<p>This paper focuses on the analysis of convergence and superconvergence properties of an ultra-weak discontinuous Galerkin (UWDG) method for nonlinear second-order Volterra integro-differential equations. The key idea for deriving optimal error estimates in the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(L^2\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>L</mi> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation>-norm is the use of appropriately chosen numerical fluxes together with a specially designed projection. When piecewise polynomials of degree <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(p \ge 2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo>≥</mo> <mn>2</mn> </mrow> </math></EquationSource> </InlineEquation> are employed, the proposed UWDG method is shown to achieve the optimal convergence order of <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(p+1\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo>+</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation>. Moreover, we prove that the UWDG solution exhibits superconvergence of order <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(p+2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo>+</mo> <mn>2</mn> </mrow> </math></EquationSource> </InlineEquation> toward a suitable projection of the exact solution. In addition, both the <i>p</i>-degree UWDG solution and its derivative are shown to be <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\mathcal {O}(h^{2p})\)</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> </mrow> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> superconvergent at the end of each time step. These theoretical results hold for arbitrary regular meshes and piecewise polynomial spaces of degree <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(p \ge 2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo>≥</mo> <mn>2</mn> </mrow> </math></EquationSource> </InlineEquation>. Finally, several numerical experiments are presented to confirm the theoretical findings. Notably, the proposed UWDG method offers a significant advantage over standard discontinuous Galerkin methods for first-order systems, as it can be applied directly without introducing auxiliary variables or reformulating the problem as a larger system, thereby reducing both memory requirements and computational cost.</p>

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Superconvergence analysis of an ultra-weak discontinuous Galerkin method for nonlinear second-order volterra integro-differential equations

  • Mahboub Baccouch

摘要

This paper focuses on the analysis of convergence and superconvergence properties of an ultra-weak discontinuous Galerkin (UWDG) method for nonlinear second-order Volterra integro-differential equations. The key idea for deriving optimal error estimates in the \(L^2\) L 2 -norm is the use of appropriately chosen numerical fluxes together with a specially designed projection. When piecewise polynomials of degree \(p \ge 2\) p 2 are employed, the proposed UWDG method is shown to achieve the optimal convergence order of \(p+1\) p + 1 . Moreover, we prove that the UWDG solution exhibits superconvergence of order \(p+2\) p + 2 toward a suitable projection of the exact solution. In addition, both the p-degree UWDG solution and its derivative are shown to be \(\mathcal {O}(h^{2p})\) O ( h 2 p ) superconvergent at the end of each time step. These theoretical results hold for arbitrary regular meshes and piecewise polynomial spaces of degree \(p \ge 2\) p 2 . Finally, several numerical experiments are presented to confirm the theoretical findings. Notably, the proposed UWDG method offers a significant advantage over standard discontinuous Galerkin methods for first-order systems, as it can be applied directly without introducing auxiliary variables or reformulating the problem as a larger system, thereby reducing both memory requirements and computational cost.