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A Framework for Modelling Dynamic Covid-19 Aerosol Dispersion and Infection Risk within the Built Environment and Transportation

FSEG responded to the COVID19 pandemic by adapting SMARTFIRE to simulate respired aerosol dispersion; and the EXODUS evacuation model to simulate physical distancing during pedestrian circulation.

The Problem

A Covid-19 Modelling Framework

The key features of the novel modelling framework are based on integrating and merging a set of new modelling capabilities with a number of existing modelling capabilities that were modified and enhanced to address the new Covid-19 aerosol dispersion application area. These included:

New Modelling Capabilities:

  1. Respired droplet release model providing appropriate characterisation of droplet size distribution and suitable expired breath airflow for an infected person (e.g., when breathing, talking, coughing, etc.);
  2. Ability to evaluate absolute risk of infection based on exposure to aerosol droplets at a target volume of interest using a Wells-Riley approach;
  3. Support for moving sources i.e., walking sources (infected or “index” patients);
  4. Support for stationary or moving targets (i.e., susceptible people);
  5. The impact of wake flows generated by occupants walking through the droplet dispersal tracking field, using the immersed boundary method;
  6. RNG turbulence model to improve flow modelling accuracy;
  7. Support for air conditioning modelling capabilities to allow the re-circulation and re-distribution of droplets with the possibility of droplet culling due to filtration effects (e.g. ordinary or HEPA based filters) whilst also allowing the arbitrary configuration of the proportion of fresh and recycled air.

Modified Existing Capabilities:

  1. Aerosol droplet tracking using Lagrangian particle tracking;
  2. Droplet evaporation, that is sensitive to humidity and temperature, with droplet size reduction to “fate” nuclei/fomites with history of original number of likely virions released in each droplet to allow infection risk to be deduced from exposure to multiple droplets at arbitrary times since exhaled;
  3. Droplet surface deposition, accumulation and persistence;
  4. New flow pattern definition over the cross section of an inlet. 

Adopted Approach using Localised Wells-Riley with CFD Modelling

FSEG implemented a localised form of the Wells-Riley model in SMARTFIRE[1] using a “quanta” based release allowing calibration of the many unknowns of Infection Risk against known infection events.

Basic Wells-Riley Equation for Probability of Infection, where D is dose of infectious agent.

Chinese G-Train Infection Risk Modelling

Chinese (long dist.) G-Trains have several ventilation strategies and large airflow rates.

Seat Layout in Standard Class G Train Carriage Example Ventilation Strategy

Statistical analysis[2] considered reported infections from many passenger-journeys during the early stages of the pandemic. This allowed evaluation of Infection Risk due to proximity to an index patient in various types of carriage.

CFD Transport Equation for a Scalar Concentration.

Inflight Transmission of COVID-19 Based on Aerosol Dispersion Data

FSEG have published an article [3] in Journal of Travel Medicine, exploring the relationship between exposure time and Infection Risk, based on Boeing aircraft experimental aerosol dispersion data.

Aircraft Aerosol Dispersion Experimental Trial Aircraft Infection Probability with Usage of Face Masks

Summary of FSEG’s conclusions from this Research:

Modelling the Dynamics and Impact of People Movement

Although static/steady-state models can be helpful, the real world is often more complex with transient perturbations. FSEG is developing dynamic modelling capabilities to allow these complexities to be included in Infection Risk analysis.

People following through first walker’s respired aerosol cloud (with wake flows).


Airborne droplets from infected person (mobile source) in air-conditioned supermarket.

FSEG have also modelled the dynamics of an infected person walking through, and releasing aerosol droplets in, a ventilated supermarket. This highlights the impact of low ACH ventilation rates that allow the respired aerosol droplet cloud to persist for a considerable time and, potentially, infect others. Droplets can evaporate, deposit on surfaces or deactivate (over time).

Key Observations

Challenges During the Project

Other Developments

Most capabilities developed/validated in isolation. FSEG are testing full integration and investigating significant multi-featured and complex scenarios.
Link with agent-based simulation software EXODUS, enabling movement of agents attempting to maintain physical distancing, to move sources and targets for dynamic infection risk analysis in realistic circulation scenarios.


EXODUS modelling movement (faster than actual) of agents attempting to maintain physical distancing.

FSEG are continuing to research and develop additional capabilities to support the Covid-19 aerosol dispersion modelling capabilities. This includes the development of User Interface capabilities to allow easier generation and configuration of scenarios and an unstructured meshing approach to support some of the complex geometries that can be found in modern buildings and in the fine details of ventilation handling.

Related Work and Links

Presentation (FSEG COVID19 Mitigation Analysis using CFD and Agent Based Models) describing FSEG CFD model developments relating to dispersion of respiratory aerosols and COVID19 and applications to transport systems at the RAMP conference, ‘New Models of Spatial and Social Behaviour in a Pandemic’ held at Cambridge University, 26-27 May 2021,

Presentation (FSEG COVID19 Mitigation Analysis – Harnessing CFD Fire Simulation And Agent Based Models), describing FSEG agent based and CFD model developments associated with COVID19, presented at the Isaac Newton Institute For Mathematical Sciences, Cambridge University, Infectious Dynamics Of Pandemics (IDP): Mathematical And Statistical Challenges In Understanding The Dynamics Of Infectious Disease, Seminar, Afternoon Session, 14/07/20. Presentation Starts At 01:31:41 Into Video.

Other outreach and promotion activities have used the project work to target diverse audiences on platforms such as LinkedIn, e.g.: 

Referenced Work

[1] Z Wang, F Jia, E R Galea, and J H Choi, (2017), “A forensic analysis of a fatal fire in an indoor shooting range using coupled fire and evacuation modelling tools”, Fire Safety Journal, http://doi.org/10.1016/j.firesaf.2017.03.029
[2] Hu et al., "The risk of COVID-19 transmission in train passengers: an epidemiological and modelling study," Clinical Infectious Diseases, no. https://doi.org/10.1093/cid/ciaa1057, 2020
[3] Z Wang, E R Galea, A Grandison, J Ewer, F Jia, “Inflight Transmission of COVID-19 Based on Experimental Aerosol Dispersion Data”, Journal of Travel Medicine, 2021; https://doi.org/10.1093/jtm/taab023


University of Greenwich Innovation Fund – Proof of Concept Development Award