Prediction of COVID-19 Infection in Dental Clinic by CFD and Wells-Riley Model, Identifying Safe Area and Proper Ventilation Velocity: Prédiction de l'infection au COVID-19 dans une clinique dentaire par CFD et modèle Wells-Riley, identification de la zone de sécurité et de la vitesse de ventilation appropriée.

The COVID-19 virus is recognized worldwide as a significant public health threat. A dental clinic is one of the most dangerous places in the COVID-19 epidemic, and disease transmission is rapid. Planning is essential to create the right conditions in the dental clinic. In this study, the cough of an infected person is examined in a 9 × 6 × 3 m3 area. Computational fluid dynamic (CFD) is applied to simulate the flow field and to determine the dispersion path. The innovation of this research is checking the risk of infection for each person in the designated dental clinic, choosing the suitable velocity for ventilation, and identifying safe areas. In the first step, the effects of different ventilation velocities on the dispersion of virus-infected droplets are investigated, and the most appropriate ventilation flow velocity has been identified. Then, the results of the presence or absence of a dental clinic separator shield on the spread of respiratory droplets have been identified. Finally, the risk of infection (by the Wells-Riley equation) is assessed, and safe areas are identified. The effect of RH on droplet evaporation in this dental clinic is assumed to be 50%. The NTn values in an area with a separator shield are less than 1%. When there is a separator shield, the infection risk of people in A3 and A7 (the other side of the separator shield) is reduced from 23% to 4%, and 21% to 2%, respectively.

Finding the proper position of supply and return registers of air condition system in a conference hall in term of COVID-19 virus spread.

The outbreak of the COVID-19 has affected all aspects of people's lives around the world. As air transmits the viruses, air-conditioning systems in buildings, surrounded environments, and public transport have a significant role in restricting the transmission of airborne pathogens. In this paper, a computational fluid dynamic (CFD) model is deployed to simulate the dispersion of the COVID-19 virus due to the coughing of a patient in a conference hall, and the effect of displacement of supply and return registers of the air conditioning system is investigated. A validated Eulerian-Lagrangian CFD model is used to simulate the airflow in the conference hall. The particles created by coughing are droplets of the patient's saliva that contain the virus. Three cases with different positions of supply and return registers have been compared. The simulation results show that case1 has the best performance; since after 80 s in case 1 that the inlet registers are in the longitudinal wall, the whole particles are removed from space. However, in other cases, some particles are still in space.

Investigation of the effects of mechanical and underfloor heating systems on the COVID-19 viruses distribution.

Investigation of the spread of pollutants and especially pathogenic particles in the interior of today's buildings has become an integral part of the design of such buildings. When the Coronavirus is prevalent in the world, it is necessary to pay attention to the spread of the virus in the interior of residential apartments. In the present study, the Coronavirus particles emitted from the sneezing of a sick person in the bedroom of a residential apartment were tracked. Meanwhile, the degree of exposure of a mannequin that has been placed in the living room playing the role of a healthy person is examined. In this research, a segregated solution of steady-state flow and an unsteady particle solution have been separately used: a suitable, accurate, and optimal solution in particle studies. A comparison of the results shows that underfloor heating creates a healthier space around the healthy person's respiratory system, but instead, we will see more polluted areas around the sick person. According to the PRE results, the PRE value for a mechanical heating system is higher than a floor heating system. Therefore, it is recommended to use mechanical heating system in the apartments where the person with COVID-19 is hospitalized.

COVID-19 spread in a classroom equipped with partition - A CFD approach.

In this study, the motion and distribution of droplets containing coronaviruses emitted by coughing of an infected person in front of a classroom (e.g., a teacher) were investigated using CFD. A 3D turbulence model was used to simulate the airflow in the classroom, and a Lagrangian particle trajectory analysis method was used to track the droplets. The numerical model was validated and was used to study the effects of ventilation airflow speeds of 3, 5, and 7 m/s on the dispersion of droplets of different sizes. In particular, the effect of installing transparent barriers in front of the seats on reducing the average droplet concentration was examined. The results showed that using the seat partitions for individuals can prevent the infection to a certain extent. An increase in the ventilation air velocity increased the droplets' velocities in the airflow direction, simultaneously reducing the trapping time of the droplets by solid barriers. As expected, in the absence of partitions, the closest seats to the infected person had the highest average droplet concentration (3.80 × 10-8 kg/m3 for the case of 3 m/s).