Drag constants for common indoor bioaerosols

Abstract

In practice, the drag coefficient of a particle is usually calculated using empirical relationships obtained by generalizing experimental data. This study demonstrates that using the default Stokes’ law settings in FLUENT to computationally predict the drag coefficients for bioaerosol deposition is not really appropriate: the average fractional bias is 7% and the average normalized mean square error is 15%. Comparatively, the errors for bacteria (−12% to 24%) are larger than those for fungi (−8% to 26%). These errors, however, can be minimized by selecting a suitable drag constant, which can be determined based on the bioaerosol diameter. The average drag constants for bacteria were shown by the results to vary from 0.25 to 3.1, which are much smaller than the default value of 24, whereas the values for fungi were generally larger and in a wider range. This study also investigated the correlation between the drag coefficient and Reynolds number for common indoor bioaerosols with diameters between 0.69 and 8.6 µm. The outcome of this study would therefore provide a good reference point for future estimation of the deposition distribution patterns of various common indoor bioaerosols.

An air distribution optimization of hospital wards for minimizing cross-infection

“…Three main assumptions are adopted in this paper: (1) Breathing effect of humans are ignored; (2) Movement of people inside the ward is ignored; (3) The sneeze or cough process is simplified according to Wong’s work ( Wong et al., 2015 ); (4) Dry air is adopted (see Figure A1 and Table A1 ); (5) droplet evaporation is ignored. In this paper, an ACH of 2 h −1 , where the total air mass flow rate is 1.24 kg/s, is adopted.…”

“…For Each AD proposal, six cases are simulated: (1) Steady state of a one-shot sneeze of Man 1; (2) Transient state of a constant sneeze of Man 1; (3) Steady state of a one-shot sneeze of Man 2; (4) Transient state of a constant sneeze of Man 2; (5) Steady state of a one-shot sneeze of Man 1; (6) Transient state of a constant sneeze of Man 1. The boundary conditions of each steady and transient state are also provided in Table 4 where the physical parameters of the virus particle are referred from Wong et al. (2015) and Gupta et al.…”

A numerical study of ventilation strategies for infection risk mitigation in general inpatient wards

“…The validity of Eqs. (9) and (10) was established for a range of particles with equivalent bioaerosol diameters (d b ) from 0.69 μm to 6.9 μm and further examined for particles with d b as low as 0.054 μm (Wong et al 2015).…”

Numerical simulation of bioaerosol particle exposure assessment in office environment from MVAC systems

“…3 ). 26 The insufficient VR office (i.e. 1 ACH) of C. cladosporioides and S. aureus were also demonstrated in the bioaerosol fractional count FC in Figure 8.…”