Numerical solution of second-order ordinary differential equations with singular source term using fourth-order Runge-Kutta methods
DOI:
https://doi.org/10.14393/BEJOM-v7-2026-77844Keywords:
Fourth-order Runge-Kutta, Numerical verification, Dirac DeltaAbstract
This work numerically investigates initial value problems governed by ordinary differential equations with source terms of Dirac delta type, using a direct approach based on classical Runge--Kutta methods. In contrast to the literature on impulsive systems, where singularities are handled through jump conditions at known times, the singularity is explicitly treated via a regularization of the Dirac delta. Five approximation functions are considered: one with non-compact support and four with compact support, the latter being widely used in fluid--structure interaction problems within the framework of Peskin's immersed boundary method. The classical RK4 and the RK46 methods were implemented in the C programming language and first validated using test problems with smooth solutions, for which both methods achieved the expected fourth-order convergence. When applied to problems with singular sources, the results reveal a significant loss of convergence order, with observed values below one, indicating limitations of the direct approach. Nevertheless, the RK46 method showed slightly better performance than RK4 in terms of absolute error, and the regularization function with non-compact support yielded the best results among the approximations considered. These findings provide a systematic assessment of the behavior of classical methods in the presence of directly treated singularities and highlight the need for the development of more robust numerical schemes for this class of problems. They also motivate further investigation into alternative regularization functions for approximating the Dirac delta, aiming at improved numerical accuracy.Downloads
References
Abouelkheir, I.; El Kihal, F.; Rachik, M.; Elmouki, I. Optimal impulse vaccination approach for an SIR control model with short-term immunity. Mathematics 7 (2019), no. 5, 420. DOI: 10.3390/math7050420.
Peskin, C. S. The immersed boundary method. Acta Numerica 11 (2002), 479–517. DOI: 10.1017/S0962492902000077.
Suarez, J. P. et al. A high-order Dirac-Delta Regularization with optimal scaling in the spectral solution of one dimensional singular hyperbolic conservation laws. SIAM Journal on Scientific Computing 36 (2014), no. 4, A1831–A1849. DOI: 10.1137/130939341.
Bainov, D. D.; Simeonov, P. Impulsive Differential Equations: Asymptotic Properties of the Solutions. Singapore: World Scientific Publishing Company, 1995.
Liang, H.; Song, M. H.; Liu, M. Z. Stability of the analytic and numerical solutions for impulsive differential equations. Applied Numerical Mathematics 61 (2011), no. 11, 1103–1113. DOI: 10.1016/j.apnum.2010.12.005.
Santos, L. H. C. Equações diferenciais impulsivas: uma abordagem sobre estabilidade e métodos numéricos. C.Q.D.– Revista Eletrônica Paulista de Matemática 23 (2023), no. 1, 111–140.
Li, C.; Hui, F.; Li, F. Stability of differential systems with impulsive effects. Mathematics 11 (2023), no. 20, 4382. DOI: 10.3390/math11204382.
Xing, B. et al. Neural network methods based on efficient optimization algorithms for solving impulsive differential equations. IEEE Transactions on Artificial Intelligence 5 (2024), no. 3, 1067–1076. DOI: 10.1109/TAI.2022.3217207.
Zill, D. G.; Cullen, M. R. Equações Diferenciais. São Paulo: Pearson, 2001.
Allampalli, V. et al. High accuracy large-step explicit Runge-Kutta (HALE-RK) schemes for computational aeroacoustics. Journal of Computational Physics 228 (2009), no. 10, 3837–3850. DOI: 10.1016/j.jcp.2009.05.030.
Monteiro, L. M.; Mariano, F. P. Flow modeling over airfoils and vertical axis wind turbines using Fourier Pseudo-Spectral method and coupled Immersed Boundary Method. Axioms 12 (2023), no. 2, 212. DOI: 10.3390/axioms12020212.
Scherer, C. Métodos Computacionais da Física. São Paulo: Livraria da Física, 2010.
Hairer, E.; Nørsett, S. P.; Wanner, G. Solving Ordinary Differential Equations I: Nonstiff Problems. 2ª ed. Springer, 1993.
Roache, P. J. Verification and Validation in Computational Science and Engineering. Hermosa Publishers, 1998.
Roy, C. J. Review of code and solution verification procedures for computational simulation. Journal of Computational Physics 205 (2005), no. 1, 131–156. DOI: 10.1016/j.jcp.2004.10.036.
Rufato, R. C.; Enriquez-Remigio, S. A.; Morais, T. S. Application of direct integration methods in the solution of a nonlinear beam problem. REMAT: Revista Eletrônica da Matemática 7 (2021), no. 1, e3002. DOI: 10.35819/remat2021v7i1id4277.
Yang, X. et al. A smoothing technique for discrete delta functions with application to immersed boundary method in moving boundary simulations. Journal of Computational Physics 228 (2009), no. 20, 7821–7836. DOI: 10.1016/j.jcp.2009.07.023.
Halliday, D.; Resnick, R.; Walker, J. Fundamentos de Física, Vol. 1: Mecânica. 10ª ed. Rio de Janeiro: LTC, 2016.
Butkov, E. Física Matemática. Rio de Janeiro: Livros Técnicos e Científicos, 1978.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Santos Alberto Enriquez Remigio, Davi de Mélo Cordeiro

This work is licensed under a Creative Commons Attribution 4.0 International License.
- Articles published from 2025 onwards are licensed under the CC BY 4.0 license. By submitting material for publication, authors automatically agree to the journal’s editorial guidelines and affirm that the text has been properly reviewed. Simultaneous submission of articles to other journals is prohibited, as is the translation of articles published in this journal into another language without proper authorization.
- Articles published prior to 2025 are licensed under the CC BY-NC 4.0 license.






