Approximation of Offset Surfaces Using Generalized Wendland Radial Basis Functions

We introduce a new methodological approach for the approximation of generalized offset surfaces using smoothing radial basis functions (RBFs). Existing offset surface generation methods often exhibit limitations such as self-intersections and singularities, which affect their robustness and accuracy. To address these issues, we employ generalized Wendland radial basis functions, which are compactly supported and provide enhanced stability. We establish the existence and uniqueness of the solution of the proposed method, analyze its computational aspects, and prove convergence results. Finally, numerical experiments are presented to demonstrate its effectiveness as well as to compare it with an existing method from the literature.

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Publication Details

Journal
Mathematics
Published
2026-04-13
DOI
https://doi.org/10.3390/math14081300
Primary Topic
Advanced Numerical Analysis Techniques
Type
article
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article

Approximation of Offset Surfaces Using Generalized Wendland Radial Basis Functions

A. Kouibia, Hossain O. Yakhlef, Hamza El Bazi, Loubna Omri
Mathematics
Advanced Numerical Analysis Techniques
article

Approximation of Offset Surfaces Using Generalized Wendland Radial Basis Functions

A. Kouibia, Hossain O. Yakhlef, Hamza El Bazi, Loubna Omri
article en

Abstract

We introduce a new methodological approach for the approximation of generalized offset surfaces using smoothing radial basis functions (RBFs). Existing offset surface generation methods often exhibit limitations such as self-intersections and singularities, which affect their robustness and accuracy. To address these issues, we employ generalized Wendland radial basis functions, which are compactly supported and provide enhanced stability. We establish the existence and uniqueness of the solution of the proposed method, analyze its computational aspects, and prove convergence results. Finally, numerical experiments are presented to demonstrate its effectiveness as well as to compare it with an existing method from the literature.

MathematicsVol. 14(8)
Universidad de Granada (ES), Abdelmalek Essaâdi University (MA), Instituto Superior da Maia (PT)
Openalex Percentile: Top 22%
Advanced Numerical Analysis Techniques
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