Construction of Additive Semi-Implicit Runge-Kutta methods with low-storage requirements
It addresses memory storage limitations in large-scale simulations of time-dependent PDEs for computational scientists, but the contribution is incremental as it extends existing ASIRK methods.
The paper constructs second-order, 3-stage Additive Semi-Implicit Runge-Kutta methods with low-storage requirements for solving additive ODEs with stiff and non-stiff terms, demonstrating advantages through numerical experiments.
Space discretization of some time-dependent partial differential equations gives rise to systems of ordinary differential equations in additive form whose terms have different stiffness properties. In these cases, implicit methods should be used to integrate the stiff terms while efficient explicit methods can be used for the non-stiff part of the problem. However, for systems with a large number of equations, memory storage requirement is also an important issue. When the high dimension of the problem compromises the computer memory capacity, it is important to incorporate low memory usage to some other properties of the scheme. In this paper we consider Additive Semi-Implicit Runge-Kutta (ASIRK) methods, a class of implicitexplicit Runge-Kutta methods for additive differential systems. We construct two second order 3-stage ASIRK schemes with low-storage requirements. Having in mind problems with stiffness parameters, besides accuracy and stability properties, we also impose stiff accuracy conditions. The numerical experiments done show the advantages of the new methods.