solve No-Probabilistic Finite Element Method

Chang Hong Liu, X.C. Qing, Fu‐Zhen Xuan, S.T. Tu

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Abstract

According to the non-probabilistic finite element algorithms, the random finite element equations are translated into the interval finite element equations. Firstly, with the concept of confidence interval in the probability, a interval number can be taken as the random variable with the uniform distribution. Secondly, the uniform random Monte Carlo (MC) finite element method and optimization finite element method are presented. Finally, the example shown, when the numbers of random parameters are small, the two algorithms are all effective. But when numbers of random parameters are large, only the uniform random finite element method has the stabilized solving ability.

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What this paper is about

According to the non-probabilistic finite element algorithms, the random finite element equations are translated into the interval finite element equations. Firstly, with the concept of confidence interval in the probability, a interval number can be taken as the random variable with the uniform distribution. Secondly, the uniform random Monte Carlo (MC) finite element method and optimization finite element method are presented. Finally, the example shown, when the numbers of random parameters are small, the two algorithms are all effective. But when numbers of random parameters are large, only the uniform random finite element method has the stabilized solving ability.

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Available abstract

According to the non-probabilistic finite element algorithms, the random finite element equations are translated into the interval finite element equations. Firstly, with the concept of confidence interval in the probability, a interval number can be taken as the random variable with the uniform distribution. Secondly, the uniform random Monte Carlo (MC) finite element method and optimization finite element method are presented. Finally, the example shown, when the numbers of random parameters are small, the two algorithms are all effective. But when numbers of random parameters are large, only the uniform random finite element method has the stabilized solving ability.

Key concepts: Mixed finite element method, Finite element method, Random element, Extended finite element method, Finite element limit analysis, Mathematics, Smoothed finite element method, Probabilistic logic

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