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Regional Deposition: Deposition Models.
- Source :
-
Journal of Aerosol Medicine & Pulmonary Drug Delivery . Oct2020, Vol. 33 Issue 5, p239-248. 10p. - Publication Year :
- 2020
-
Abstract
- Modeling particle deposition in the human lung requires information about the morphology of the lung in terms of simple geometric units, e.g., characterizing bronchial airways by straight cylindrical tubes. Five different regional deposition models are discussed in this section with respect to morphometric lung models and related mathematical modeling techniques: 1) one-dimensional cross-section or "trumpet" model, 2) deterministic symmetric generation or "single-path" model, 3) deterministic asymmetric generation or "multiple-path" model, 4) stochastic asymmetric generation or "multiple-path" model, and 5) single-path computational fluid and particle dynamics (CFPD) model. Current deposition models can predict the following regional deposition quantities relevant for the administration of medical aerosols: 1) regional bronchial and alveolar deposition, 2) generational lung deposition, 3) lobar deposition, 4) generational lobar deposition, and 5) generational surface deposition. Although deposition fractions predicted by the different models depend on the selection of a specific morphometric lung model and a specific set of analytical deposition equations, all models predict the same trends as functions of particle diameter and breathing parameters. In general, the overall agreement between the modeling predictions obtained by the various deposition models and the available experimental evidence indicates that current deposition models correctly predict regional and generational deposition. [ABSTRACT FROM AUTHOR]
- Subjects :
- *COMPUTATIONAL fluid dynamics
*MATHEMATICAL models
Subjects
Details
- Language :
- English
- ISSN :
- 19412711
- Volume :
- 33
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Journal of Aerosol Medicine & Pulmonary Drug Delivery
- Publication Type :
- Academic Journal
- Accession number :
- 146171999
- Full Text :
- https://doi.org/10.1089/jamp.2020.29031.wh