This paper introduces the first adaptive least-squares finite element method (LS-FEM) for the Stokes equations with optimal convergence rates based on the newest vertex bisection with lowest-order Raviart-Thomas and conforming discrete spaces for the divergence least-squares formulation in 2D. Although the least-squares functional is a reliable and efficient error estimator, the novel refinement indicator stems from an alternative explicit residual-based a posteriori error control with exact solve. Particular interest is on the treatment of the data approximation error which requires a separate marking strategy. The paper proves linear convergence in terms of the levels and optimal convergence rates in terms of the number of unknowns relative to the notion of a non-linear approximation class. It extends and generalizes the approach of Carstensen and Park (SIAM J. Numer. Anal. 53:43-62 2015) from the Poisson model problem to the Stokes equations.
机构:
Purdue Univ, Dept Math, 150 N Univ St, W Lafayette, IN 47907 USAPurdue Univ, Dept Math, 150 N Univ St, W Lafayette, IN 47907 USA
Cai, Zhiqiang
Chen, Binghe
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Wells Fargo Corp & Investment Banking, Charlotte, NC 28202 USAPurdue Univ, Dept Math, 150 N Univ St, W Lafayette, IN 47907 USA
Chen, Binghe
Yang, Jing
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Beijing Univ Technol, Sch Math Stat & Mech, 100 Pingleyuan, Beijing 100124, Peoples R ChinaPurdue Univ, Dept Math, 150 N Univ St, W Lafayette, IN 47907 USA
机构:
China Univ Petr, Sch Math & Computat Sci, Dongying 257061, Peoples R ChinaChina Univ Petr, Sch Math & Computat Sci, Dongying 257061, Peoples R China
Guo, Hui
Rui, Hongxing
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Shandong Univ, Sch Math & Syst Sci, Jinan 250100, Peoples R ChinaChina Univ Petr, Sch Math & Computat Sci, Dongying 257061, Peoples R China
Rui, Hongxing
Lin, Chao
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China Univ Petr, Network & Educ Technol Ctr, Dongying 257061, Peoples R ChinaChina Univ Petr, Sch Math & Computat Sci, Dongying 257061, Peoples R China