A quasi-realistic computational model development and flow field study of the human upper and central airways

The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate a...

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Published inMedical & biological engineering & computing Vol. 62; no. 10; pp. 3025 - 3041
Main Authors Rezazadeh, Mohammad Reza, Dastan, Alireza, Sadrizadeh, Sasan, Abouali, Omid
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2024
Springer Nature B.V
Subjects
Air
Air flow
Air flow-rate
Algorithms
bioinformatics
Biological organs
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
breathing
cadaver
Computational fluid dynamic
Computational fluid dynamics
Computational fluid dynamics (CFD)
Computational modelling
Computed tomography
Computer Applications
Computer Simulation
Computerized tomography
Drops
Drug delivery
drugs
Exhalation
Field study
Flow fields
Fluid dynamics
Fluid flow
Human Physiology
Humans
Hydrodynamics
Imaging
Inhalation
Inhalation and Exhalation
Kitaoka’s algorithm
Kitaokum’s algorithm
Laminar flow
Lung - diagnostic imaging
Lung - physiology
Lung generation
Lung generations
lungs
Model development
Models, Biological
Original Article
Particulate matter
particulates
Physiological effects
Physiological factors
Pressure drop
Radiology
Respiration
Respiratory System - anatomy & histology
Respiratory System - diagnostic imaging
Respiratory tract
Reynold number
Reynolds number
S-algorithms
Three dimensional models
Tomography, X-Ray Computed
Trachea
Trachea - diagnostic imaging
Trachea - physiology
Velocity
Respiratory tract
Kitaoka’s algorithm
Computational fluid dynamics (CFD)
Lung generations
Inhalation and Exhalation
Online AccessGet full text
ISSN0140-0118
1741-0444
1741-0444
DOI10.1007/s11517-024-03117-9

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Abstract The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka’s deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka’s model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract. Graphical Abstract
AbstractList The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka’s deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka’s model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract.
The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka's deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka's model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract.The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka's deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka's model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract.
The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka's deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka's model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract.
The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka’s deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka’s model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract. Graphical Abstract
The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka’s deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka’s model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract. Graphical Abstract: (Figure presented.)
The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka’s deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka’s model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract. Graphical Abstract: (Figure presented.)
Author Dastan, Alireza
Sadrizadeh, Sasan
Abouali, Omid
Rezazadeh, Mohammad Reza
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  surname: Rezazadeh
  fullname: Rezazadeh, Mohammad Reza
  organization: School of Mechanical Engineering, Shiraz University
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  givenname: Alireza
  surname: Dastan
  fullname: Dastan, Alireza
  organization: Department of Mechanical Engineering, Faculty of Engineering, University of Isfahan
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  givenname: Sasan
  surname: Sadrizadeh
  fullname: Sadrizadeh, Sasan
  email: ssad@kth.se
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  givenname: Omid
  orcidid: 0000-0002-0967-4672
  surname: Abouali
  fullname: Abouali, Omid
  email: abouali@shirazu.ac.ir
  organization: School of Mechanical Engineering, Shiraz University, Department of Civil and Architectural Engineering, KTH University
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1741-0444
IngestDate Thu Oct 30 11:29:37 EDT 2025
Tue Sep 09 23:29:53 EDT 2025
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IsPeerReviewed true
IsScholarly true
Issue 10
Keywords Respiratory tract
Kitaoka’s algorithm
Computational fluid dynamics (CFD)
Lung generations
Inhalation and Exhalation
Language English
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SubjectTerms Air
Air flow
Air flow-rate
Algorithms
bioinformatics
Biological organs
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
breathing
cadaver
Computational fluid dynamic
Computational fluid dynamics
Computational fluid dynamics (CFD)
Computational modelling
Computed tomography
Computer Applications
Computer Simulation
Computerized tomography
Drops
Drug delivery
drugs
Exhalation
Field study
Flow fields
Fluid dynamics
Fluid flow
Human Physiology
Humans
Hydrodynamics
Imaging
Inhalation
Inhalation and Exhalation
Kitaoka’s algorithm
Kitaokum’s algorithm
Laminar flow
Lung - diagnostic imaging
Lung - physiology
Lung generation
Lung generations
lungs
Model development
Models, Biological
Original Article
Particulate matter
particulates
Physiological effects
Physiological factors
Pressure drop
Radiology
Respiration
Respiratory System - anatomy & histology
Respiratory System - diagnostic imaging
Respiratory tract
Reynold number
Reynolds number
S-algorithms
Three dimensional models
Tomography, X-Ray Computed
Trachea
Trachea - diagnostic imaging
Trachea - physiology
Velocity
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