On the Lagrangian dynamics of saliva particles during normal mouth breathing

Abstract

The flow and saliva particulate transport dynamics during normal human breathing through the mouth are simulated numerically using an Eulerian large-eddy simulation (LES) approach for the flow coupled with a Lagrangian approach for the transport of saliva particles. The coupled Eulerian–Lagrangian (EL) simulation results reveal new striking insights into the rich dynamics of the Lagrangian coherent structures (LCS) that arise from saliva particles during normal breathing. Specifically, they uncover a new time-periodic mechanism via which particles are introduced into the flow as individual breathing pulses and accumulate to form a slowly propagating vortex front that persists long distances away from the source. The simulated LCS reveal a wealth of recurrent material motion through which the biosols propagate forward while their cloud expands laterally with a slowly evolving vortex front. Also, the finite-time Lyapunov exponent (FTLE) field of human breathing was calculated using the flow map from the LES velocity field. The ridges of the calculated FTLE field revealed distinct hyperbolic LCS, which closely resemble trajectories of saliva particles obtained from the coupled EL simulation. Finally, simulation results for normal breathing with a non-medical face mask show that the mask can effectively disrupt the formation of coherent particle surfaces and, thus, effectively limit saliva particle propagation.

Lagrangian particle tracking velocimetry investigation of vortex shedding topology for oscillating heavy spherical pendulums underwater

“…Considering a length scale L f = D = 0.01271 m, the bulk velocity 0.7 m s −1 , and the tracer particles' diameter and density 50 μm and 1.016 g cm −3 , respectively, the expected Stokes numbers (S tk < 0.008) of the experiments with various sphere characteristics are significantly less than 0.1. Therefore, the tracer particles tend to follow the fluid flow streamlines closely, and the tracing accuracy errors are well below 1 % (Brennen 2005;Oaks et al 2022).…”

“…Therefore, the tracer particles tend to follow the fluid flow streamlines closely, and the tracing accuracy errors are well below 1 % (Brennen 2005; Oaks et al. 2022).…”

“…However, tomo-PIV has disadvantages as it is computationally expensive and relies on cross-correlation over spatial averages, which can smooth out velocity gradients (Schanz, Gesemann & Schröder 2016). As a result, approaches based on Lagrangian particle tracking, commonly referred to as particle tracking velocimetry (PTV), have become more popular (Raffel et al 2018). Nowadays, time-resolved 3-D PTV (tr-3-D-PTV) constitutes one of the most advanced approaches in 3-D flow measurements, and has proven its utility for identifying and visualising coherent flow structures and vortex dynamics (Schobesberger et al 2022).…”

On the efficacy of facial masks to suppress the spreading of pathogen-carrying saliva particles during human respiratory events: Insights gained via high-fidelity numerical modeling

“…Thence, several studies have observed that LCS manifest as flows throughout natural and engineered systems, including medical applications 51 – 59 . Oaks et al 60 innovated by applying LCS to describe the biological flow in normal human breathing, and Seyedzadeh et al 61 elaborated the initial study by identifying other intricate three-dimensional (3D) structures such as jet in crossflow (JICF) 62 and counter-rotating vortex pairs (CRVP). Exploration of LCSs has guided similarly innovative studies in medicinal settings 32 , 46 , 63 .…”

Numerical investigation of airborne transmission in low-ceiling rooms under displacement ventilation

“…Compared with experimental and theoretical studies, Computational Fluid Dynamics (CFD) studies can provide full physical details of flow fields and particle transport (i.e., field distributions of pressure, temperature, velocity, and concentrations of contaminants or particle trajectories). With the advancement in computational power, the CFD method has been extensively utilized to predict and design ventilation flows to prevent airborne transmission in buildings [39][40][41][42][43][44][45]. For example, Zhao & Chao [39] used the discrete trajectory model to study airborne transmission in a full-scale room and found that a displacement ventilated room has a larger number of escaped particles and a higher average particle concentration due to its lower deposition rate than the mixing room.…”