The influence of inertia weight on particle swarm optimization 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

2 Citations (Scopus)

Abstract

Particle Swarm Optimization (PSO) has been applied as optimization tool in various engineering problems. Inverse analysis is one of the potential application fields for PSO. In this research, the behavior of PSO, related to its inertia weight, in boundary element inverse analysis for detecting corrosion of rebar in concrete is studied. Boundary element inverse analysis was developed by combining BEM and PSO. 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. PSO is used to minimize the cost function. Thus, the corrosion profile of concrete steel, such as location and size, can be detected. Variation in its inertia weight was applied to analyze the behavior of PSO for inverse analysis. The numerical simulation results show that PSO can be used for the inverse analysis for detecting rebar corrosion by combining with BEM. Also, it shows different behavior in minimizing cost function depending on inertia weight.

Original languageEnglish
Title of host publicationAdvanced Materials Research
Pages266-272
Number of pages7
Volume686
DOIs
Publication statusPublished - 2013
Event8th International Materials Technology Conference and Exhibition, IMTCE 2012 - Petaling Jaya
Duration: 9 Jul 201212 Jul 2012

Publication series

NameAdvanced Materials Research
Volume686
ISSN (Print)10226680

Other

Other8th International Materials Technology Conference and Exhibition, IMTCE 2012
CityPetaling Jaya
Period9/7/1212/7/12

Fingerprint

Particle swarm optimization (PSO)
Corrosion
Cost functions
Concretes
Laplace equation
Steel
Computer simulation

Keywords

  • BEM
  • Inertia weight
  • Inverse analysis
  • PSO
  • Rebar corrosion

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Fonna, S., Ridha, M., Huzni, S., & Mohd Ihsan, A. K. A. (2013). The influence of inertia weight on particle swarm optimization in boundary element inverse analysis for rebar corrosion detection. In Advanced Materials Research (Vol. 686, pp. 266-272). (Advanced Materials Research; Vol. 686). https://doi.org/10.4028/www.scientific.net/AMR.686.266

The influence of inertia weight on particle swarm optimization in boundary element inverse analysis for rebar corrosion detection. / Fonna, S.; Ridha, M.; Huzni, S.; Mohd Ihsan, Ahmad Kamal Ariffin.

Advanced Materials Research. Vol. 686 2013. p. 266-272 (Advanced Materials Research; Vol. 686).

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

Fonna, S, Ridha, M, Huzni, S & Mohd Ihsan, AKA 2013, The influence of inertia weight on particle swarm optimization in boundary element inverse analysis for rebar corrosion detection. in Advanced Materials Research. vol. 686, Advanced Materials Research, vol. 686, pp. 266-272, 8th International Materials Technology Conference and Exhibition, IMTCE 2012, Petaling Jaya, 9/7/12. https://doi.org/10.4028/www.scientific.net/AMR.686.266
Fonna, S. ; Ridha, M. ; Huzni, S. ; Mohd Ihsan, Ahmad Kamal Ariffin. / The influence of inertia weight on particle swarm optimization in boundary element inverse analysis for rebar corrosion detection. Advanced Materials Research. Vol. 686 2013. pp. 266-272 (Advanced Materials Research).
@inproceedings{d30d3860c6e8498c962caa664f8fd4f0,
title = "The influence of inertia weight on particle swarm optimization in boundary element inverse analysis for rebar corrosion detection",
abstract = "Particle Swarm Optimization (PSO) has been applied as optimization tool in various engineering problems. Inverse analysis is one of the potential application fields for PSO. In this research, the behavior of PSO, related to its inertia weight, in boundary element inverse analysis for detecting corrosion of rebar in concrete is studied. Boundary element inverse analysis was developed by combining BEM and PSO. 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. PSO is used to minimize the cost function. Thus, the corrosion profile of concrete steel, such as location and size, can be detected. Variation in its inertia weight was applied to analyze the behavior of PSO for inverse analysis. The numerical simulation results show that PSO can be used for the inverse analysis for detecting rebar corrosion by combining with BEM. Also, it shows different behavior in minimizing cost function depending on inertia weight.",
keywords = "BEM, Inertia weight, Inverse analysis, PSO, Rebar corrosion",
author = "S. Fonna and M. Ridha and S. Huzni and {Mohd Ihsan}, {Ahmad Kamal Ariffin}",
year = "2013",
doi = "10.4028/www.scientific.net/AMR.686.266",
language = "English",
isbn = "9783037856581",
volume = "686",
series = "Advanced Materials Research",
pages = "266--272",
booktitle = "Advanced Materials Research",

}

TY - GEN

T1 - The influence of inertia weight on particle swarm optimization in boundary element inverse analysis for rebar corrosion detection

AU - Fonna, S.

AU - Ridha, M.

AU - Huzni, S.

AU - Mohd Ihsan, Ahmad Kamal Ariffin

PY - 2013

Y1 - 2013

N2 - Particle Swarm Optimization (PSO) has been applied as optimization tool in various engineering problems. Inverse analysis is one of the potential application fields for PSO. In this research, the behavior of PSO, related to its inertia weight, in boundary element inverse analysis for detecting corrosion of rebar in concrete is studied. Boundary element inverse analysis was developed by combining BEM and PSO. 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. PSO is used to minimize the cost function. Thus, the corrosion profile of concrete steel, such as location and size, can be detected. Variation in its inertia weight was applied to analyze the behavior of PSO for inverse analysis. The numerical simulation results show that PSO can be used for the inverse analysis for detecting rebar corrosion by combining with BEM. Also, it shows different behavior in minimizing cost function depending on inertia weight.

AB - Particle Swarm Optimization (PSO) has been applied as optimization tool in various engineering problems. Inverse analysis is one of the potential application fields for PSO. In this research, the behavior of PSO, related to its inertia weight, in boundary element inverse analysis for detecting corrosion of rebar in concrete is studied. Boundary element inverse analysis was developed by combining BEM and PSO. 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. PSO is used to minimize the cost function. Thus, the corrosion profile of concrete steel, such as location and size, can be detected. Variation in its inertia weight was applied to analyze the behavior of PSO for inverse analysis. The numerical simulation results show that PSO can be used for the inverse analysis for detecting rebar corrosion by combining with BEM. Also, it shows different behavior in minimizing cost function depending on inertia weight.

KW - BEM

KW - Inertia weight

KW - Inverse analysis

KW - PSO

KW - Rebar corrosion

UR - http://www.scopus.com/inward/record.url?scp=84878258707&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84878258707&partnerID=8YFLogxK

U2 - 10.4028/www.scientific.net/AMR.686.266

DO - 10.4028/www.scientific.net/AMR.686.266

M3 - Conference contribution

SN - 9783037856581

VL - 686

T3 - Advanced Materials Research

SP - 266

EP - 272

BT - Advanced Materials Research

ER -