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dc.contributor.authorKalimullah, Nur M.M.
dc.contributor.authorShukla, Kaushik
dc.contributor.authorShelke, Amit
dc.contributor.authorHabib, Anowarul
dc.date.accessioned2023-08-31T09:13:06Z
dc.date.available2023-08-31T09:13:06Z
dc.date.issued2023-02-02
dc.description.abstractThe potential application of Lithium Niobate (LiNbO3) crystal is immense, specifically in the domain of metasurfaces and nano-resonators. However, the practical application of LiNbO<sub>3</sub> is impeded due to unreliable experimental techniques and inaccurate inversion algorithms for material characterization. In the current research, material characterization of anisotropic crystal is proposed by exploring the wavefield evolution in the spatial and temporal domains. The presented framework has three major components: a physics-based mathematical model (Christoffel equation), a novel experimental technique, and an inversion algorithm based on Bayesian filtering. An experimental technique based on Coulomb coupling is devised to visualize the propagation of ultrasonic waves in an anisotropic crystal. The crystal is characterized by measuring the directional-dependent acoustic wave velocity from the spatial–temporal information of the wave propagation. The anisotropic constitutive properties of the crystal are estimated by exploring the wave velocity in the Bayesian filtering algorithm. The proposed algorithm is based on the probabilistic framework that integrates the experimental measurement in a physics-based mathematical model for optimal state prediction of stiffness tensor through the Bayesian filtering algorithm. In particular, we utilize the unscented Kalman filter (UKF) in conjunction with the plane-wave Eigen solution to estimate the constitutive parameters. In the presence of measurement uncertainties, the performance of the optimal prediction algorithm is illustrated by comparing the estimated parameter with the corresponding theoretical value. The comparison demonstrates that the proposed inversion algorithm is efficient and robust and performs satisfactorily even with significant measurement uncertainties.en_US
dc.identifier.citationKalimullah, Shukla, Shelke, Habib. Stiffness tensor estimation of anisotropic crystal using point contact method and unscented Kalman filter. Ultrasonics. 2023;131en_US
dc.identifier.cristinIDFRIDAID 2150847
dc.identifier.doi10.1016/j.ultras.2023.106939
dc.identifier.issn0041-624X
dc.identifier.issn1874-9968
dc.identifier.urihttps://hdl.handle.net/10037/30577
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalUltrasonics
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleStiffness tensor estimation of anisotropic crystal using point contact method and unscented Kalman filteren_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution 4.0 International (CC BY 4.0)