Numerical solutions of random mean square Fisher-KPP models with advection
| Autor: | M.-C. Casabán, LUCAS JODAR, Rafael Company Rossi |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Mean square
Advection Semidiscretization General Mathematics Mean square random calculus Partial differential equations with randomness General Engineering Applied mathematics Computational methods for stochastic equations Random Fisher-KPP equation MATEMATICA APLICADA Exponential time differencing Mathematics |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| Popis: | [EN] This paper deals with the construction of numerical stable solutions of random mean square Fisher-Kolmogorov-Petrosky-Piskunov (Fisher-KPP) models with advection. The construction of the numerical scheme is performed in two stages. Firstly, a semidiscretization technique transforms the original continuous problem into a nonlinear inhomogeneous system of random differential equations. Then, by extending to the random framework, the ideas of the exponential time differencing method, a full vector discretization of the problem addresses to a random vector difference scheme. A sample approach of the random vector difference scheme, the use of properties of Metzler matrices and the logarithmic norm allow the proof of stability of the numerical solutions in the mean square sense. In spite of the computational complexity, the results are illustrated by comparing the results with a test problem where the exact solution is known. Ministerio de Economia y Competitividad, Grant/Award Number: MTM2017-89664-P |
| Databáze: | OpenAIRE |
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