Numerical analysis of human airways natural breathing characteristics

This study offers novel insights into the natural breathing of human airways by utilizing a CT-scan-based in-silico model, which spans from the nasal cavity to the 6th generation bronchi- a comprehensive, non-invasive simulation explicitly tailored to a healthy 45-year-old male participant. Unlike previous models, this work captures the inherent asymmetry of the nasal cycle, providing a detailed analysis of airflow that deviates from the conventional assumption of symmetric breathing cycles. Specifically, in this study we analyse the naturally occurring tidal volume ratio of 2/3 during inhalation and 1/3 during exhalation, a ratio often overlooked in traditional pulmonary function tests (PFTs), which are limited by their assumption of symmetry. A key innovation of this study is the transient simulation of asymmetric breathing under light breathing conditions (Q = 10 L/min), which is compared with symmetric inspiratory airflow profiles. By employing user-defined functions (UDFs) within the numerical solver, we accurately model natural inflow velocity conditions, enabling the first detailed comparison of asymmetric and symmetric air exchange processes in human airways. Additionally, the use of the Realizable k–ε turbulence model, refined for low Reynolds number conditions, further enhances the accuracy of airflow dynamics analysis during respiration. The novel identification and explanation of the subtle distinctions between symmetric and asymmetric breathing patterns provide critical insights into their consequences for airway function. These findings lay the foundation for future investigations into abnormal airway flow characteristics, offering new directions for respiratory research and clinical applications.

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Publication Details

Journal
Discover Applied Sciences
Published
2025-11-03
DOI
https://doi.org/10.1007/s42452-025-07368-5
Primary Topic
Inhalation and Respiratory Drug Delivery
Type
article
Field-Weighted Citation Impact
0.00

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article

Numerical analysis of human airways natural breathing characteristics

Bholu Kumar, Digamber Singh, Md Roknujjaman
Discover Applied Sciences
Inhalation and Respiratory Drug Delivery
article

Numerical analysis of human airways natural breathing characteristics

Bholu Kumar, Digamber Singh, Md Roknujjaman
article en

Abstract

This study offers novel insights into the natural breathing of human airways by utilizing a CT-scan-based in-silico model, which spans from the nasal cavity to the 6th generation bronchi- a comprehensive, non-invasive simulation explicitly tailored to a healthy 45-year-old male participant. Unlike previous models, this work captures the inherent asymmetry of the nasal cycle, providing a detailed analysis of airflow that deviates from the conventional assumption of symmetric breathing cycles. Specifically, in this study we analyse the naturally occurring tidal volume ratio of 2/3 during inhalation and 1/3 during exhalation, a ratio often overlooked in traditional pulmonary function tests (PFTs), which are limited by their assumption of symmetry. A key innovation of this study is the transient simulation of asymmetric breathing under light breathing conditions (Q = 10 L/min), which is compared with symmetric inspiratory airflow profiles. By employing user-defined functions (UDFs) within the numerical solver, we accurately model natural inflow velocity conditions, enabling the first detailed comparison of asymmetric and symmetric air exchange processes in human airways. Additionally, the use of the Realizable k–ε turbulence model, refined for low Reynolds number conditions, further enhances the accuracy of airflow dynamics analysis during respiration. The novel identification and explanation of the subtle distinctions between symmetric and asymmetric breathing patterns provide critical insights into their consequences for airway function. These findings lay the foundation for future investigations into abnormal airway flow characteristics, offering new directions for respiratory research and clinical applications.

Discover Applied SciencesVol. 7(11)
Alliance University (IN), Rochester Institute of Technology (US), Poornima University (IN)
Motilal Nehru National Institute of Technology Allahabad
Openalex Percentile: Top 54%
Inhalation and Respiratory Drug Delivery
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