In vitro-in silico correlation of three-dimensional turbulent flows in an idealized mouth-throat model

PLoS Comput Biol. 2023 Mar 23;19(3):e1010537. doi: 10.1371/journal.pcbi.1010537. eCollection 2023 Mar.

Abstract

There exists an ongoing need to improve the validity and accuracy of computational fluid dynamics (CFD) simulations of turbulent airflows in the extra-thoracic and upper airways. Yet, a knowledge gap remains in providing experimentally-resolved 3D flow benchmarks with sufficient data density and completeness for useful comparison with widely-employed numerical schemes. Motivated by such shortcomings, the present work details to the best of our knowledge the first attempt to deliver in vitro-in silico correlations of 3D respiratory airflows in a generalized mouth-throat model and thereby assess the performance of Large Eddy Simulations (LES) and Reynolds-Averaged Numerical Simulations (RANS). Numerical predictions are compared against 3D volumetric flow measurements using Tomographic Particle Image Velocimetry (TPIV) at three steady inhalation flowrates varying from shallow to deep inhalation conditions. We find that a RANS k-ω SST model adequately predicts velocity flow patterns for Reynolds numbers spanning 1'500 to 7'000, supporting results in close proximity to a more computationally-expensive LES model. Yet, RANS significantly underestimates turbulent kinetic energy (TKE), thus underlining the advantages of LES as a higher-order turbulence modeling scheme. In an effort to bridge future endevours across respiratory research disciplines, we provide end users with the present in vitro-in silico correlation data for improved predictive CFD models towards inhalation therapy and therapeutic or toxic dosimetry endpoints.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Mouth*
  • Pharynx*
  • Rheology

Associated data

  • figshare/10.6084/m9.figshare.20239125

Grants and funding

This work was supported by the Israel Science Foundation (ISF) (grant no. 1840/21 to JS), the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 677772 to JS) as well as the PBC Fellowship Program by the Israeli council for supporting SB with partial funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.