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Spectral analysis and shape optimization of Steklov--Dirichlet eigenvalues on shell-type domains

Abstract

We investigate the Steklov--Dirichlet eigenvalues on shell-type domains in ℝn, n≥ 2, where the Steklov and Dirichlet conditions are imposed on the outer and the inner boundaries, respectively. We introduce the Green function associated with the problem, which is well-defined for spectral parameters outside the spectrum and exhibits blow-up behavior at eigenvalues, and establish its spectral representation. We also examine its differentiability and derive its shape derivative under translations of the inner boundary. Using these results and a layer potential approach, we propose a computational framework for optimizing the eigenvalue with respect to the position of the inner boundary, incorporating an eigenvalue estimator for which a local error bound is established. Numerical experiments for various inner and outer boundary shapes demonstrate the effectiveness of the proposed approach in identifying configurations that maximize the first eigenvalue.

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BibTeX
@misc{han2026spectral,
  title = {{Spectral analysis and shape optimization of Steklov--Dirichlet eigenvalues on shell-type domains}},
  author = {Dohyeong Han and Woojoo Lee and Mikyoung Lim},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.04410},
  eprint = {2611.04410},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.04410},
}
RIS
TY  - UNPB
TI  - Spectral analysis and shape optimization of Steklov--Dirichlet eigenvalues on shell-type domains
AU  - Dohyeong Han
AU  - Woojoo Lee
AU  - Mikyoung Lim
PY  - 2026
DA  - 2026/11/03
PB  - arXiv
DO  - 10.48550/arxiv.2611.04410
UR  - https://arxiv.org/abs/2611.04410
AB  - We investigate the Steklov--Dirichlet eigenvalues on shell-type domains in ℝ^n, n≥ 2, where the Steklov and Dirichlet conditions are imposed on the outer and the inner boundaries, respectively. We introduce the Green function associated with the problem, which is well-defined for spectral parameters outside the spectrum and exhibits blow-up behavior at eigenvalues, and establish its spectral representation. We also examine its differentiability and derive its shape derivative under translations of the inner boundary. Using these results and a layer potential approach, we propose a computational framework for optimizing the eigenvalue with respect to the position of the inner boundary, incorporating an eigenvalue estimator for which a local error bound is established. Numerical experiments for various inner and outer boundary shapes demonstrate the effectiveness of the proposed approach in identifying configurations that maximize the first eigenvalue.
ER  -