Support minimized inversion of acoustic and elastic wave scattering

dc.contributor.advisor W. Lord
dc.contributor.advisor R. A. Roberts
dc.contributor.author Safaeinili, Ali
dc.contributor.department Electrical and Computer Engineering
dc.date 2018-08-23T10:41:44.000
dc.date.accessioned 2020-06-30T07:03:24Z
dc.date.available 2020-06-30T07:03:24Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 1993
dc.date.issued 1993
dc.description.abstract <p>Inversion of limited data is common in many areas of NDE such as X-ray Computed Tomography (CT), Ultrasonic and eddy current flaw characterization and imaging;In many applications, it is common to have a bias toward a solution with minimum (L[superscript]2)[superscript]2 norm without any physical justification. When it is a priori known that objects are compact as, say, with cracks and voids, by choosing "Minimum Support" functional instead of the minimum (L[superscript]2)[superscript]2 norm, an image can be obtained that is equally in agreement with the available data, while it is more consistent with what is most probably seen in the real world;We have utilized a minimum support functional to find a solution with the smallest volume. This inversion algorithm is most successful in reconstructing objects that are compact like voids and cracks. To verify this idea, we first performed a variational nonlinear inversion of acoustic backscatter data using minimum support objective function. A full nonlinear forward model was used to accurately study the effectiveness of the minimized support inversion without error due to the linear (Born) approximation. After successful inversions using a full nonlinear forward model, a linearized acoustic inversion was developed to increase speed and efficiency in imaging process. The results indicate that by using minimum support functional, we can accurately size and characterize voids and/or cracks which otherwise might be uncharacterizable;An extremely important feature of support minimized inversion is its ability to compensate for unknown absolute phase (zero-of-time). Zero-of-time ambiguity is a serious problem in the inversion of the pulse-echo data. The minimum support inversion was successfully used for the inversion of acoustic backscatter data due to compact scatterers without the knowledge of the zero-of-time;The main drawback to this type of inversion is its computer intensiveness. In order to make this type of constrained inversion available for common use, work needs to be performed in three areas: (1) exploitation of state-of-the-art parallel computation, (2) improvement of theoretical formulation of the scattering process for better computation efficiency, and (3) development of better methods for guiding the non-linear inversion. (Abstract shortened by UMI.)</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/rtd/10264/
dc.identifier.articleid 11263
dc.identifier.contextkey 6399170
dc.identifier.doi https://doi.org/10.31274/rtd-180813-11442
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/10264
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/63391
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/rtd/10264/r_9335013.pdf|||Fri Jan 14 18:17:14 UTC 2022
dc.subject.disciplines Acoustics, Dynamics, and Controls
dc.subject.disciplines Applied Mechanics
dc.subject.disciplines Electrical and Computer Engineering
dc.subject.disciplines Physics
dc.subject.keywords Electrical engineering and computer engineering
dc.subject.keywords Electrical engineering (Electromagnetics)
dc.subject.keywords Electromagnetics
dc.title Support minimized inversion of acoustic and elastic wave scattering
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication a75a044c-d11e-44cd-af4f-dab1d83339ff
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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