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Direct numerical simulations of inhalation in a 23-generation lung model

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arxiv 2506.14729 v1 pith:TA2XUXRU submitted 2025-06-17 physics.flu-dyn

Marco Atzori , Emanuele Gallorini , Ciro Cottini , Andrea Benassi , Maurizio Quadrio This is my paper
classification physics.flu-dyn
keywords flowlungbifurcationsfluctuationsgenerationsmodelairwayassumptions
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The air flows in the proximal and distal portions of the human lungs are interconnected: the lower Reynolds number in the deeper generations causes a progressive flow regularization, while mass conservation requires flow rate oscillations to propagate through the airway bifurcations. To explain how these two competing effects shape the flow state in the deeper generations, we have performed the first high-fidelity numerical simulations of the air flow in a lung model including 23 successive bifurcations of a single planar airway. Turbulence modelling or assumptions on flow regimes are not required. The chosen flow rate is stationary (steady on average), and representative of the peak inspiratory flow reached by adult patients breathing through therapeutical inhalers. As expected, advection becomes progressively less important after each bifurcation, until a time-dependent Stokes regime governed solely by viscous diffusion is established in the smallest generations. However, fluctuations in this regime are relatively fast and large with respect to the mean flow, which is in contrast with the commonly agreed picture that only the breathing frequency is relevant at the scale of the alveoli. We demonstrate that the characteristic frequency and amplitude of these fluctuations are linked to the flow in the upper part of the bronchial tree, as they originate from the time-dependent flow splitting in the upper bifurcations. Even though these fluctuations are observed here in an idealized, rigid lung model, our findings suggest that the assumptions usually adopted in many of the current lung models might need to be revised.

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Works this paper leans on

47 extracted references · 36 canonical work pages

  1. [1]

    E. R. Weibel, D. M. Gomez, Architecture of the Human Lung: Use of quantitative methods establishes fundamental relations between size and number of lung structures, Science 137 (3530) (1962) 577–585. doi: 10.1126/science.137.3530.577

    work page doi:10.1126/science.137.3530.577 1962

  2. [2]

    T. J. Pedley, Pulmonary Fluid Dynamics, Annual Review of Fluid Me- chanics 9 (V olume 9, 1977) (1977) 229–274. doi:10.1146/annurev. fl.09.010177.001305

    arXiv 1977

  3. [3]

    W. H. Finlay, The Mechanics of Inhaled Pharmaceutical Aerosols, 2nd Edition, 2019

    work page 2019

  4. [4]

    Neelakantan, Y

    S. Neelakantan, Y . Xin, D. P. Gaver, M. Cereda, R. Rizi, B. J. Smith, R. Avazmohammadi, Computational lung modelling in respira- tory medicine, Journal of The Royal Society Interface 19 (191) (2022) 20220062. doi:10.1098/rsif.2022.0062

    arXiv 2022

  5. [5]

    E. Kole, K. Jadhav, N. Shirsath, P. Dudhe, R. K. Verma, A. Chatter- jee, J. Naik, Nanotherapeutics for pulmonary drug delivery: An emerg- ing approach to overcome respiratory diseases, Journal of Drug Delivery Science and Technology 81 (2023) 104261. doi:10.1016/j.jddst. 2023.104261

    work page arXiv 2023

  6. [6]

    Koullapis, B

    P. Koullapis, B. Ollson, S. C. Kassinos, J. Sznitman, Multiscale in silico lung modeling strategies for aerosol inhalation therapy and drug delivery, Current Opinion in Biomedical Engineering 11 (2019) 130–136. doi: 10.1016/j.cobme.2019.11.003

    work page doi:10.1016/j.cobme.2019.11.003 2019

  7. [7]

    H. Yeh, G. Schum, Models of human lung airways and their application to inhaled particle deposition, Bulletin of Mathematical Biology 42 (3) (1980) 461–480. doi:10.1016/S0092-8240(80)80060-7

    work page doi:10.1016/s0092-8240(80)80060-7 1980

  8. [8]

    Koblinger, W

    L. Koblinger, W. Hofmann, Monte Carlo modeling of aerosol deposition in human lungs. Part I: Simulation of particle transport in a stochastic lung structure, Journal of Aerosol Science 21 (5) (1990) 661–674. doi: 10.1016/0021-8502(90)90121-D

    work page doi:10.1016/0021-8502(90)90121-d 1990

Show all 47 references
  1. [9]

    M. J. Grill, J. Biehler, K.-R. Wichmann, D. Rudlstorfer, M. Rixner, M. Brei, J. Richter, J. B ¨ugel, N. Pischke, W. A. Wall, K. W. M ¨uller, In silico high-resolution whole lung model to predict the locally de- livered dose of inhaled drugs (Jul. 2023). arXiv:2307.04757, doi: ...

    2023 doi arXiv

  2. [10]

    Zhang, F

    X. Zhang, F. Li, P. K. Rajaraman, J. Choi, A. P. Comellas, E. A. Ho ff- man, B. M. Smith, C.-L. Lin, A computed tomography imaging-based subject-specific whole-lung deposition model, European Journal of Phar- maceutical Sciences 177 (2022) 106272. doi:10.1016/j.ejps.2022. 106272

    2022 doi

  3. [11]

    R. L. Walenga, C. Butler, B. A. Craven, P. W. Longest, R. Mohamed, B. Newman, B. Olsson, G. Hochhaus, B. V . Li, M. C. Luke, L. Zhao, A. Przekwas, R. Lionberger, Mechanistic modeling of generic orally in- haled drug products: A workshop summary report, CPT Pharmacom & Syst Pha...

    2023 doi

  4. [12]

    M ¨oller, M

    G. M ¨oller, M. Bieber, S. G ¨urzing, A. L. Thiebes, S. Klein, C. G. Cor- nelissen, M. A. Reddemann, Transparent 23-generation airway model for experimental investigation of aerosol flow and deposition within the hu- man respiratory tract, Journal of Aerosol Science 156 (2021)...

    2021

  5. [13]

    Christou, T

    S. Christou, T. Chatziathanasiou, S. Angeli, P. Koullapis, F. Stylianou, J. Sznitman, H. H. Guo, S. C. Kassinos, Anatomical variability in the upper tracheobronchial tree: Sex-based di fferences and implications for personalized inhalation therapies, Journal of Applied Physiol...

    2021

  6. [14]

    S. C. Kassinos, J. Sznitman, Multiscale Modeling of Respiratory Trans- port Phenomena and Intersubject Variability (Aug. 2024). doi:10. 1146/annurev-fluid-031424-103721

    2024

  7. [15]

    Haefeli-Bleuer, E

    B. Haefeli-Bleuer, E. R. Weibel, Morphometry of the human pulmonary acinus, The Anatomical Record 220 (4) (1988) 401–414.doi:10.1002/ ar.1092200410

    1988

  8. [16]

    Heistracher, W

    T. Heistracher, W. Hofmann, Physiologically realistic models of bronchial airway bifurcations, Journal of Aerosol Science 26 (3) (1995) 497–509. doi:10.1016/0021-8502(94)00113-D

    1995 doi

  9. [17]

    Schmidt, S

    A. Schmidt, S. Zidowitz, A. Kriete, T. Denhard, S. Krass, H.-O. Peit- gen, A digital reference model of the human bronchial tree, Comput- erized Medical Imaging and Graphics 28 (4) (2004) 203–211. doi: 10.1016/j.compmedimag.2004.01.001

    2004 doi

  10. [18]

    Kleinstreuer, Z

    C. Kleinstreuer, Z. Zhang, Airflow and Particle Transport in the Human Respiratory System, Annu. Rev. Fluid Mech. 42 (1) (2010) 301–334. doi:10.1146/annurev-fluid-121108-145453

    2010 doi

  11. [19]

    D. Jan, A. Shapiro, R. Kamm, Some features of oscillatory flow in a model bifurcation | Journal of Applied Physiology | American Physio- logical Society, https://doi.org/10.1152/jappl.1989.67.1.147 (1989)

    1989 doi

  12. [20]

    Y . Suh, J. Y . Park, E ffect of o ff-plane bifurcation angles of primary bronchi on expiratory flows in the human trachea, Computers in Biology and Medicine 95 (2018) 63–74. doi:10.1016/j.compbiomed.2018. 01.014

    2018 doi

  13. [21]

    A. J. Banko, F. Coletti, C. J. Elkins, J. K. Eaton, Oscillatory flow in the human airways from the mouth through several bronchial generations, International Journal of Heat and Fluid Flow 61 (2016) 45–57. doi: 10.1016/j.ijheatfluidflow.2016.04.006

    2016 doi

  14. [22]

    J. A. Bernate, T. S. Geisler, S. Padhy, E. S. G. Shaqfeh, G. Iaccarino, Study of the flow unsteadiness in the human airway using large eddy simulation, Phys. Rev. Fluids 2 (8) (2017) 083101. doi:10.1103/ PhysRevFluids.2.083101

    2017

  15. [23]

    H. Jing, H. Ge, L. Wang, Q. Zhou, L. Chen, S. Choi, X. Cui, Large eddy simulation study of the airflow characteristics in a human whole- lung airway model, Physics of Fluids 35 (7) (2023) 071903. doi: 10.1063/5.0156310

    2023 doi

  16. [24]

    Koullapis, S

    P. Koullapis, S. Kassinos, J. Muela, C. Perez-Segarra, J. Rigola, O. Lehmkuhl, Y . Cui, M. Sommerfeld, J. Elcner, M. Jicha, I. Saveljic, N. Filipovic, F. Lizal, L. Nicolaou, Regional aerosol deposition in the hu- man airways: The SimInhale benchmark case and a critical assessm...

    2018 doi

  17. [25]

    Janke, P

    T. Janke, P. Koullapis, S. Kassinos, K. Bauer, PIV measurements of the SimInhale benchmark case, European Journal of Pharmaceutical Sciences 133 (2019) 183–189. doi:10.1016/j.ejps.2019.03.025

    2019 doi

  18. [26]

    Spasov, R

    G. Spasov, R. Rossi, A. Vanossi, C. Cottini, A. Benassi, A critical analysis of the CFD-DEM simulation of pharmaceutical aerosols deposition in up- per intra-thoracic airways: Considerations on air flow, Computers in Biol- ogy and Medicine 170 (2024) 107948. doi:10.1016/j.comp...

    2024

  19. [27]

    Sznitman, Respiratory microflows in the pulmonary acinus, Journal of Biomechanics 46 (2) (2013) 284–298

    J. Sznitman, Respiratory microflows in the pulmonary acinus, Journal of Biomechanics 46 (2) (2013) 284–298. doi:10.1016/j.jbiomech. 2012.10.028

    2013 doi

  20. [28]

    Haber, J

    S. Haber, J. P. Butler, H. Brenner, I. Emanuel, A. Tsuda, Shear flow over 15 a self-similar expanding pulmonary alveolus during rhythmical breath- ing, Journal of Fluid Mechanics 405 (2000) 243–268. doi:10.1017/ S0022112099007375

    2000

  21. [29]

    E. R. Weibel, B. Sapoval, M. Filoche, Design of peripheral airways for efficient gas exchange, Respiratory Physiology & Neurobiology 148 (1) (2005) 3–21. doi:10.1016/j.resp.2005.03.005

    2005 doi

  22. [30]

    F. Shen, C. Yan, M. Li, Z. Liu, Experimental study of transient behaviors of start-up flow in long microcavities, Chemical Engineering Science 219 (2020) 115591. doi:10.1016/j.ces.2020.115591

    2020

  23. [31]

    J. Goo, C. S. Kim, Theoretical analysis of particle deposition in hu- man lungs considering stochastic variations of airway morphology, Journal of Aerosol Science 34 (5) (2003) 585–602. doi:10.1016/ S0021-8502(03)00024-7

    2003

  24. [32]

    A. H. Sonnenberg, J. Herrmann, M. W. Grinsta ff, B. Suki, A Markov chain model of particle deposition in the lung, Sci Rep 10 (1) (2020) 13573. doi:10.1038/s41598-020-70171-2

    2020 doi

  25. [33]

    A. J. Swan, A. R. Clark, M. H. Tawhai, A computational model of the topographic distribution of ventilation in healthy human lungs, Journal of Theoretical Biology 300 (2012) 222–231. doi:10.1016/j.jtbi. 2012.01.042

    2012 doi

  26. [34]

    G. Tian, P. W. Longest, G. Su, M. Hindle, Characterization of Respiratory Drug Delivery with Enhanced Condensational Growth using an Individual Path Model of the Entire Tracheobronchial Airways, Ann Biomed Eng 39 (3) (2011) 1136–1153. doi:10.1007/s10439-010-0223-z

    2011 doi

  27. [35]

    P. W. Longest, G. Tian, N. Khajeh-Hosseini-Dalasm, M. Hindle, Validat- ing Whole-Airway CFD Predictions of DPI Aerosol Deposition at Multi- ple Flow Rates, Journal of Aerosol Medicine and Pulmonary Drug Deliv- ery 29 (6) (2016) 461–481. doi:10.1089/jamp.2015.1281

    2016

  28. [36]

    S. B. Pope, Turbulent Flows, Cambridge University Press, Cambridge, 2000

    2000

  29. [37]

    Koullapis, P

    P. Koullapis, P. Hofemeier, J. Sznitman, S. Kassinos, An efficient compu- tational fluid-particle dynamics method to predict deposition in a simpli- fied approximation of the deep lung, European Journal of Pharmaceutical Sciences 113 (2018) 132–144. doi:10.1016/j.ejps.2017.09.016

    2018 doi

  30. [38]

    M. S. Islam, S. C. Saha, E. Sauret, T. Gemci, Y . Gu, Pulmonary aerosol transport and deposition analysis in upper 17 generations of the human respiratory tract, Journal of Aerosol Science 108 (2017) 29–43. doi: 10.1016/j.jaerosci.2017.03.004

    2017 doi

  31. [39]

    A. V . Kolanjiyil, C. Kleinstreuer, Computationally e fficient analysis of particle transport and deposition in a human whole-lung-airway model. Part I: Theory and model validation, Computers in Biology and Medicine 79 (2016) 193–204. doi:10.1016/j.compbiomed.2016.10.020

    2016 doi

  32. [40]

    USP /NF General Chapter <601> Physical Tests and determinations- Inhalation and Nasal drug products: Aerosols, Sprays, and Powders- Performance Quality Tests., National Formulary, USP38-NF-33 (2015)

    2015

  33. [41]

    Luchini, Introducing CPL (Nov

    P. Luchini, Introducing CPL (Nov. 2021). arXiv:2021.12143v2

    2021

  34. [42]

    Luchini, D

    P. Luchini, D. Gatti, A. Chiarini, F. Gattere, M. Atzori, M. Quadrio, A simple and e fficient immersed-boundary method for the incompressible Navier–Stokes equations, J. Comp. Phys. (Submitted) (2025)

    2025

  35. [43]

    Russo, P

    S. Russo, P. Luchini, A fast algorithm for the estimation of statistical error in DNS (or experimental) time averages, J. Comput. Phys. 347 (2017) 328–340

    2017

  36. [44]

    Kundu, M

    D. Kundu, M. V . Panchagnula, Asymmetric lung increases particle fil- tration by deposition, Sci Rep 13 (1) (2023) 9040. doi:10.1038/ s41598-023-36176-3

    2023

  37. [45]

    Pirozzoli, P

    S. Pirozzoli, P. Orlandi, Natural grid stretching for DNS of wall-bounded flows, J. Comp. Phys. 439 (2021) 110408. doi:10.1016/j.jcp.2021. 110408

    2021 doi

  38. [46]

    Dean, Reynolds number dependence of skin friction and other bulk flow variables in two-dimensional rectangular duct flow, Trans

    R. Dean, Reynolds number dependence of skin friction and other bulk flow variables in two-dimensional rectangular duct flow, Trans. ASME I: J. Fluids Eng. 100 (1978) 215–223

    1978

  39. [47]

    Ducros, V

    F. Ducros, V . Ferrand, F. Nicoud, C. Weber, D. Darracq, C. Gacherieu, T. Poinsot, Large-Eddy Simulation of the Shock /Turbulence Interaction, J. Comp. Phys. 152 (2) (1999) 517–549. doi:10.1006/jcph.1999. 6238. 16

    1999 doi

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