Zhang, L., Siddiqui, N. A., Tay, S., Ge, Z., Li, H., Ang, E. Y. M., & Wang, P. C. (2025). Quantifying time-evolving droplet velocities and size: Insights from experimental image analysis. Building and Environment, 273, 112739. https://doi.org/10.1016/j.buildenv.2025.112739
Abstract:
Respiratory droplets, ranging from 0.1 μm to 1,000 μm in size, are emitted during activities, such as coughing and sneezing, and can travel substantial distances through air currents. Current experimental studies often focus on time-averaged or spatially averaged results, and velocity profiles are typically measured independently from droplet size. Through Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) analyses, this paper aims to address the identified gaps. We quantified temporal and spatial velocity profiles, droplet sizes, and droplet number distributions at various locations downstream relative to the nozzle exit. The results can serve as time-varying boundary conditions and validation datasets for numerical models involving spray dynamics.
Using a commercial spray, the spray dynamics, involving water droplets with a diameter range of 0 to 1200μm and velocity from 0 to about 10m/s, are quantified. PIV and PTV results showed a transition in droplet dispersion behavior from an initial conical-shaped distribution at the nozzle exit to downward motion influenced by gravity. Larger particles settled earlier due to their mass and susceptibility to gravity. Further away from the nozzle, horizontal velocity of the droplets was observed to decrease, while the vertical velocity value increased.
CFD simulations, initialized with time- and space-varying boundary conditions from this work, demonstrated good agreement with experimental velocity distributions and droplet trajectories. The robust PIV and PTV datasets on expelled droplet behavior can enhance the accuracy of predicting droplet behavior. These findings enable a detailed, transient analysis of droplet dynamics during respiratory activities.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the Ministry of Health, Singapore, and National Research Foundation - National Epidemic Preparedness and Response R&D Funding Initiative Programme And Response (PREPARE)
Grant Reference no. : MOH-001041