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A computational model for expiratory flow

Lambert, R. K., Wilson, T. A., Hyatt, R. E., Rodarte, J. R.·1982·Journal of Applied Physiology

Abstract

A mathematical model of maximal expiratory flow was developed. Coupled equations describing the pressure losses in the flow and the pressure-area behavior of the airway were integrated along the airway from the periphery to the flow-limiting site. Equations describing pressure losses in the flow were adapted from studied of bronchial casts. The bronchial anatomy utilized was that described by Weibel. Bronchial mechanical properties were obtained from measurements in excised human lungs for the central airways and by extrapolations of these data for the peripheral airways. The maximal flow for air and helium predicted by the model agrees with that of five lungs from which mechanical properties were obtained. The model predictions agree with published values of density and viscosity dependence of maximal flow. At high and midlung volumes, maximal flow is determined primarily by the wave-speed mechanism. At low lung volumes, maximal flow is primarily determined by the coupling of viscous pressure losses and airway mechanical properties.

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Crossref · 10.1152/jappl.1982.52.1.44

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Metadata

Authors
Lambert, R. K., Wilson, T. A., Hyatt, R. E., & Rodarte, J. R.
Venue
Journal of Applied Physiology
Published
1982-01-01
Volume
52
Issue
1
Pages
44-56
ISSN
  • 0161-7567 (ISSN-L)
  • 8750-7587
  • 1522-1601
OpenAlex
W1937043149
Cited by
259
References
0
FWCI
2.43
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A computational model for expiratory flow. https://app.cochat.ai/papers/10.1152/jappl.1982.52.1.44
The paper
Lambert, R. K., Wilson, T. A., Hyatt, R. E., & Rodarte, J. R. (1982). A computational model for expiratory flow. Journal of Applied Physiology. https://doi.org/10.1152/jappl.1982.52.1.44

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.