Mechanical Engineering Faculty Publications and Presentations
Document Type
Article
Publication Date
5-23-2025
Abstract
In the context of turbulent dispersal of aerosol pollutants from a source within a ventilated indoor space, the present work addresses the importance of going beyond accurate prediction of the mean ensemble-averaged exposure, by evaluating the expected level of variability in individual realizations. This uncertainty quantification requires a statistical description of the inherent stochastic turbulent dispersal process and the inhomogeneous nature of the indoor flow. We leverage large datasets from turbulence-resolving EulerLagrange simulations of aerosol dispersal in varying indoor geometries. The datasets provide time-resolved concentrations of pollutants emitted by a source located anywhere in a room and reaching a sink (susceptible individual) that may be located anywhere else in the same room. The statistical information is used to accurately predict the mean pollutant concentration as a function of source-sink separation distance and associated variability in two different experimental measurements to demonstrate the importance of estimating the uncertainty associated with the predicted average concentration. The average pollutant concentration results are compared with the predictions of three other commonly used models (well-mixed model, near-field/far-field model, and eddy diffusivity model)
Recommended Citation
Krishnaprasad, K. A., N. Zgheib, and S. Balachandar. "Statistical approach to turbulent dispersal of aerosols for accurate prediction of concentration and associated uncertainties." Physical Review Fluids 10, no. 5 (2025): 054302. https://doi.org/10.1103/PhysRevFluids.10.054302
Publication Title
Physical Review Fluids
DOI
10.1103/PhysRevFluids.10.054302
Comments
© 2025 American Physical Society. Original published version available at
https://doi.org/10.1103/PhysRevFluids.10.054302