Functional A Posteriori Error Control for Conforming Mixed Approximations of Coercive Problems with Lower Order Terms
Functional A Posteriori Error Control for Conforming Mixed Approximations of Coercive Problems with Lower Order Terms
复制标题
具有低阶项的强制问题的混合近似的泛函后验误差控制
DOI:
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发表时间:
2015
期刊:
影响因子:
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通讯作者:
D. Pauly
中科院分区:
文献类型:
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作者:
I. Anjam;D. Pauly
Abstract The results of this contribution are derived in the framework of functional type a posteriori error estimates. The error is measured in a combined norm which takes into account both the primal and dual variables denoted by x and y, respectively. Our first main result is an error equality for all equations of the class A * A x + x = f ${mathrm{A}^{*}mathrm{A}x+x=f}$ or in mixed formulation A * y + x = f ${mathrm{A}^{*}y+x=f}$ , A x = y ${mathrm{A}x=y}$ , where the exact solution ( x , y ) $(x,y)$ is in D ( A ) × D ( A * ) $D(mathrm{A}) imes D(mathrm{A}^{*})$ . Here A ${mathrm{A}}$ is a linear, densely defined and closed (usually a differential) operator and A * ${mathrm{A}^{*}}$ its adjoint. In this paper we deal with very conforming mixed approximations, i.e., we assume that the approximation ( x ~ , y ~ ) ${( ilde{x}, ilde{y})}$ belongs to D ( A ) × D ( A * ) ${D(mathrm{A}) imes D(mathrm{A}^{*})}$ . In order to obtain the exact global error value of this approximation one only needs the problem data and the mixed approximation itself, i.e., we have the equality | x - x ~ | 2 + | A ( x - x ~ ) | 2 + | y - y ~ | 2 + | A * ( y - y ~ ) | 2 = ℳ ( x ~ , y ~ ) , $lvert x- ilde{x}
vert^{2}+lvertmathrm{A}(x- ilde{x})
vert^{2}+lvert y-% ilde{y}
vert^{2}+lvertmathrm{A}^{*}(y- ilde{y})
vert^{2}=mathcal{M}(% ilde{x}, ilde{y}),$ where ℳ ( x ~ , y ~ ) := | f - x ~ - A * y ~ | 2 + | y ~ - A x ~ | 2 ${mathcal{M}( ilde{x}, ilde{y}):=lvert f- ilde{x}-mathrm{A}^{*} ilde{y}%
vert^{2}+lvert ilde{y}-mathrm{A} ilde{x}
vert^{2}}$ contains only known data. Our second main result is an error estimate for all equations of the class A * A x + i x = f ${mathrm{A}^{*}mathrm{A}x+ix=f}$ or in mixed formulation A * y + i x = f ${mathrm{A}^{*}y+ix=f}$ , A x = y ${mathrm{A}x=y}$ , where i is the imaginary unit. For this problem we have the two-sided estimate 2 2 + 1 ℳ i ( x ~ , y ~ ) ≤ | x - x ~ | 2 + | A ( x - x ~ ) | 2 + | y - y ~ | 2 + | A * ( y - y ~ ) | 2 ≤ 2 2 - 1 ℳ i ( x ~ , y ~ ) , $frac{sqrt{2}}{sqrt{2}+1}mathcal{M}_{i}( ilde{x}, ilde{y})leqlvert x-% ilde{x}
vert^{2}+lvertmathrm{A}(x- ilde{x})
vert^{2}+lvert y- ilde{y}%
vert^{2}+lvertmathrm{A}^{*}(y- ilde{y})
vert^{2}leqfrac{sqrt{2}}{% sqrt{2}-1}mathcal{M}_{i}( ilde{x}, ilde{y}),$ where ℳ i ( x ~ , y ~ ) := | f - i x ~ - A * y ~ | 2 + | y ~ - A x ~ | 2 ${mathcal{M}_{i}( ilde{x}, ilde{y}):=lvert f-i ilde{x}-mathrm{A}^{*}% ilde{y}
vert^{2}+lvert ilde{y}-mathrm{A} ilde{x}
vert^{2}}$ contains only known data. We will point out a motivation for the study of the latter problems by time discretizations or time-harmonic ansatz of linear partial differential equations and we will present an extensive list of applications including the reaction-diffusion problem and the eddy current problem.