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

Brahim Benaissa; Samir Khatir; Mohamed Soufiane Jouini; Mohamed Kamel Riahi

doi:10.3390/en16052448

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

Brahim Benaissa, Samir Khatir, Mohamed Soufiane Jouini, Mohamed Kamel Riahi

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

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.

Original language	British English
Article number	2448
Journal	Energies
Volume	16
Issue number	5
DOIs	https://doi.org/10.3390/en16052448
State	Published - Mar 2023

Keywords

eddy-current
finite element method
inverse problem
linear sampling method
NDT
optimal design
surrogate optimization

Access to Document

10.3390/en16052448

Cite this

@article{b210cd62922a436e8fd57dd4dea3d4bf,

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

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.",

keywords = "eddy-current, finite element method, inverse problem, linear sampling method, NDT, optimal design, surrogate optimization",

author = "Brahim Benaissa and Samir Khatir and Jouini, {Mohamed Soufiane} and Riahi, {Mohamed Kamel}",

note = "Publisher Copyright: {\textcopyright} 2023 by the authors.",

year = "2023",

month = mar,

doi = "10.3390/en16052448",

language = "British English",

volume = "16",

journal = "Energies",

issn = "1996-1073",

publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",

number = "5",

}

TY - JOUR

T1 - Optimal Axial-Probe Design for Foucault-Current Tomography

T2 - A Global Optimization Approach Based on Linear Sampling Method

AU - Benaissa, Brahim

AU - Khatir, Samir

AU - Jouini, Mohamed Soufiane

AU - Riahi, Mohamed Kamel

PY - 2023/3

Y1 - 2023/3

N2 - 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.

AB - 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.

KW - eddy-current

KW - finite element method

KW - inverse problem

KW - linear sampling method

KW - NDT

KW - optimal design

KW - surrogate optimization

UR - http://www.scopus.com/inward/record.url?scp=85149721564&partnerID=8YFLogxK

U2 - 10.3390/en16052448

DO - 10.3390/en16052448

M3 - Article

AN - SCOPUS:85149721564

SN - 1996-1073

VL - 16

JO - Energies

JF - Energies

IS - 5

M1 - 2448

ER -

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this