Reduced-cost two-level surrogate antenna modeling using domain confinement and response features.

Journal

Scientific reports

ISSN: 2045-2322

Titre abrégé: Sci Rep

Pays: England

ID NLM: 101563288

Informations de publication

Date de publication:
18 Mar 2022

Historique:

received: 04 10 2021

accepted: 11 03 2022

entrez: 19 3 2022

pubmed: 20 3 2022

medline: 20 3 2022

Statut: epublish

Résumé

Electromagnetic (EM) simulation tools have become indispensable in the design of contemporary antennas. Still, the major setback of EM-driven design is the associated computational overhead. This is because a single full-wave simulation may take from dozens of seconds up to several hours, thus, the cost of solving design tasks that involve multiple EM analyses may turn unmanageable. This is where faster system representations (surrogates) come into play. Replacing expensive EM-based evaluations by cheap yet accurate metamodels seems to be an attractive solution. Still, in antenna design, application of surrogate models is hindered by the curse of dimensionality. A practical workaround has been offered by the recently reported reference-design-free constrained modeling techniques that restrict the metamodel domain to the parameter space region encompassing high-quality designs. Therein, the domain is established using only a handful of EM-simulations. This paper proposes a novel modeling technique, which incorporates the response feature technology into the constrained modeling framework. Our methodology allows for rendering accurate surrogates using exceptionally small training data sets, at the expense of reducing the generality of the modeling procedure to antennas that exhibit consistent shape of input characteristics. The proposed technique can be employed in other fields that employ costly simulation models (e.g., mechanical or aerospace engineering).

Identifiants

DOI: 10.1038/s41598-022-08710-2 PMID: 35305009 PMC: PMC8933475

pubmed: 35305009

doi: 10.1038/s41598-022-08710-2

pii: 10.1038/s41598-022-08710-2

pmc: PMC8933475

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

4667

Subventions

Organisme : Narodowe Centrum Nauki

ID : 2018/31/B/ST7/02369

Organisme : Icelandic Centre for Research

ID : 217771

Informations de copyright

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