Quantitative Object Reconstruction using Abel Transform X-Ray Tomography and Mixed Variable Optimization

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dc.contributor.authorAbramson, Mark A.en_US
dc.contributor.authorAsaki, Thomas J.en_US
dc.contributor.authorDennis, J.E. Jr.en_US
dc.contributor.authorO'Reilly, Kevin R.en_US
dc.contributor.authorPingel, Rachael L.en_US
dc.date.accessioned2018-06-18T17:58:13Zen_US
dc.date.available2018-06-18T17:58:13Zen_US
dc.date.issued2007-02en_US
dc.date.noteFebruary 2007 (Revised on June 2008)en_US
dc.description.abstractThis paper introduces a new approach to the problem of quantitatively reconstructing cylindrically symmetric objects from radiograph data obtained via x-ray tomography. Specifically, a mixed variable programming (MVP) problem is formulated, in which the variables of interest are the number and types of materials and the thickness of each concentric layer. The objective function is a measure of distance between one-dimensional radiograph data and a material property vector operated on by a forward projection based on the Abel transform. The mixed variable pattern search (MVPS) algorithm for linearly constrained MVP problems is applied to the problem by means of the NOMADm MATLABĀ® software package. Numerical results are presented for several test configurations and show that, while there are difficulties yet to be overcome, the method appears to be very promising for solving this class of problems in practice.en_US
dc.format.extent23 ppen_US
dc.identifier.citationAbramson, Mark A., Asaki, Thomas J., Dennis, J.E. Jr., et al.. "Quantitative Object Reconstruction using Abel Transform X-Ray Tomography and Mixed Variable Optimization." (2007) <a href="https://hdl.handle.net/1911/102068">https://hdl.handle.net/1911/102068</a>.en_US
dc.identifier.digitalTR07-03en_US
dc.identifier.urihttps://hdl.handle.net/1911/102068en_US
dc.language.isoengen_US
dc.titleQuantitative Object Reconstruction using Abel Transform X-Ray Tomography and Mixed Variable Optimizationen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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