Influence of two-dimensional expiratory airflow variations on respiratory particle propagation during pronunciation of the fricative [f].

Propagation of respiratory particles, potentially containing viable viruses, plays a significant role in the transmission of respiratory diseases (e.g., COVID-19) from infected people. Particles are produced in the upper respiratory system and exit the mouth during expiratory events such as sneezing, coughing, talking, and singing. The importance of considering speaking and singing as vectors of particle transmission has been recognized by researchers. Recently, in a companion paper, dynamics of expiratory flow during fricative utterances were explored, and significant variations of airflow jet trajectories were reported. This study focuses on respiratory particle propagation during fricative productions and the effect of airflow variations on particle transport and dispersion as a function of particle size. The commercial ANSYS-Fluent computational fluid dynamics (CFD) software was employed to quantify the fluid flow and particle dispersion from a two-dimensional mouth model of sustained fricative [f] utterance as well as a horizontal jet flow model. The fluid velocity field and particle distributions estimated from the mouth model were compared with those of the horizontal jet flow model. The significant effects of the airflow jet trajectory variations on the pattern of particle transport and dispersion during fricative utterances were studied. Distinct differences between the estimations of the horizontal jet model for particle propagation with those of the mouth model were observed. The importance of considering the vocal tract geometry and the failure of a horizontal jet model to properly estimate the expiratory airflow and respiratory particle propagation during the production of fricative utterances were emphasized.

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.

Influence of Indoor Relative Humidity on the Number Concentration, Size Distribution, and Trajectory of Sneeze Droplets: Effects on Social Distancing Guidelines

The spread of the COVID-19 pandemic is mainly due to the direct transmission routes of SARS-CoV-2 virus-carrying aerosols in indoor environments. In this study, the effect of indoor relative humidity (RH∞) on the number concentration, size distribution, and trajectory of sneeze droplets was studied in a confined space experimentally and numerically. Computational fluid dynamics (CFD) simulations using the renormalization group k-ε turbulence model by considering the one-way and two-way (humidity) coupling models were performed to assess the effects of humidity fields on the propagation of droplets. Number concentration profiles indicated that the RH∞ affected the dispersion modes of droplets differently for the puff, droplet cloud, fully-dispersed, and dilute-dispersed droplets phases identified by the shadowgraph imaging technique. The two-way (humidity) coupling model led to a close agreement with the experimental data in all phases. In particular, the two-way coupling provided better agreement with the data in the puff phase compared to the one-way coupling model. However, the one-way coupling model was sufficient for studying the motion of airborne droplets in the other phases. The velocity fields in the droplet cloud were more sensitive to RH∞ than the puff and fully-dispersed droplets phases. Also, the effect of RH∞ on the maximum spreading distance of droplets, dmax,sp, in the puff was insignificant, while its effect became dominant in the dilute-dispersed droplets phase. A dynamic change in the velocity profile of the sneeze jet was seen at a critical relative humidity RH∞,crit of about 48%. At RH∞< RH∞,crit, the number concentration of aerosolized droplets increases, significantly affecting the size distribution and the velocity of droplets. At RH∞≥ RH∞,crit, the effect of evaporation time on the number concentration, and diameter of droplets was negligible. At RH∞ of 24 and 64%, dmax,sp was 2.14 m (7 feet) and 3.05 m (10 feet), respectively. However, a dry indoor environment led to an increase in evaporation rate and more than four times number concentration of aerosolized droplets compared to a humid environment. Thus, the risk of direct transmission of Covid-19 in a humid indoor environment was higher than the dry conditions, which suggested the requirements for incorporating the RH∞ effect in the social distancing guideline.

Selecting the Safe Area and Finding Proper Ventilation in the Spread of the COVID-19 Virus

Coughing and sneezing are the main ways of spreading coronavirus-2019 (SARS-CoV-2). People sometimes need to work together at close distances. This study presents the results of the computational fluid dynamics (CFD) simulation of the dispersion and transport of respiratory droplets emitted by an infected person who coughs in an indoor space with an air ventilation system. The resulting information is expected to help in risk assessment and development of mitigation measures to prevent the infection spread. The turbulent flow of air in the indoor space is simulated using the k-εmodel. The particle equation of motion included the drag, the Saffman lift, the Brownian force and gravity/buoyancy forces. The innovation of this study includes A: Using the Eulerian-Lagrangian CFD model for the simulation of the cough droplet dispersion. B: Assessing the infection risk by the Wells-Riley equation. C: A safer design for the ventilation system (changing the ventilation supplies and exhausts in the indoor space and choosing the right location for air ventilation). The droplet distribution in the indoor space is strongly influenced by the air ventilation layout. The air-curtain flow pattern significantly reduces the dispersion and spreading of virus-infected cough droplets. When the ventilation air flow occurs along the room length, it takes about 115 s for the cough droplets to leave the space. However, when the ventilation air flow is across the width of the indoor space and there are air curtain-type air flow patterns in the room, it takes about 75 s for the cough droplets to leave the space.

Effect of indoor temperature on the velocity fields and airborne transmission of sneeze droplets: An experimental study and transient CFD modeling.

The spread of the COVID-19 pandemic through the airborne transmission of coronavirus-containing droplets emitted during coughing, sneezing, and speaking has now been well recognized. This study presented the effect of indoor temperature (T∞) on the airflow dynamics, velocity fields, size distribution, and airborne transmission of sneeze droplets in a confined space through experimental investigation and computational fluid dynamic (CFD) modeling. The CFD simulations were performed using the renormalization group k-ε turbulence model. The experimental shadowgraph imaging and CFD simulations showed the time evolution of sneeze droplet concentrations into the turbulent expanded puff, droplet cloud, and fully-dispersed droplets. Also, the predicted mean velocity of droplets was compared with the obtained experimental data to assess the accuracy of the results. In addition, the validated computational model was used to study the sneeze complex airflow behavior and airborne transmission of small, medium, and large respiratory droplets in confined spaces at different temperatures. The warm room showed more than ∼14 % increase in airborne aerosols than the room with a mild temperature. The study provides information on the effect of room temperature on the evaporation of respiratory droplets during sneezing. The findings of this fundamental study may be used in developing exposure guidelines by controlling the temperature level in indoor environments to reduce the exposure risk of COVID-19.

Particle inhalability of a standing mannequin with large airways in a ventilated room.

This study presents a series of numerical simulations for airflow field and particle dispersion and deposition around a mannequin inside a ventilated room. A 3-D airway system of a volunteer subject with a large respiratory system was reconstructed from the nostril inlet to the end of the tracheobronchial tree 4th generation and was integrated into a standing mannequin at the center of a room. The room ventilation system supplied air through a diffuser and expelled air via a damper in three modes. The airflow field was first evaluated by solving the governing equations and the k-ω SST transitional turbulence model using the Ansys-Fluent software. Then spherical particles with various diameters were released into the room, and their trajectories were evaluated using the Lagrangian approach. Aspiration fraction and particle deposition for inhalation flow rates of 15 and 30 L/min were analyzed using a modified discrete random walk (DRW) stochastic model using a user-defined function (UDF) coupled to the Ansys-Fluent discrete phase model. For the first ventilation mode, a recirculation flow region formed behind the mannequin that led the airflow streamlines to the breathing zone. A recirculation flow formed in front of the face for the second ventilation mode that led the airflow streamlines out of the mannequin breathing zone. For the third mode, however, there was no strong recirculation flow zone around the mannequin. Simulation results showed that the aspiration fraction in the first ventilation mode was higher than the other modes. In addition, the regional deposition rates and deposition patterns of particles inside the respiratory system were presented for each region. Accordingly, most large particles were trapped in the nasal passage; however, some large particles penetrated deeper into the airway due to the large airway size. For the higher breathing rate, the percentage of large escaped particles from the lobe branches dropped by a factor of 7 compared to the lower breathing rate.

Variability in expiratory trajectory angles during consonant production by one human subject and from a physical mouth model: Application to respiratory droplet emission.

The COVID-19 pandemic has highlighted the need to improve understanding of droplet transport during expiratory emissions. While historical emphasis has been placed on violent events such as coughing and sneezing, the recognition of asymptomatic and presymptomatic spread has identified the need to consider other modalities, such as speaking. Accurate prediction of infection risk produced by speaking requires knowledge of both the droplet size distributions that are produced, as well as the expiratory flow fields that transport the droplets into the surroundings. This work demonstrates that the expiratory flow field produced by consonant productions is highly unsteady, exhibiting extremely broad inter- and intra-consonant variability, with mean ejection angles varying from ≈+30° to -30°. Furthermore, implementation of a physical mouth model to quantify the expiratory flow fields for fricative pronunciation of [f] and [θ] demonstrates that flow velocities at the lips are higher than previously predicted, reaching 20-30 m/s, and that the resultant trajectories are unstable. Because both large and small droplet transport are directly influenced by the magnitude and trajectory of the expirated air stream, these findings indicate that prior investigations of the flow dynamics during speech have largely underestimated the fluid penetration distances that can be achieved for particular consonant utterances.

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).