Partitioned Runge–Kutta–Chebyshev Methods for Diffusion-Advection-Reaction Problems | Zendy

Christophe J. Zbinden | Zendy

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Partitioned Runge–Kutta–Chebyshev Methods for Diffusion-Advection-Reaction Problems

Author(s) -

Christophe J. Zbinden

Publication year - 2011

Publication title -

siam journal on scientific computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.674

H-Index - 147

eISSN - 1095-7197

pISSN - 1064-8275

DOI - 10.1137/100807892

Subject(s) - runge–kutta methods , mathematics , chebyshev filter , stability (learning theory) , diffusion , function (biology) , boundary (topology) , advection , mathematical analysis , algorithm , numerical analysis , computer science , physics , machine learning , evolutionary biology , biology , thermodynamics

An integration method based on Runge–Kutta–Chebyshev (RKC) methods is discussed which has been designed to treat moderately stiff and nonstiff terms separately. The method, called partitioned Runge–Kutta–Chebyshev (PRKC), is a one-step, partitioned RK method of second order. It belongs to the class of stabilized methods, namely explicit RK methods possessing extended real stability intervals. The aim of the PRKC method is to reduce the number of function evaluations of the nonstiff terms and to get a nonzero imaginary stability boundary

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