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Open AccessArticle

Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring

Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia
Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Department of Physics, Al-Azhar University, Assiut 71524, Egypt
Geology Department, Bayero University Kano (BUK), Kano 700241, Nigeria
Author to whom correspondence should be addressed.
Sensors 2020, 20(4), 1014;
Received: 12 September 2019 / Revised: 12 November 2019 / Accepted: 1 December 2019 / Published: 13 February 2020
(This article belongs to the Section Optical Sensors)
In the current study, we developed an adaptive algorithm that can predict oil mobilization in a porous medium on the basis of optical data. Associated mechanisms based on tuning the electromagnetic response of magnetic and dielectric nanoparticles are also discussed. This technique is a promising method in rational magnetophoresis toward fluid mobility via fiber Bragg grating (FBG). The obtained wavelength shift due to Fe3O4 injection was 75% higher than that of dielectric materials. This use of FBG magneto-optic sensors could be a remarkable breakthrough for fluid-flow tracking in oil reservoirs. Our computational algorithm, based on piecewise linear polynomials, was evaluated with an analytical technique for homogeneous cases and achieved 99.45% accuracy. Theoretical values obtained via coupled-mode theory agreed with our FBG experiment data of at a level of 95.23% accuracy. View Full-Text
Keywords: nanotechnology; fiber Bragg grating; coupled-mode theory; inversion algorithm nanotechnology; fiber Bragg grating; coupled-mode theory; inversion algorithm
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Yahya, N.; Mui Nyuk, C.; Ismail, A.F.; Hussain, N.; Rostami, A.; Ismail, A.; Ganeson, M.; Ali, A.M. Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring. Sensors 2020, 20, 1014.

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