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On the T-matrix for thermo-visco-elastic scattering.

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Title: On the T-matrix for thermo-visco-elastic scattering.
Authors: Martin, P A1 (AUTHOR)
Source: Quarterly Journal of Mechanics & Applied Mathematics. Feb2025, Vol. 78 Issue 1, p1-24. 24p.
Subjects: T-matrix, Algorithms
Abstract: Waves in a thermo-visco-elastic medium interact with a bounded penetrable obstacle of arbitrary shape. The T -matrix for such a scattering problem connects the expansion of the incident wave in terms of regular vector spherical wavefunctions to the expansion of the scattered waves in terms of outgoing vector spherical wavefunctions. It is shown that the T -matrix is symmetric, and an algorithm for its calculation is presented. [ABSTRACT FROM AUTHOR]
Copyright of Quarterly Journal of Mechanics & Applied Mathematics is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: On the T-matrix for thermo-visco-elastic scattering.
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  Data: Waves in a thermo-visco-elastic medium interact with a bounded penetrable obstacle of arbitrary shape. The T -matrix for such a scattering problem connects the expansion of the incident wave in terms of regular vector spherical wavefunctions to the expansion of the scattered waves in terms of outgoing vector spherical wavefunctions. It is shown that the T -matrix is symmetric, and an algorithm for its calculation is presented. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Quarterly Journal of Mechanics & Applied Mathematics is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1093/qjmam/hbaf002
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        Text: English
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      – SubjectFull: Algorithms
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              Text: Feb2025
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