NUMERICAL SOLUTION OF THE DIRICHLET PROBLEM FOR A STATIONARY NONLINEAR SYSTEM OF PARTIAL DIFFERENTIAL EQUATIONS

Authors

  • Bobur Islomov Author
  • Jasurbek Sharipov Author
  • Tojiddin Khojiev Author

Abstract

This paper presents a numerical solution to the Dirichlet problem applied to a stationary nonlinear system of partial differential equations. The methodology integrates the pseudo-time stepping method with finite difference schemes, utilizing the backward sweep algorithm (Thomas algorithm) and the method of alternating directions (MAD). Comprehensive numerical experiments validate the proposed framework, demonstrating second-order spatial convergence and robust stability across highly coupled nonlinear domains. Furthermore, the study shows that the judicious selection of initial approximations is critical for accelerating steady-state convergence and mitigating computational overhead in strongly nonlinear scenarios.

References

[1] T. K. Khojiev and B. A. Islomov. On the numerical modeling of a nonlinear stationary heat conduction problem with Dirichlet boundary conditions. Educational Research in Universal Sciences, 2(5), June 2023.

[2] D. H. Sattinger. Monotone methods in nonlinear elliptic and parabolic boundary value problems. Indiana University Mathematics Journal, 21(11):979–1000, 1972.

[3] M. M. Aripov and T. K. Khojiev. Algorithm and program for solving the first boundary value problem of a system of nonlinear elliptic equations. Algorithms of Applied and Computational Mathematics, 55:52–60, 1984.

[4] Hiroshi Fujita. On the nonlinear equations δu +e^u= 0 and ∂/∂t v = δv + e^v. Technical report, University of Tokyo, 1968.

[5] D. W. Drott and R. Aris. Communication on the theory of diffusion and reaction.Chemical Engineering Science, 24:541–551, 1969.

[6] T. K. Khojiev and N. N. Karimov. Numerical modeling of a nonlinear heat conduction problem by the Fourier method. In NUUz. Contemporary Mathematics and its Applications, 2021.

[7] Bobur Islomov. Automodel solution and numerical approximation of a cross-diffusion system with variable density of the non-divergent type. International Multidisci-plinary Research in Academic Science, 7(6):531–536, June 2024.

[8] A. A. Samarskii. The Theory of Difference Schemes. CRC Press, New York, 2001. Fundamental reference for operational formulations of finite difference methods.

[9] S. K. Godunov and V. S. Ryabenkii. Difference Schemes: An Introduction to the Underlying Theory. North-Holland, Amsterdam, 1987. A fundamental reference for the stability of finite difference methods and the establishment method.

[10] Jim Douglas and James E. Gunn. A general formulation of alternating direction methods. Numerische Mathematik, 6(1):428–453, 1962. Advancement of the MAD/ADI method for multi-dimensional problems.

[11] Nanako Shigesada, Kohkichi Kawasaki, and Ei Teramoto. Spatial segregation of interacting species. Journal of Theoretical Biology, 79(1):83–99, 1979. Fundamental study on cross-diffusion systems in biological populations.

[12] D. W. Peaceman and H. H. Rachford. The numerical solution of parabolic and elliptic differential equations. Journal of the Society for Industrial and Applied Mathematics, 3(1):28–41, 1955. Classic paper introducing the Alternating Direction Implicit (ADI/MAD) method.

[13] Herbert Amann. Dynamic theory of quasilinear parabolic equations. ii. reaction-diffusion systems. Differential and Integral Equations, 3(1):13–75, 1989. Crucial for the theoretical stability and convergence analysis of nonlinear systems.

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Published

2026-03-08