@ARTICLE{Benaissa2023,
	author = {Benaissa, Brahim and Khatir, Samir and Jouini, Mohamed Soufiane and Riahi, Mohamed Kamel},
	title = {Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method},
	year = {2023},
	journal = {Energies},
	volume = {16},
	number = {5},
	doi = {10.3390/en16052448},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149721564&doi=10.3390%2fen16052448&partnerID=40&md5=e3b9daab453951ab71e9e9fe0928f16f},
	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. © 2023 by the authors.},
	note = {Cited by: 12; All Open Access, Gold Open Access}
}

{"_id":"678Foc92XcfN8Tjzk","bibbaseid":"benaissa-khatir-jouini-riahi-optimalaxialprobedesignforfoucaultcurrenttomographyaglobaloptimizationapproachbasedonlinearsamplingmethod-2023","author_short":["Benaissa, B.","Khatir, S.","Jouini, M. S.","Riahi, M. K."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Benaissa"],"firstnames":["Brahim"],"suffixes":[]},{"propositions":[],"lastnames":["Khatir"],"firstnames":["Samir"],"suffixes":[]},{"propositions":[],"lastnames":["Jouini"],"firstnames":["Mohamed","Soufiane"],"suffixes":[]},{"propositions":[],"lastnames":["Riahi"],"firstnames":["Mohamed","Kamel"],"suffixes":[]}],"title":"Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method","year":"2023","journal":"Energies","volume":"16","number":"5","doi":"10.3390/en16052448","url":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149721564&doi=10.3390%2fen16052448&partnerID=40&md5=e3b9daab453951ab71e9e9fe0928f16f","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. © 2023 by the authors.","note":"Cited by: 12; All Open Access, Gold Open Access","bibtex":"@ARTICLE{Benaissa2023,\n\tauthor = {Benaissa, Brahim and Khatir, Samir and Jouini, Mohamed Soufiane and Riahi, Mohamed Kamel},\n\ttitle = {Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method},\n\tyear = {2023},\n\tjournal = {Energies},\n\tvolume = {16},\n\tnumber = {5},\n\tdoi = {10.3390/en16052448},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149721564&doi=10.3390%2fen16052448&partnerID=40&md5=e3b9daab453951ab71e9e9fe0928f16f},\n\tabstract = {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. © 2023 by the authors.},\n\tnote = {Cited by: 12; All Open Access, Gold Open Access}\n}\n\n","author_short":["Benaissa, B.","Khatir, S.","Jouini, M. S.","Riahi, M. K."],"key":"Benaissa2023","id":"Benaissa2023","bibbaseid":"benaissa-khatir-jouini-riahi-optimalaxialprobedesignforfoucaultcurrenttomographyaglobaloptimizationapproachbasedonlinearsamplingmethod-2023","role":"author","urls":{"Paper":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149721564&doi=10.3390%2fen16052448&partnerID=40&md5=e3b9daab453951ab71e9e9fe0928f16f"},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://docs.google.com/uc?export=download&id=1GhoAKJBee1PlLyIx6KepRvIg2UrLVBRg","dataSources":["EebkmJjgLhgSZMFtf"],"keywords":[],"search_terms":["optimal","axial","probe","design","foucault","current","tomography","global","optimization","approach","based","linear","sampling","method","benaissa","khatir","jouini","riahi"],"title":"Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method","year":2023}