Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156096
Title: Computational modeling of nonlinear reaction-diffusion Fisher–KPP equation with mixed modal discontinuous Galerkin scheme
Authors: Singh, Satyvir
Keywords: Science::Mathematics::Applied mathematics::Simulation and modeling
Issue Date: 2022
Publisher: CRC Press
Source: Singh, S. (2022). Computational modeling of nonlinear reaction-diffusion Fisher–KPP equation with mixed modal discontinuous Galerkin scheme. M. K. Awasthi, R. Tomar & M. Gupta (Eds.), Mathematical Modeling for Intelligent Systems: Theory, Methods and Simulation. CRC Press. https://hdl.handle.net/10356/156096
Project: NAP-SUP M408074
Abstract: In this study, a mixed modal discontinuous Galerkin (DG) scheme is developed for solving the two-dimensional nonlinear Fisher-Kolmogorov-Petrovsky-Piscounov (Fisher–KPP) reaction-diffusion equation emerging in biology sciences. This numerical scheme is based on the concept of addressing an additional auxiliary unknown in the high-order derivative diffusion term. The scaled Legendre polynomials with third-order accuracy are used for spatial discretization, while, an explicit Strongly Stability Preserving Runge-Kutta scheme with third-order accuracy is adopted for the temporal discretization. This numerical approach is widely applicable for several nonlinear reaction-diffusion problems. To verify the accuracy and reliability of the DG scheme, several well-known numerical problems in literature are solved. The derived numerical solutions and errors show that the results are in good agreement with the exact solutions. This proposed DG approach demonstrates that it is an efficient technique for finding numerical solutions for a wide range of linear and nonlinear physical models.
URI: https://hdl.handle.net/10356/156096
ISBN: 9781032272252
DOI: 10.1201/9781003291916
Schools: School of Physical and Mathematical Sciences 
Rights: This is an Accepted Manuscript of a book chapter published by CRC Press in Mathematical Modeling for Intelligent Systems: Theory, Methods and Simulation on 29 July 2022, available online at https://doi.org/10.1201/9781003291916.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Books & Book Chapters

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