“…The corresponding maximum expiratory turbulent kinetic energies were 7.03 and 45.24 m 2 /s 2 . Because of greater turbulence, more mixing of streamlines was observed response to running than that of walking ( Figure 4 ) [ 6 , 31 ]. Figure 9 Turbulence kinetic energy for respiration response to (a) walking (b) running.…”
“…The corresponding maximum expiratory turbulent kinetic energies were 7.03 and 45.24 m 2 /s 2 . Because of greater turbulence, more mixing of streamlines was observed response to running than that of walking ( Figure 4 ) [ 6 , 31 ]. Figure 9 Turbulence kinetic energy for respiration response to (a) walking (b) running.…”
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.
“…The heat transfer within the upper airway has been simulated both during inhalation of hot air [16] and during respiration in air at room temperature [34]. Other studies focused on oral breathing in idealized [6,8,9] or realistic [43] models from mouth to trachea, showing that the glottis greatly influences the flow field.…”
There is a considerable interest in understanding transient human upper airway aerodynamics, especially in view of assessing the effects of various ventilation therapies. Experimental analyses in a patient-specific manner pose challenges as the upper airway consists of a narrow confined region with complex anatomy. Pressure measurements are feasible, but, for example, PIV experiments require special measures to accommodate for the light refraction by the model. Computational fluid dynamics can bridge the gap between limited experimental data and detailed flow features. This work aims to validate the use of combined lattice Boltzmann method and a large eddy scale model for simulating respiration, and to identify clinical features of the flow and show the clinical potential of the method. Airflow was computationally analyzed during a realistic, transient, breathing profile in an upper airway geometry ranging from nose to trachea, and the resulting pressure calculations were compared against in vitro experiments. Simulations were conducted on meshes containing about 1 billion cells to ensure accuracy and to capture intrinsic flow features. Airway pressures obtained from simulations and in vitro experiments are in good agreement both during inhalation and exhalation. High velocity pharyngeal and laryngeal jets and recirculation in the region of the olfactory cleft are observed.
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