Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method

This paper is concerned with the optimal design of axial probes, commonly used in the Non-Destructive Testing (NDT) of tube boiling in steam generators. The goal is to improve the low-frequency Foucault-current imaging of these deposits by designing a novel probe. The approach uses a combination of...

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Published inEnergies (Basel) Vol. 16; no. 5; p. 2448
Main Authors Benaissa, Brahim, Khatir, Samir, Jouini, Mohamed Soufiane, Riahi, Mohamed Kamel
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.03.2023
Subjects
Boilers
Design
Design and construction
Design optimization
eddy-current
Electric fields
finite element method
Global optimization
Image processing
inverse problem
Inverse problems
linear sampling method
Mathematical models
Mathematical optimization
Methods
NDT
Non-destructive testing
Nondestructive testing
optimal design
Partial differential equations
Radiation
Search algorithms
Sensors
Signal processing
Steam-boilers
Symmetry
Testing
Tomography
Japan
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Abstract This paper is concerned with the optimal design of axial probes, commonly used in the Non-Destructive Testing (NDT) of tube boiling in steam generators. The goal is to improve the low-frequency Foucault-current imaging of these deposits by designing a novel probe. The approach uses a combination of an inverse problem solver with global optimization to find the optimal probe characteristics by minimizing a function of merit defined using image processing techniques. The evaluation of the function of merit is computationally intensive and a surrogate optimization approach is used, incorporating a multi-particle search algorithm. The proposed design is validated through numerical experiments and aims to improve the accuracy and efficiency of identifying deposits in steam generator tubes.
AbstractList This paper is concerned with the optimal design of axial probes, commonly used in the Non-Destructive Testing (NDT) of tube boiling in steam generators. The goal is to improve the low-frequency Foucault-current imaging of these deposits by designing a novel probe. The approach uses a combination of an inverse problem solver with global optimization to find the optimal probe characteristics by minimizing a function of merit defined using image processing techniques. The evaluation of the function of merit is computationally intensive and a surrogate optimization approach is used, incorporating a multi-particle search algorithm. The proposed design is validated through numerical experiments and aims to improve the accuracy and efficiency of identifying deposits in steam generator tubes.
Audience Academic
Author Jouini, Mohamed Soufiane
Khatir, Samir
Riahi, Mohamed Kamel
Benaissa, Brahim
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  givenname: Mohamed Kamel
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  surname: Riahi
  fullname: Riahi, Mohamed Kamel
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Snippet This paper is concerned with the optimal design of axial probes, commonly used in the Non-Destructive Testing (NDT) of tube boiling in steam generators. The...
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StartPage 2448
SubjectTerms Boilers
Design
Design and construction
Design optimization
eddy-current
Electric fields
finite element method
Global optimization
Image processing
inverse problem
Inverse problems
linear sampling method
Mathematical models
Mathematical optimization
Methods
NDT
Non-destructive testing
Nondestructive testing
optimal design
Partial differential equations
Radiation
Search algorithms
Sensors
Signal processing
Steam-boilers
Symmetry
Testing
Tomography
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Title Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method
URI https://www.proquest.com/docview/2785194078
https://doaj.org/article/4e4fa4f486064b33850b7dc8e9eb6e46
Volume 16
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