The present study investigates aerosol transport and surface deposition in a realistic classroom environment using computational fluid-particle dynamics simulations. Effects of particle size, aerosol source location, glass barriers, and windows are explored. While aerosol transport in air exhibits some stochasticity, it is found that a significant fraction (24%–50%) of particles smaller than 15 µ m exit the system within 15 min through the air conditioning system. Particles larger than 20 µ m almost entirely deposit on the ground, desks, and nearby surfaces in the room. Source location strongly influences the trajectory and deposition distribution of the exhaled aerosol particles and affects the effectiveness of mitigation measures such as glass barriers. Glass barriers are found to reduce the aerosol transmission of 1 µ m particles from the source individual to others separated by at least 2.4 m by ∼92%. By opening windows, the particle exit fraction can be increased by ∼38% compared to the case with closed windows and reduces aerosol deposition on people in the room. On average, ∼69% of 1 µ m particles exit the system when the windows are open.

Identifying economically viable intervention measures to reduce COVID-19 transmission on aircraft is of critical importance especially as new SARS-CoV2 variants emerge. Computational fluid-particle dynamic simulations are employed to investigate aerosol transmission and intervention measures on a Boeing 737 cabin zone. The present study compares aerosol transmission in three models: (a) a model at full passenger capacity (60 passengers), (b) a model at reduced capacity (40 passengers), and (c) a model at full capacity with sneeze guards/shields between passengers. Lagrangian simulations are used to model aerosol transport using particle sizes in the 1–50 μ m range, which spans aerosols emitted during breathing, speech, and coughing. Sneeze shields placed between passengers redirect the local air flow and transfer part of the lateral momentum of the air to longitudinal momentum. This mechanism is exploited to direct more particles to the back of the seats in front of the index patient (aerosol source) and reduce lateral transfer of aerosol particles to other passengers. It is demonstrated that using sneeze shields on full capacity flights can reduce aerosol transmission to levels below that of reduced capacity flights without sneeze shields.

Simulation results conducted for incompressible planar wall-bounded turbulent flows with the Reynolds-Averaged Navier-Stokes (RANS) equations with no modeling involved are presented. Instead, all terms but the molecular diffusion are represented by the data from direct numerical simulation (DNS). In simulations, the transport equations for velocity moments through the second order (and the fourth order where the data are available) are solved in a zero-pressure gradient boundary layer over a flat plate and in a fully-developed channel flow in a wide range of Reynolds numbers using DNS data from Sillero et al. (2013), Lee & Moser (2015), and Jeyapaul et al. (2015). The results obtained demonstrate that DNS data are the significant and dominant source of uncertainty in such simulations (hereafter, RANS-DNS simulations). Effects of the Reynolds number, flow geometry, and the velocity moment order as well as an uncertainty quantification technique used to collect the DNS data on the results of RANS-DNS simulations are analyzed. New criteria for uncertainty quantification in statistical data collected from DNS are proposed to guarantee the data accuracy sufficient for their use in RANS equations and for the turbulence model validation.

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Rapid distortion calculations of initially anisotropic turbulence are performed to better understand the physics of the pressure-strain correlation in strain-dominated mean flows. Based on the results of simulations we infer important physical characteristics of the “rapid” pressure-strain correlation Φij(r) in such flows: (i) it vanishes when there is no production of anisotropy, (ii) in the proximity of two-componential state it tends to decrease Reynolds stress anisotropy, and (iii) its magnitude is generally smaller than that of production. The observed characteristics are proposed as criteria that pressure-strain correlation models may be required to satisfy. All of the current popular models violate the above criteria for a sizeable subset of anisotropic initial conditions. Reynolds stress transport model calculations show that unphysical and unrealizable model behavior can be directly attributed to these violations.