Comparison of GA and PSO in boundary element inverse analysis for rebar corrosion detection

S. Fonna, M. Ridha, S. Huzni, Ahmad Kamal Ariffin Mohd Ihsan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents the comparison of the two optimization methods, particle swarm optimization (PSO) and genetic algorithm (GA) in boundary element inverse analysis that applied to detect the corrosion location of rebar in the concrete. This comparison focuses at analyzing the performance of both methods in reaching the global optimum, considering that both heuristics are based on population search techniques. The model of 2-dimension rectangular reinforced concrete was used as a case example to compare both methods in boundary element inverse analysis. The boundary element inverse analysis was developed by combining Boundary Element Method (BEM) and PSO or GA. The inverse analysis is carried out by means of minimizing a cost function. The cost function is a residual between the calculated and measured potentials on the concrete surface. The calculated potentials are obtained by solving the Laplace's equation using BEM. The GA or PSO is used to minimize the cost function. Thus, the corrosion location of reinforcing steel in concrete can be detected. The numerical simulation results showed that one of PSO or GA can be used for the inverse analysis for detecting rebar corrosion by combining with BEM. However, it shows that PSO seem numerically superior compared to GA in term of consistency and accuracy in finding global optimum solution for such a problem.

Original languageEnglish
Title of host publicationApplied Mechanics and Materials
Pages319-323
Number of pages5
Volume471
DOIs
Publication statusPublished - 2014
Event4th International Conference on Noise, Vibration and Comfort, NVC 2012 - Kuala Lumpur
Duration: 26 Nov 201228 Nov 2012

Publication series

NameApplied Mechanics and Materials
Volume471
ISSN (Print)16609336
ISSN (Electronic)16627482

Other

Other4th International Conference on Noise, Vibration and Comfort, NVC 2012
CityKuala Lumpur
Period26/11/1228/11/12

Fingerprint

Particle swarm optimization (PSO)
Genetic algorithms
Corrosion
Boundary element method
Cost functions
Concretes
Laplace equation
Reinforced concrete
Steel
Computer simulation

Keywords

  • Bem
  • Concrete
  • GA
  • Inverse analysis
  • PSO
  • Rebar corrosion

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Fonna, S., Ridha, M., Huzni, S., & Mohd Ihsan, A. K. A. (2014). Comparison of GA and PSO in boundary element inverse analysis for rebar corrosion detection. In Applied Mechanics and Materials (Vol. 471, pp. 319-323). (Applied Mechanics and Materials; Vol. 471). https://doi.org/10.4028/www.scientific.net/AMM.471.319

Comparison of GA and PSO in boundary element inverse analysis for rebar corrosion detection. / Fonna, S.; Ridha, M.; Huzni, S.; Mohd Ihsan, Ahmad Kamal Ariffin.

Applied Mechanics and Materials. Vol. 471 2014. p. 319-323 (Applied Mechanics and Materials; Vol. 471).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fonna, S, Ridha, M, Huzni, S & Mohd Ihsan, AKA 2014, Comparison of GA and PSO in boundary element inverse analysis for rebar corrosion detection. in Applied Mechanics and Materials. vol. 471, Applied Mechanics and Materials, vol. 471, pp. 319-323, 4th International Conference on Noise, Vibration and Comfort, NVC 2012, Kuala Lumpur, 26/11/12. https://doi.org/10.4028/www.scientific.net/AMM.471.319
Fonna S, Ridha M, Huzni S, Mohd Ihsan AKA. Comparison of GA and PSO in boundary element inverse analysis for rebar corrosion detection. In Applied Mechanics and Materials. Vol. 471. 2014. p. 319-323. (Applied Mechanics and Materials). https://doi.org/10.4028/www.scientific.net/AMM.471.319
Fonna, S. ; Ridha, M. ; Huzni, S. ; Mohd Ihsan, Ahmad Kamal Ariffin. / Comparison of GA and PSO in boundary element inverse analysis for rebar corrosion detection. Applied Mechanics and Materials. Vol. 471 2014. pp. 319-323 (Applied Mechanics and Materials).
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