Application of High-Performance Computing for Modeling the Hydrobiological Processes in Shallow Water
The paper covers the development and research of a mathematical model for description hydrobiological processes using the modern information technologies and computational methods to improve the accuracy of predictive modeling the ecological situation in shallow waters. The model takes into account...
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Published in | Supercomputing pp. 166 - 181 |
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Main Authors | , , , , |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
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Series | Communications in Computer and Information Science |
Subjects | |
Online Access | Get full text |
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Summary: | The paper covers the development and research of a mathematical model for description hydrobiological processes using the modern information technologies and computational methods to improve the accuracy of predictive modeling the ecological situation in shallow waters. The model takes into account the following factors: movement of water flows; microturbulent diffusion; gravitational settling of pollutants; nonlinear interaction of phyto- and zooplankton populations; nutrient, temperature and oxygen regimes; and influence of salinity. A space splitting scheme taking into account the partial filling of cells was proposed for model discretization. This scheme significantly reduces both error and calculation time. The practical significance of the paper is determined by software implementation of the model and the determination of limits and prospects of its practical use. Experimental software is designed on the basis of a supercomputer for mathematical modeling of possible development scenarios of shallow water ecosystems taking into account the influence of environment. For this, we consider as an example the Azov Sea in summer. The parallel implementation involves decomposition methods for computationally laborious diffusion-convection problems taking into account the architecture and parameters of a multiprocessor computer system. |
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Bibliography: | This paper was partially supported by grant No. 17-11-01286 of the Russian Science Foundation. |
ISBN: | 9783030365912 3030365913 |
ISSN: | 1865-0929 1865-0937 |
DOI: | 10.1007/978-3-030-36592-9_14 |