Numerical Model and System for Prediction and Reduction of Indoor COVID-19 Infection Risk

Airborne aerosol transmission is a significant route of SARS-CoV-2 and other viruses in indoor environments. The developed numerical model assesses the risk of a COVID-19 infection in a room based on the measurements of temperature, relative humidity, CO2 and particle concentration, as well as the number of people and occurrences of speech, coughing, and sneezing obtained through a dedicated low-cost sensor system [1]. As the model operates faster than real-time, it can dynamically feed this information back to the measurement system or building management system, and it can activate an air purifier with filtration and UV-C disinfection when the predicted infection risk is high. This solution enhances energy efficiency as (1) lower ventilation intensity is necessary in the cold season to reach the same safety level and (2) the purifier is activated only if the predicted infection risk is above a certain threshold.The model is integral and takes into account the average values of simulated variables. However, it considers the inhomogeneous vertical distribution of concentration of droplets and aerosol particles. The droplets expelled by a potentially infectious person at a certain height through breathing, speaking, coughing, and sneezing are characterized by the total amount of expelled liquid, droplet size distribution and virus particle concentration. The rate of droplet evaporation depends on the temperature and relative humidity. Droplets are redistributed within the room vertically through turbulent diffusion and gravitational force. If the final droplet diameter is less than 5 mm, these particles are considered airborne and can leave the room only by ventilation, filtration, or by sedimentation on surfaces through Brownian diffusion. As a person in the room inhales these droplets and aerosols, the risk of infection increases as the number of absorbed virions grows, with the probability of infection being 50% when 300 virions have been inhaled.The parameter studies using the model indicate that the coughing and sneezing events greatly increase the probability of infection in the room, therefore the identification of these events is crucial for the applied measurement system. A method for determining the unknown ventilation intensity by measuring the number of people and the CO2 concentration is proposed and tested

Airflow and aerosol transport modeling with applications to Covid-19 aerosol reduction indoors

Pēdējo pāris gadu laikā Covid-19 infekcijas slimība ir izraisījusi lielu kaitējumu cilvēkiem visā pasaulē, kas ir licis zinātniskajai kopienai apsvērt pieejas infekcijas mazināšanai, tostarp skaitliskās modelēšanas pieejas. Šī darba mērķis ir modelēt Covid-19 aerosola pārnesi un tā samazināšanu iekštelpās. Skaitliskās hidrodinamikas risināšanai tiek izmantota Reinoldsa vidējotā Navjē Stoksa modelēšanas pieeja kopā ar turbulentās difūzijas modeli aerosola pārnesei. Darbs sākas ar konkrētas telpas gaisa plūsmas modelēšanu un skaitlisko aprēķina parametru izpēti. Nākamajā daļā tiek izveidots gaisa attīrīšanas iekārtas matemātiskais modelis, kas tiek skaitliski ieviests un pārbaudīts izmantojot skaitliskās hidrodinamikas rīkkopu OpenFOAM. Aerosola koncentrācijas aprēķina rezultāti liek secināt, ka stacionārajā RANS modelī iekštelpu gaisa plūsmu gadījumā turbulentā koncentrācijas izkliede netiek korekti aprakstīta, tāpēc nākotnē modeli nepieciešams pilnveidot.Over the past few years, the Covid-19 infection disease has caused great harm to humans worldwide, which has led the scientific community to consider various approaches to mitigate the infection, including numerical modelling approaches. The aim of this work is to model the aerosol transmission of Covid-19 and its reduction in an indoor environment. The Reynolds averaged Navier Stokes approach is used in the computational fluid dynamics model along with a turbulent diffusion model for the aerosol transport. The work starts off with the indoor airflow modeling of specific room, for which the numerical parameters are studied. In the next part a mathematical model of an air purifier is develped, which is numerically implemented and verified using the computational fluid dynamics toolbox OpenFOAM. The results of the aerosol concentration calculation suggest that the stationary RANS model does not correctly describe the turbulent concentration dispersion in the case of indoor air flows, which is cause to improve the model in the future