Finite Element Model Updating Using Fish School Search Optimization Method

Author

Boulkabeit, Ilyes ; Mthembu, Linda ; Marwala, Tshilidzi ; Buarque De Lima Neto, Fernando

Author_Institution

Electr. & Electron. Eng. Dept., Univ. of Johannesburg, Johannesburg, South Africa

fYear

2013

fDate

8-11 Sept. 2013

Firstpage

447

Lastpage

452

Abstract

A recent nature inspired optimization algorithm, Fish School Search (FSS) is applied to the finite element model (FEM) updating problem. This method is tested on a GARTEUR SM-AG19 aeroplane structure. The results of this algorithm are compared with two other metaheuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). It is observed that on average, the FSS and PSO algorithms give more accurate results than the GA. A minor modification to the FSS is proposed. This modification improves the performance of FSS on the FEM updating problem which has a constrained search space.

Keywords

finite element analysis; genetic algorithms; search problems; FEM updating problem; FSS; GARTEUR SM-AG19 aeroplane structure; PSO algorithms; constrained search space; finite element model; fish school search optimization method; genetic algorithm; metaheuristic algorithms; minor modification; nature inspired optimization algorithm; particle swarm optimization; Educational institutions; Finite element analysis; Frequency selective surfaces; Genetic algorithms; Marine animals; Mathematical model; Vectors; Finite Element Model (FEM); Fish School Search (FSS); Genetic Algorithm (GA); Particle Swarm Optimization (PSO);

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC), 2013 BRICS Congress on

Conference_Location

Ipojuca

Type

conf

DOI

10.1109/BRICS-CCI-CBIC.2013.80

Filename

6855889