Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Implicit Runge-Kutta Methods Based on Gauss-Kronrod-Lobatto Quadrature Formulae

View through CrossRef
In this paper, four new implicit Runge-Kutta methods which based on 7-point Gauss-Kronrod-Lobatto quadrature formula were developed. The resulting implicit methods were 7-stage tenth order Gauss-Kronrod-Lobatto III (GKLM(7,10)-III), 7-stage tenth order Gauss-Kronrod-Lobatto IIIA (GKLM(7,10)-IIIA), 7-stage tenth order Gauss-Kronrod-Lobatto IIIB (GKLM(7,10)-IIIB) and 7-stage tenth order Gauss-Kronrod-Lobatto IIIC (GKLM(7,10)-IIIC). Each of these methods required 7 function of evaluations at each integration step and gave accuracy of order 10. Theoretical analyses showed that the stage order for GKLM(7,10)-III, GKLM(7,10)-IIIA, GKLM(7,10)-IIIB and GKLM(7,10)-IIIC are 6, 7, 3 and 4, respectively. GKLM(7,10)-IIIC possessed the strongest stability condition i.e. L-stability, followed by GKLM(7,10)-IIIA and GKLM(7,10)-IIIB which both possessed A-stability, and lastly GKLM(7,10)-III having finite region of absolute stability. Numerical experiments compared the accuracy of these four implicit methods and the classical 5-stage tenth order Gauss-Legendre method in solving some test problems. Numerical results revealed that, GKLM(7,10)-IIIA was the most accurate method in solving a scalar stiff problem. All the proposed methods were found to have comparable accuracy and more accurate than the 5-stage tenth order Gauss-Legendre method in solving a two-dimensional stiff problem.
Title: Implicit Runge-Kutta Methods Based on Gauss-Kronrod-Lobatto Quadrature Formulae
Description:
In this paper, four new implicit Runge-Kutta methods which based on 7-point Gauss-Kronrod-Lobatto quadrature formula were developed.
The resulting implicit methods were 7-stage tenth order Gauss-Kronrod-Lobatto III (GKLM(7,10)-III), 7-stage tenth order Gauss-Kronrod-Lobatto IIIA (GKLM(7,10)-IIIA), 7-stage tenth order Gauss-Kronrod-Lobatto IIIB (GKLM(7,10)-IIIB) and 7-stage tenth order Gauss-Kronrod-Lobatto IIIC (GKLM(7,10)-IIIC).
Each of these methods required 7 function of evaluations at each integration step and gave accuracy of order 10.
Theoretical analyses showed that the stage order for GKLM(7,10)-III, GKLM(7,10)-IIIA, GKLM(7,10)-IIIB and GKLM(7,10)-IIIC are 6, 7, 3 and 4, respectively.
GKLM(7,10)-IIIC possessed the strongest stability condition i.
e.
L-stability, followed by GKLM(7,10)-IIIA and GKLM(7,10)-IIIB which both possessed A-stability, and lastly GKLM(7,10)-III having finite region of absolute stability.
Numerical experiments compared the accuracy of these four implicit methods and the classical 5-stage tenth order Gauss-Legendre method in solving some test problems.
Numerical results revealed that, GKLM(7,10)-IIIA was the most accurate method in solving a scalar stiff problem.
All the proposed methods were found to have comparable accuracy and more accurate than the 5-stage tenth order Gauss-Legendre method in solving a two-dimensional stiff problem.

Related Results

Μέθοδοι Runge-Kutta και Runge-Kutta-Nystrom με ειδικές ιδιότητες για την επίλυση διαφορικών εξισώσεων
Μέθοδοι Runge-Kutta και Runge-Kutta-Nystrom με ειδικές ιδιότητες για την επίλυση διαφορικών εξισώσεων
Στην παρούσα διδακτορική διατριβή μελετάται η αριθμητική επίλυση συστημάτων πρωτοβάθμιων και δευτεροβάθμιων συνήθων διαφορικών εξισώσεων με λύση ταλαντωτικής μορφής. Για την αριθμη...
Gauss-Simpson Quadrature Algorithm for Calcaulting Additional Stress in Foundation Soils
Gauss-Simpson Quadrature Algorithm for Calcaulting Additional Stress in Foundation Soils
Abstract The additional pressure at the bottom of a building’s foundation produces an additional stress in the foundation soils under the building’s foundation. In order to...
Characteristics of the Differential Quadrature Method and Its Improvement
Characteristics of the Differential Quadrature Method and Its Improvement
The differential quadrature method has been widely used in scientific and engineering computation. However, for the basic characteristics of time domain differential quadrature met...
Symplectic Partitioned Runge-Kutta and Symplectic Runge-Kutta Methods Generated by 2-Stage RadauIA Method
Symplectic Partitioned Runge-Kutta and Symplectic Runge-Kutta Methods Generated by 2-Stage RadauIA Method
To preserve the symplecticity property, it is natural to require numerical integration of Hamiltonian systems to be symplectic. As a famous numerical integration, it is known that ...
Simulasi Perilaku Fluks Neutron di Reaktor RSG-GAS dengan Metode RUNGE KUTTA
Simulasi Perilaku Fluks Neutron di Reaktor RSG-GAS dengan Metode RUNGE KUTTA
Pemodelan reaktor sebagai sebuah titik menghasilkan satu set pasangan persamaan diferensial biasa yang disebut sebagai persamaan kinetika reaktor titik (reactor point kinetic). Per...
Method for Estimating and Compensating the Phase Imbalance of Quadrature Signal Components
Method for Estimating and Compensating the Phase Imbalance of Quadrature Signal Components
Currently, methods of direct modulation using complex signals are widely used. A complex signal consists of in-phase I (In-phase) and quadrature Q (Quadrature) components. When a s...
Nullspaces yield new explicit Runge--Kutta pairs
Nullspaces yield new explicit Runge--Kutta pairs
Abstract Sixty years ago Butcher [1] characterized a natural tabulation of the or- der conditions for Runge{Kutta methods as an isomorphism from the set of rooted trees hav...
Quasi-dynamic opposite learning enhanced Runge-Kutta optimizer for solving complex optimization problems
Quasi-dynamic opposite learning enhanced Runge-Kutta optimizer for solving complex optimization problems
Abstract The Runge-Kutta Optimization (RUNGE) algorithm is a recently proposed metaphor-free metaheuristic optimizer borrowing practical mathematical foundations of the fam...

Back to Top