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An optimization-based methodology for the definition of amplitude thresholds of the ground penetrating radar

  • Eslam Mohammed AbdelkaderEmail author
  • Mohamed Marzouk
  • Tarek Zayed
Methodologies and Application
  • 33 Downloads

Abstract

Existing infrastructure is aging, while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges are subjected to severe deterioration agents such as variable traffic loading, deferred maintenance, cycles of freeze and thaw. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays due to the huge variance between the need for maintenance actions and the available funds to perform such actions. Condition assessment is regarded as one of the most critical and vital components of BMSs. Ground penetrating radar (GPR) is one of the nondestructive techniques that are used to evaluate the condition of bridge decks which are subjected to the rebar corrosion. There is a major issue associated with the GPR which is the absence of a scale for the amplitude values. The objective of the proposed model is to compute standardized amplitude thresholds for corrosion maps. The proposed model considers eight un-supervised clustering algorithms to obtain the thresholds. The proposed model incorporates a multi-objective optimization-based methodology that employs three evolutionary optimization algorithms to calculate the optimum thresholds which are: (1) genetic algorithm, (2) particle swarm optimization algorithm, and (3) shuffled frog-leaping algorithm. Five multi-criteria decision-making techniques are used to provide a ranking for the solutions. Finally, group decision-making is performed to aggregate the results and obtain a consensus and compromise solution. The standardized thresholds obtained from the proposed methodology are: − 16.7619, − 8.8161, and − 2.9744 dB.

Keywords

Bridge Management System Ground penetrating radar Nondestructive techniques Corrosion Amplitude thresholds Evolutionary optimization algorithms Multi-criteria decision-making 

Notes

Acknowledgements

This project was funded by the Academy of Scientific Research and Technology (ASRT), Egypt, JESOR-Development Program—Project ID: 40.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Eslam Mohammed Abdelkader
    • 1
    • 2
    Email author
  • Mohamed Marzouk
    • 3
  • Tarek Zayed
    • 4
  1. 1.Department of Building, Civil, and Environmental EngineeringConcordia UniversityMontrealCanada
  2. 2.Structural Engineering Department, Faculty of EngineeringCairo UniversityGizaEgypt
  3. 3.Construction Engineering and Management, Structural Engineering Department, Faculty of EngineeringCairo UniversityGizaEgypt
  4. 4.Construction and Real Estate DepartmentThe Hong Kong Polytechnic UniversityHung HomHong Kong

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