Variational Analysis and Galerkin Method in Infinite Dimension: Theory, Convergence and Extension for the Poisson

Authors

  • Ndogotar Nelio
  • Gabyi Sewore
  • Ngarkodje Ngarasta
  • Koina Rodoumta

Keywords:

Poisson equation, variational formulation, Galerkin method, finite element method, a priori error estimates, numerical experiments, nonlinear elliptic PDEs

Abstract

This paper presents a concise and conceptually unified exposition of the variational formulation and Galerkin finite element discretization of the Poisson equation with Dirichlet boundary conditions. The problem is posed in the Sobolev space  , where well-posedness is established via the Lax–Milgram theorem. Standard a priori error estimates are derived, including quasi-optimal convergence in the energy norm through Céa’s lemma and an -error bound obtained by the Aubin–Nitsche duality argument under suitable elliptic regularity assumptions. Reproducible numerical experiments in one dimension using  elements and in two dimensions using  elements on uniform meshes confirm the optimal convergence rates        and   . The paper weaves together functional-analytic foundations, finite element assembly, and visual diagnostics into a coherent end-to-end narrative, and briefly explores extensions to semilinear and quasilinear elliptic problems.

Author Biographies

  • Ndogotar Nelio

    Department of Mathematics and Computer Science, University of Sarh, Sarh BP 105, Chad

  • Gabyi Sewore

    Department of Mathematics and Computer Science,University of Sarh, Sarh BP 105,Chad

  • Ngarkodje Ngarasta

    Department of Mathematics and Computer Science,University of Sarh, Sarh BP 105,Chad

  • Koina Rodoumta

    National School of Civil Engineering, Ndjamena, Chad

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Published

2026-06-12

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Articles

How to Cite

Ndogotar Nelio, Gabyi Sewore, Ngarkodje Ngarasta, & Koina Rodoumta. (2026). Variational Analysis and Galerkin Method in Infinite Dimension: Theory, Convergence and Extension for the Poisson. International Journal of Sciences: Basic and Applied Research (IJSBAR), 79(1), 197-215. https://www.gssrr.org/JournalOfBasicAndApplied/article/view/17681