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Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks
The aim of this paper consists in the derivation of an analytic formula for the hydraulic resistance of capillaries, taking into account the tube hematocrit level. The consistency of the derived formula is verified using Finite Element simulations. Such an effective formula allows for assigning resi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721022/ https://www.ncbi.nlm.nih.gov/pubmed/31531122 http://dx.doi.org/10.1155/2019/4235937 |
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author | Botkin, Nikolai D. Kovtanyuk, Andrey E. Turova, Varvara L. Sidorenko, Irina N. Lampe, Renée |
author_facet | Botkin, Nikolai D. Kovtanyuk, Andrey E. Turova, Varvara L. Sidorenko, Irina N. Lampe, Renée |
author_sort | Botkin, Nikolai D. |
collection | PubMed |
description | The aim of this paper consists in the derivation of an analytic formula for the hydraulic resistance of capillaries, taking into account the tube hematocrit level. The consistency of the derived formula is verified using Finite Element simulations. Such an effective formula allows for assigning resistances, depending on the hematocrit level, to the edges of networks modeling biological capillary systems, which extends our earlier models of blood flow through large capillary networks. Numerical simulations conducted for large capillary networks with random topologies demonstrate the importance of accounting for the hematocrit level for obtaining consistent results. |
format | Online Article Text |
id | pubmed-6721022 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-67210222019-09-17 Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks Botkin, Nikolai D. Kovtanyuk, Andrey E. Turova, Varvara L. Sidorenko, Irina N. Lampe, Renée Comput Math Methods Med Research Article The aim of this paper consists in the derivation of an analytic formula for the hydraulic resistance of capillaries, taking into account the tube hematocrit level. The consistency of the derived formula is verified using Finite Element simulations. Such an effective formula allows for assigning resistances, depending on the hematocrit level, to the edges of networks modeling biological capillary systems, which extends our earlier models of blood flow through large capillary networks. Numerical simulations conducted for large capillary networks with random topologies demonstrate the importance of accounting for the hematocrit level for obtaining consistent results. Hindawi 2019-08-18 /pmc/articles/PMC6721022/ /pubmed/31531122 http://dx.doi.org/10.1155/2019/4235937 Text en Copyright © 2019 Nikolai D. Botkin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Botkin, Nikolai D. Kovtanyuk, Andrey E. Turova, Varvara L. Sidorenko, Irina N. Lampe, Renée Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks |
title | Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks |
title_full | Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks |
title_fullStr | Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks |
title_full_unstemmed | Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks |
title_short | Accounting for Tube Hematocrit in Modeling of Blood Flow in Cerebral Capillary Networks |
title_sort | accounting for tube hematocrit in modeling of blood flow in cerebral capillary networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721022/ https://www.ncbi.nlm.nih.gov/pubmed/31531122 http://dx.doi.org/10.1155/2019/4235937 |
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