BuildWind

Advanced Simulator for Airborne Pathogen Propagation

ASAPP simulation software by BuildWind is based on the finite volume numerical code OpenFOAM and consists in a coupled Eulerian-Lagrangian method, where unsteady particle tracking is used to predict the position of respiratory droplets. 

The computational grid for each room consists of approximately 10 million hexahedral cells. Forniture, people and part of the HVAC system are included in the computational domain. 

The time-evolving turbulent flow field is solved employing a URANS approach with a k-ω SST model. The solution of the governing equations is obtained with a pressure-based solver and a PIMPLE algorithm. Second order schemes are used for the transported variables, and the Euler scheme is employed for time, with a constant time step of 5e-03s. Buoyancy effects, e.g. around the bodies of the occupants, are also taken into account.

The time-dependent local pathogen concentration calculated by simulations is then used by the software to perform an analysis of the risk of infection for susceptible hosts based on their position, protective equipment and time of exposure. 

  1. Morawska, L., G. R. Johnson, Z. D. Ristovski, M. Hargreaves, K. Mengersen, S. Corbett, C. Y. H. Chao, Y. Li, and D. Katoshevski. 2009. “Size Distribution and Sites of Origin of Droplets Expelled from the Human Respiratory Tract during Expiratory Activities.” Journal of Aerosol Science 40 (3): 256–69.
  2. Buonanno, G., Stabile, L. and Morawska, L., 2020. Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infection risk assessment. Environment international, 141, p.105794.
  3. Buonanno, G., Morawska, L. and Stabile, L., 2020. Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: prospective and retrospective applications. Environment international, 145, p.106112.
  4. Bourouiba, L., 2020. Turbulent gas clouds and respiratory pathogen emissions: potential implications for reducing transmission of COVID-19. Jama, 323(18), pp.1837-1838.
  5. Bourouiba, L., 2021. The fluid dynamics of disease transmission. Annual Review of Fluid Mechanics, 53, pp.473-508.
  6. Scharfman, B.E., Techet, A.H., Bush, J.W.M. and Bourouiba, L., 2016. Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets. Experiments in Fluids, 57(2), pp.1-9.
  7. Chao, C.Y.H., Wan, M.P., Morawska, L., Johnson, G.R., Ristovski, Z.D., Hargreaves, M., Mengersen, K., Corbett, S., Li, Y., Xie, X. and Katoshevski, D., 2009. Characterization of expiration air jets and droplet size distributions immediately at the mouth opening. Journal of aerosol science, 40(2), pp.122-133.

ASAPP simulation software has been developed and validated with the support of Innoviris, the innovation agency of the Brussels Capital Region. BuildWind gratefully acknowledges Innoviris for financial support under grant number 2020-RDIDS-61.

Propagation of droplets exhaled during normal breathing in intensive care rooms

Simulation of droplet propagation inside an intensive care room equipped with standard ventilation system working at low flow rate. 3 hours of simulated time.

Simulation of droplet propagation inside an intensive care room with different setup and ventilation system.

Propagation of droplets exhaled during coughing and breathing in intensive care rooms

Simulation of droplet propagation inside an intensive care room equipped with standard ventilation system working at low flow rate. 1 hours of simulated time. Particles are generated by normal breathing and 3 coughing events every 3 minutes.

Home