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ISSN: 2277-1891

International Journal of Advance Innovations, Thoughts & Ideas
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  • Mini Review   
  • Int J Adv Innovat Thoughts Ideas 2022, Vol 11(5): 186
  • DOI: 10.4172/2277-1891.1000186

An Adaptive Rectangular Mesh Management and Refining Method with Applications to Models of Cancer Invasion

Nikolaos Sfakianakis*
School of Mathematics and Statistics, University of St Andrews, UK
*Corresponding Author : Nikolaos Sfakianakis, School of Mathematics and Statistics, University of St Andrews, UK, Email: nikolsnakis@gmail.com

Received Date: Sep 05, 2022 / Published Date: Sep 28, 2022

Abstract

For the administration of adaptive mesh refinement on (hyper-)rectangular meshes, we provide a method. Our method is an efficient, easy-to-use method for h-refinement on 1-, 2-, and 3-D domains that does not need navigating the connectivity graph of the ancestry of mesh cells. The use of a rectangular mesh structure substantially facilitates the detection of siblings and nearby cells [1-15]. The administration method is especially made for meshes that are smooth since matrix operations use smoothness on an as-needed basis. It is inexpensive for a variety of mesh resolutions over a broad class of issues thanks to its modest memory footprint. We provide three uses for this method, one of which discusses the advantages of h-refinement in a 2D setting.

Adaptive mesh refinement (AMR) has frequently been used to increase the precision of numerical techniques and lessen their computing weight. AMR is frequently used in the domains of engineering, astronomy, and fluid dynamics, where the related techniques have become an essential part of the total numerical inquiry. Mathematical biology, on the other hand, has not yet seen much of their use. Examples are available.

Citation: Sfakianakis N (2022) An Adaptive Rectangular Mesh Management and Refining Method with Applications to Models of Cancer Invasion. Int J Adv Innovat Thoughts Ideas, 11: 186. Doi: 10.4172/2277-1891.1000186

Copyright: © 2022 Sfakianakis N. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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