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We propose a goal-oriented, local a posteriori error estimator for H(div) least-squares (LS) finite element methods. Our main interest is to develop an a posteriori error estimator for the flux approximation in a preassigned region of interest D ⊂ Ω. The estimator is obtained from the LS functional by scaling residuals with proper weight coefficients. The(More)
The div least-squares methods have been studied by many researchers for the secondorder elliptic equations, elasticity, and the Stokes equations, and optimal error estimates have been obtained in the H(div) × H1 norm. However, there is no known convergence rate when the given data f belongs only to L2 space. In this paper, we will establish an optimal error(More)