Journal
MATHEMATICS AND COMPUTERS IN SIMULATION
Volume 185, Issue -, Pages 372-383Publisher
ELSEVIER
DOI: 10.1016/j.matcom.2021.01.002
Keywords
PPIA; Tensor product Bezier patch; Diagonally compensated reduction; Preconditioning technique; IPPIA
Categories
Funding
- National Natural Science Foundation of China [11371075, 11771453]
- Hunan Key Laboratory of Mathematical Modeling and Analysis in Engineering, Natural Science Foundation of Hunan Province, China [2020JJ5267]
- Scientific Research Funds of Hunan Provincial Education Department [18C0877, 19B301]
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This paper presents the preconditioned progressive iterative approximation (PPIA) based on diagonally compensated reduction for tensor product Bezier patches, which significantly accelerates the convergence rate of progressive iterative approximation (PIA). An inexact PPIA format is introduced to enhance the robustness and reduce the computational complexity. Several numerical examples are provided to demonstrate the effectiveness of the proposed methods.
Based on the diagonally compensated reduction, the preconditioned progressive iterative approximation (PPIA) for tensor product Bezier patches is presented. Due to the effectiveness of the preconditioner, the convergence rate of progressive iterative approximation (PIA) is accelerated significantly. To improve the robustness and reduce the computational complexity of PPIA, the inexact PPIA format for tensor product Bezier patches is presented. Several numerical examples are presented to illustrate the effectiveness of the proposed methods. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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