Handling effectively the rejected stages in Runge–Kutta pairs implementation

Author:

Xiang Er‐Ping1,Lin Chia‐Liang23,Simos T. E.45678ORCID,Tsitouras Ch.2

Affiliation:

1. PhD Programme, Jingdezhen Ceramic University Jingdezhen Jiangxi Province China

2. General Department National and Kapodistrian University of Athens Euripus Campus Greece

3. Department of Visual Communications Huzhou University Huzhou China

4. Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology West Mishref Kuwait

5. Department of Medical Research China Medical University Hospital, China Medical University Taichung City Taiwan

6. Laboratory of Inter‐Disciplinary Problems in Clean Energy Production Ulyanovsk State Technical University Ulyanovsk Russian Federation

7. Data Recovery Key Laboratory of Sichun Province Neijiang Normal University Neijiang China

8. Section of Mathematics, Department of Civil Engineering Democritus University of Thrace Xanthi Greece

Abstract

Runge–Kutta (RK) pairs are widely used for numerically solving initial value problems (IVPs), but dealing with step rejections during integration is a common occurrence. Conventionally, when a step is rejected, all calculations made during that step are discarded, and a completely new set of computations is initiated. In our research, we propose a method to address this inefficiency by repurposing the previously computed RK stages from rejected steps. Our primary focus is on the renowned RKF45 pair, consisting of fifth‐ and fourth‐order methods. When a step rejection occurs, we leverage the stages computed in prior steps and introduce just three additional stages. These stages are then used to evaluate the results with a smaller step size. This approach effectively reduces computational costs in various challenging IVPs where RK algorithms with different step sizes encounter difficulties

Publisher

Wiley

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4. Solving Ordinary Differential Equations I

5. A case study of fractal-fractional tuberculosis model in China: Existence and stability theories along with numerical simulations

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