<p>Normal breathing induces significant variations in Reynolds numbers throughout the human airways, resulting in distinct flow regimes. However, the onset of instabilities and the development of flow structures in this context are not yet fully understood. This study presents the application of a novel point-wise measurement technique, Correlation Velocimetry (CV), to investigate unsteady velocity variations within breathing cycles at very high temporal resolution over a strongly extended measurement duration. Our approach enabled the evaluation of velocity data from more than 1000 successive breathing cycles in a realistic airway model, providing unprecedented statistical robustness. We observed both high- and low-frequency oscillating structures with spatial and temporal coherence across all investigated breathing regimes, ranging from Reynolds numbers of 274 to 4382. The cycle-to-cycle repeatability of these structures suggests the presence of defined physical mechanisms. Contrary to previous interpretations attributing similar fluctuations to turbulence or transitional states, our analysis indicates that these oscillations likely arise from geometric features forming systems of harmonic oscillators driven by the fundamental breathing frequency. This study provides new insights into the complex, multi-scale nature of respiratory airflow dynamics, challenging existing models and offering implications for improving computational simulations and our understanding of respiratory physiology.</p>

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Deterministic periodic structures in a model of the human airways

  • M. Kluwe,
  • T. Rockstroh,
  • H. Chaves,
  • K. Bauer

摘要

Normal breathing induces significant variations in Reynolds numbers throughout the human airways, resulting in distinct flow regimes. However, the onset of instabilities and the development of flow structures in this context are not yet fully understood. This study presents the application of a novel point-wise measurement technique, Correlation Velocimetry (CV), to investigate unsteady velocity variations within breathing cycles at very high temporal resolution over a strongly extended measurement duration. Our approach enabled the evaluation of velocity data from more than 1000 successive breathing cycles in a realistic airway model, providing unprecedented statistical robustness. We observed both high- and low-frequency oscillating structures with spatial and temporal coherence across all investigated breathing regimes, ranging from Reynolds numbers of 274 to 4382. The cycle-to-cycle repeatability of these structures suggests the presence of defined physical mechanisms. Contrary to previous interpretations attributing similar fluctuations to turbulence or transitional states, our analysis indicates that these oscillations likely arise from geometric features forming systems of harmonic oscillators driven by the fundamental breathing frequency. This study provides new insights into the complex, multi-scale nature of respiratory airflow dynamics, challenging existing models and offering implications for improving computational simulations and our understanding of respiratory physiology.