Superconvergence of differential structure on discretized surfaces is studied in this paper.The newly introduced geometric supercloseness provides us with a fundamental tool to prove the superconvergence of gradient r...Superconvergence of differential structure on discretized surfaces is studied in this paper.The newly introduced geometric supercloseness provides us with a fundamental tool to prove the superconvergence of gradient recovery on deviated surfaces.An algorithmic framework for gradient recovery without exact geometric information is introduced.Several numerical examples are documented to validate the theoretical results.展开更多
基金supported by the NSFC(Grant No.12001194)by the NSF of Hunan Province(Grant No.2024JJ5413)+2 种基金supported by the Andrew Sisson Fund,by the Dyason Fellowship and by the Ministry of Education of the People's Republic of China Chunhui Programme(Grant No.202201217)supported by the NSFC(Grant No.12101228)by the Innovative Platform Project of Hunan Province(Grant No.20K078).
文摘Superconvergence of differential structure on discretized surfaces is studied in this paper.The newly introduced geometric supercloseness provides us with a fundamental tool to prove the superconvergence of gradient recovery on deviated surfaces.An algorithmic framework for gradient recovery without exact geometric information is introduced.Several numerical examples are documented to validate the theoretical results.
