Fan Yang^1,2,3,*, Jianwei Ren^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 801-814, 2020, DOI:10.32604/cmes.2020.08889 - 12 October 2020

Abstract Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy. More >

Zhuo-Jia Fu^1,2, Wen Chen¹, Qing-Hua Qin^2,3

CMC-Computers, Materials & Continua, Vol.21, No.3, pp. 187-208, 2011, DOI:10.3970/cmc.2011.021.187

Abstract This paper presents a hybrid finite element model (FEM) with a new type of general solution as interior trial functions, named as HGS-FEM. A variational functional corresponding to the proposed general solution is then constructed for deriving the element stiffness matrix of the proposed element model and the corresponding existence of extremum is verified. Then the assumed intra-element potential field is constructed by a linear combination of novel general solutions at the points on the element boundary under consideration. Furthermore, the independent frame field is introduced to guarantee the intra-element continuity. The present scheme inherits More >