<p>In this paper, we present and rigorously analyze a novel residual-based <i>a posteriori</i> error estimator for the discontinuous Galerkin (DG) method applied to nonlinear Volterra integro-differential equations. We first prove that the DG solution using piecewise polynomials of degree <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(p \geqslant 1\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo>⩾</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation> achieves the optimal convergence rate of <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\mathcal {O}(h^{p+1})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">O</mi> <mo stretchy="false">(</mo> <msup> <mi>h</mi> <mrow> <mi>p</mi> <mo>+</mo> <mn>1</mn> </mrow> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> in the <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(L^2\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>L</mi> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation>-norm. Moreover, we show that the DG solution exhibits <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\mathcal {O}(h^{2p+1})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">O</mi> <mo stretchy="false">(</mo> <msup> <mi>h</mi> <mrow> <mn>2</mn> <mi>p</mi> <mo>+</mo> <mn>1</mn> </mrow> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> superconvergence at downwind points. These results are used to show that the DG solution is <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\mathcal {O}(h^{p+2})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">O</mi> <mo stretchy="false">(</mo> <msup> <mi>h</mi> <mrow> <mi>p</mi> <mo>+</mo> <mn>2</mn> </mrow> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> superconvergent towards a specific Gauss-Radau projection of the exact solution. This superconvergence result enables a decomposition of the discretization error into two components: a dominant term proportional to a right Radau polynomial of degree <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\((p+1)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">(</mo> <mi>p</mi> <mo>+</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> and a remainder that converges at a rate of <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(\mathcal {O}(h^{p+2})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">O</mi> <mo stretchy="false">(</mo> <msup> <mi>h</mi> <mrow> <mi>p</mi> <mo>+</mo> <mn>2</mn> </mrow> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> in the <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(L^2\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>L</mi> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation>-norm. The global superconvergence properties are used to construct a residual-based <i>a posteriori</i> error estimator. The proposed estimator is computationally efficient, easy to implement, and asymptotically exact. It is constructed by solving local residual problems without imposing initial conditions on each element. We establish convergence of the <i>a posteriori</i> error estimator to the true error at the optimal rate of <InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(\mathcal {O}(h^{p+2})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">O</mi> <mo stretchy="false">(</mo> <msup> <mi>h</mi> <mrow> <mi>p</mi> <mo>+</mo> <mn>2</mn> </mrow> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> under mesh refinement. Finally, we prove that the global effectivity index of the estimator approaches unity at a rate of <InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(\mathcal {O}(h)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">O</mi> <mo stretchy="false">(</mo> <mi>h</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>. Several numerical examples are provided to validate the theoretical results and to illustrate the accuracy and reliability of the proposed estimator.</p>

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A Posteriori Error Estimation for the Discontinuous Galerkin Method Applied to Nonlinear Volterra Integro-differential Equations

  • Mahboub Baccouch

摘要

In this paper, we present and rigorously analyze a novel residual-based a posteriori error estimator for the discontinuous Galerkin (DG) method applied to nonlinear Volterra integro-differential equations. We first prove that the DG solution using piecewise polynomials of degree \(p \geqslant 1\) p 1 achieves the optimal convergence rate of \(\mathcal {O}(h^{p+1})\) O ( h p + 1 ) in the \(L^2\) L 2 -norm. Moreover, we show that the DG solution exhibits \(\mathcal {O}(h^{2p+1})\) O ( h 2 p + 1 ) superconvergence at downwind points. These results are used to show that the DG solution is \(\mathcal {O}(h^{p+2})\) O ( h p + 2 ) superconvergent towards a specific Gauss-Radau projection of the exact solution. This superconvergence result enables a decomposition of the discretization error into two components: a dominant term proportional to a right Radau polynomial of degree \((p+1)\) ( p + 1 ) and a remainder that converges at a rate of \(\mathcal {O}(h^{p+2})\) O ( h p + 2 ) in the \(L^2\) L 2 -norm. The global superconvergence properties are used to construct a residual-based a posteriori error estimator. The proposed estimator is computationally efficient, easy to implement, and asymptotically exact. It is constructed by solving local residual problems without imposing initial conditions on each element. We establish convergence of the a posteriori error estimator to the true error at the optimal rate of \(\mathcal {O}(h^{p+2})\) O ( h p + 2 ) under mesh refinement. Finally, we prove that the global effectivity index of the estimator approaches unity at a rate of \(\mathcal {O}(h)\) O ( h ) . Several numerical examples are provided to validate the theoretical results and to illustrate the accuracy and reliability of the proposed estimator.