Computing leaky waves in semi-analytical waveguide models by exponential residual relaxation

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Hauptverfasser: Gravenkamp, Hauke, Plestenjak, Bor, Kiefer, Daniel A.
Format: Preprint
Veröffentlicht: 2025
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author Gravenkamp, Hauke
Plestenjak, Bor
Kiefer, Daniel A.
author_facet Gravenkamp, Hauke
Plestenjak, Bor
Kiefer, Daniel A.
contents Semi-analytical methods for the modeling of guided waves in structures of constant cross-section lead to frequency-dependent polynomial eigenvalue problems for the wavenumbers and mode shapes. Solving these eigenvalue problems for a range of frequencies results in continuous eigencurves that are of relevance in practical applications of ultrasonic measurement systems. Recent research has shown that eigencurves of parameter-dependent eigenvalue problems can alternatively be computed as solutions of a system of ordinary differential equations, which are obtained by postulating an exponentially decaying residual of a modal solution. This general concept for solving parameter-dependent matrix equations is, in this context, known as Zeroing Neural Networks or Zhang Neural Networks (ZNN). We exploit this idea to develop an efficient method for computing the dispersion curves of plate structures coupled to unbounded solid or fluid media. In these scenarios, the alternative formulation is particularly useful since the boundary conditions give rise to nonlinear terms that severely hinder the application of traditional solvers.
format Preprint
id arxiv_https___arxiv_org_abs_2505_04735
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Computing leaky waves in semi-analytical waveguide models by exponential residual relaxation
Gravenkamp, Hauke
Plestenjak, Bor
Kiefer, Daniel A.
Classical Physics
Semi-analytical methods for the modeling of guided waves in structures of constant cross-section lead to frequency-dependent polynomial eigenvalue problems for the wavenumbers and mode shapes. Solving these eigenvalue problems for a range of frequencies results in continuous eigencurves that are of relevance in practical applications of ultrasonic measurement systems. Recent research has shown that eigencurves of parameter-dependent eigenvalue problems can alternatively be computed as solutions of a system of ordinary differential equations, which are obtained by postulating an exponentially decaying residual of a modal solution. This general concept for solving parameter-dependent matrix equations is, in this context, known as Zeroing Neural Networks or Zhang Neural Networks (ZNN). We exploit this idea to develop an efficient method for computing the dispersion curves of plate structures coupled to unbounded solid or fluid media. In these scenarios, the alternative formulation is particularly useful since the boundary conditions give rise to nonlinear terms that severely hinder the application of traditional solvers.
title Computing leaky waves in semi-analytical waveguide models by exponential residual relaxation
topic Classical Physics
url https://arxiv.org/abs/2505.04735