The error analysis of a proper orthogonal decomposition (POD) data assimilation (DA) scheme for the Navier-Stokes equations is carried out. A grad-div stabilization term is added to the formulation of the POD method. Error bounds with constants independent on inverse powers of the viscosity parameter are derived for the POD algorithm. No upper bounds in the nudging parameter of the data assimilation method are required. Numerical experiments show that, for large values of the nudging parameter, the proposed method rapidly converges to the real solution, and greatly improves the overall accuracy of standard POD schemes up to low viscosities over predictive time intervals. (C) 2022 The Author(s). Published by Elsevier B.V.
机构:
Xiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China
Xiamen Univ, Fujian Prov Key Lab Math Modeling & High Performa, Xiamen 361005, Fujian, Peoples R ChinaXiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China
Li, Xiaoli
Shen, Jie
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Purdue Univ, Dept Math, W Lafayette, IN 47907 USAXiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China
机构:
Xiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China
Xiamen Univ, Fujian Prov Key Lab Math Modeling & High Performa, Xiamen 361005, Fujian, Peoples R ChinaXiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China
Li, Xiaoli
Shen, Jie
论文数: 0引用数: 0
h-index: 0
机构:
Purdue Univ, Dept Math, W Lafayette, IN 47907 USAXiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China