Application of grammatical evolution to coefficient identification problem in two-dimensional elastic problem
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2013, Vol 20, Issue 1
Abstract
Grammatical evolution (GE), which is a kind of evolutionary algorithms, is designed to find a function, an executable program or program fragment that will achieve a good fitness value for the given objective function to be minimized. In this study, GE is applied for the coefficient identification problem of the stiffness matrix in the two-dimensional elastic problem. Finite element analysis of the plate with a circular hole is performed for determining the set of the stress and the strain components. Grammatical evolution determines the coefficient matrix of the relationship between the stress and strain components. The coefficient matrix is compared with Hooke's law in order to confirm the validity of the algorithm. After that, three algorithms are shown for improving the convergence speed of the original GE algorithm.
Authors and Affiliations
Takuya Kuroda, Hideyuki Sugiura, Eisuke Kita
Keywords
Related Articles
- EP ID EP73590
- DOI -
- Views 153
- Downloads 0
Numerical estimation of internal stress relieving in destructive test. (Received in the final form January 18, 2010)
The paper deals with the analysis of residual stress fields in the riveted joint and the estimation of the internal stress magnitude releasing by partial and complete removing of the rivet material. Stress relieving caus...
A time-step insensitive recurrent approach to analyze non-stationary random responses. (Received in the final form October 28, 2008).
The recurrent approach constructed via the stochastic central difference (SCD) is a very fast method for analyzing non-stationary random responses. However, the computational results depend to a great extent upon the dis...
Modelling of concrete cover degradation caused by rebar?s corrosion- multicomponent media theory approach. (Received in the final form January 23, 2010)
This paper presents the model based on the theory of multicomponent media that allows modelling of rebar corrosion processes. The presented model extends and consolidates the dissertations that have been described in the...
Neural network prediction of load capacity for eccentrically loaded reinforced concrete columns
This paper presents neural networks prediction of load capacity for eccentrically loaded reinforced concrete (RC) columns. The direct modelling of the load capacity of RC columns by means of the finite element method pre...
Application of neural networks for structure updating
The paper presents the application of Artificial Neural Networks (ANNs) for finite element (FE) models updating. The investigated structures are beams and frames, their models are updated by ANNs with input vectors compo...