On sampling methods for inverse biharmonic scattering problems in supported plates

Abstract We study the inverse problem of qualitatively recovering a supported cavity in a thin elastic plate governed by the flexural (biharmonic) wave equation, using far-field pattern measurements. We derive a reciprocity principle and a factorization of the farfield operator for the supported plate boundary conditions, and we analyze its range properties to justify both the linear sampling method (LSM) and the direct sampling method (DSM). Numerical experiments assess the performance of LSM and DSM under noise, a limited amount of data, multiple scattering, and variations in the Poisson's ratio. The results show that both methods robustly recover the obstacle's location and convex hull, with DSM offering improved stability and reduced computational cost.

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Publication Details

Journal
Inverse Problems
Published
2026-11-11
DOI
https://doi.org/10.1088/1361-6420/aec0c8
Citations
2
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
3.49
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article

On sampling methods for inverse biharmonic scattering problems in supported plates

Rafael Ceja Ayala, Peter Nekrasov, Borges Carlos
2 citations
Inverse Problems
Numerical methods in inverse problems
3.49
article

On sampling methods for inverse biharmonic scattering problems in supported plates

Rafael Ceja Ayala, Peter Nekrasov, Borges Carlos
article en
2 citations

Abstract

Abstract We study the inverse problem of qualitatively recovering a supported cavity in a thin elastic plate governed by the flexural (biharmonic) wave equation, using far-field pattern measurements. We derive a reciprocity principle and a factorization of the farfield operator for the supported plate boundary conditions, and we analyze its range properties to justify both the linear sampling method (LSM) and the direct sampling method (DSM). Numerical experiments assess the performance of LSM and DSM under noise, a limited amount of data, multiple scattering, and variations in the Poisson's ratio. The results show that both methods robustly recover the obstacle's location and convex hull, with DSM offering improved stability and reduced computational cost.

Inverse Problems
University of Central Florida (US), Courant Institute of Mathematical Sciences (US), Arizona State University (US), New York University (US)
Openalex Percentile: Top 12%
Numerical methods in inverse problems
3.49
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