key: cord-0705466-laipjfq6 authors: Mirza, Shahid; Niwalkar, Amol; Gupta, Ankit; Gautam, Sneha; Anshul, Avneesh; Bherwani, Hemant; Biniwale, Rajesh; Kumar, Rakesh title: Is safe distance enough to prevent COVID-19? Dispersion and tracking of aerosols in various artificial ventilation conditions using OpenFOAM date: 2022-04-08 journal: Gondwana Res DOI: 10.1016/j.gr.2022.03.013 sha: c3adc36ce6fedb77d149f4f6b9a358237c9efa0f doc_id: 705466 cord_uid: laipjfq6 The current COVID-19 pandemic has underlined the importance of learning more about aerosols and particles that migrate through the airways when the person sneezes, cough and speak. The coronavirus transmission is influenced by particle movement, which contributes to the emergence of regulations on social distance, use of masks and face shield, crowded assemblies, and daily social activity in domestic, public, and corporate areas. Understanding the transmission of aerosols under different micro-environmental conditions, closed, or ventilated, has become extremely important to regulate safe social distances. The present work attempts to simulate the airborne transmission of coronavirus-laden particles under different respiratory-related activities, i.e., coughing and speaking using CFD modelling through OpenFOAM v8. The dispersion coupled with Discrete Phase Method (DPM) has been simulated to develop a better understanding of virus carrier particles transmission processes and their path trailing under different ventilation scenarios. The preliminary results of this study were found with respect to flow fields were found to be in close agreement with published literature, which was then extended under varied ventilation scenarios and respiratory-related activities. The study observed that improper wearing of mask leads to escape of SARS-CoV-2 aerosol having a smaller aerodynamic diameter from the gap between face mask and face and infect different surfaces on the environments in the vicinity. It is also observed that the aerosol propagation infecting the area through coughing is a faster phenomenon compared to the propagation of coronavirus-laden particles during speaking. The study's findings will help decision-makers formulate common but differentiated guidelines for safe distancing under different micro-environmental conditions. The airborne transmission risk of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first confirmed by the National Health Commission of the People's Republic of China and then by the Centre for Disease Control and Prevention (CDC) as the world faces a large outbreak of coronavirus disease 2019 (COVID-19) (Wang and Du, 2020; Feng et al., 2020) . Despite the fact that SARS-CoV-2 has a viral diameter ranging from 50 to 200 nm, it has been proved that SARS-CoV-2 transmits through inhalation or ingestion of contaminated particles. As a result, the principal causes of infection include coughing and contacting infected surfaces. The SARS-CoV-2 disease is well-known for relying on the transmission of tiny virus-containing respiratory particles that an infected person exhales when coughing or merely speaking or breathing (Guzman, 2020; Asadi et al., 2019) . The outbreak is at a distinct stage in each country. To slow the spread of the COVID-19 outbreak in most nations where the virus has produced exponential outbreaks, governments have asked for social distancing and mobility restrictions, often known as lockdown (WHO, 2020) . The World Health Organization (WHO) established guidelines stating that a virus takes 5 to 6 days to incubate, with a range of up to 14 days. COVID-and mortality. Depending on the instance, fever, dry cough, weariness, nasal congestion, diarrhea, and headache are some of the symptoms of COVID-19 (WHO, 2019a; Aldila et al., 2020) . The COVID-19 pandemic has resulted in a significant loss of civilian life throughout the world, and it poses an unprecedented threat to public health, food systems, and the workplace with psychological, economic, and societal consequences over the world, in addition to death. Few of the recent literature has also predicted the COVID-19 waves and the impact of environmental conditions, surface characteristics, air pollutions, etc. on the spread of the virus (Bherwani et al., 2020a; Bherwani et al., 2021a; Wathore et al., 2020; Nair et al., 2021) . Some work has also suggested that air pollutions and particle size play a vital role in the transmission of the SARS-COV-2, as these air particulates, especially PM 2.5 , act as carriers for the longer distance transmissions of the virus Bherwani et al., 2020c) . Due to lockdown, social distance, and economic crises, the COVID-19 pandemic has evolved in changes in the business environment and indirectly impacting gender disparity (Thakur and Jain, 2020) . Distancing oneself from others is one of the most efficient ways to slow the transmission of the virus, which is conveyed by air particles. Wearing masks, washing hands often, cleaning surfaces with alcohol, and avoiding physical contact can all help prevent the spreading of the infection and thus form an integral part of COVID-19 appropriate behaviour (Qian and Jiang, 2020) . However, improper disposal of masks and special PPE kits might be risky and infect the people in surrounding . Fine particles of water, air, tiny particles (having a diameter less than 1μm), and respiratory fluid occur as a result of active breathing and coughing. These components of human reflex processes generate at varying rates and for longer periods, resulting in a variety of impacts on the environment and the human body Zhang et al., 2015; Dudalski et al., 2020) . Aerosol particles transmission is primarily determined by the size of the particles and the speed at which they propagate (Guan et al., 2014; Sun and Ji, 2007; Chen and Zhao, 2010) . According to studies, particles with a larger diameter (100 to 1000 μm) fall on surfaces abruptly due to gravity, whereas particles with a smaller diameter (1 to 100 μm) can travel by air and remain suspended for a long period which is sufficient to carry both bacteria and viruses with SARS-CoV-2 Ribonucleic Acid (RNA) (Aliabadi et al., 2010; Wei and Li, 2015; Wells, 1934; Gralton et al., 2011; Chao et al., 2009) . During 5 minutes of conversation, a single individual can release about 3000 germs, while coughing can release even more particles. These particles are too small to be seen with the naked eye, but they are large enough to fly through the air and spread disease (Lindsley et al., 2010; Fabian et al., 2011) . A study conducted by Feng et al. investigated the impact of humidity and wind on the effect of social distance in preventing maximal airborne transmission using a numerical model (Feng et al., 2020) . To simulate realistic air flows during inhalation and the distribution of airborne particles in the room, Xu et al. used the area surrounding the human face as geometry as the infectious aerosols exist in various shapes and sizes tracking their dispersion particularly difficult (Xu et al., 2018) . The work by Hasan suggested that CFD be used to improve the ventilation system and remove infectious particles curbing the spread of the virus (Hasan, 2020) . Using environmental conditions, Busco et al. statistically examined the sneezing process in a COVID-19 virus-infected asymptomatic carrier (Busco et al., 2020) . Zhang et al. conducted a study to determine the size of aerosol in the room and the coughing of the patient (Zhang et al., 2019) . Furthermore, the microparticles' size is an essential element influencing aerosol particle dispersion and deposition (Gao and Niu, 2007; Morawska, 2006) . The transport of expelled drops can be separated into two steps, the first is linear jet transport during coughing, and the second is small particles dispersion by the airflow in the room, as the reaction speed of breathing and coughing upon escape is on average approximately 1-22 m/s . It is vital to mimic the generation and dissemination of viruses in an artificial environment to understand better how they propagate (Löhner et al., 2020) . Inhalation of coronavirus-laden airborne particles produced from an infected person can help transmit the diseases to multiple people in the vicinity. Also, in closed areas, the restricted flow can aid the presence of the virus at numerous surfaces of the room, and increase the chance of the virus spread. The multiple respiratory-related activities like speaking, coughing, and breathing release micro air particles or aerosols/particulates, which can be infected, if released from an infected person. Hence, to curb the spread of the virus through airways, it will be important to understand the transmission distance of the virus under different human activities and ventilation scenarios to avoid physical contact with infected surfaces and physical contact with potentially infected persons. Given this, it will be essential to simulate particulate/aerosol transmission to develop insights on the infected surface under different real-world conditions. OpenFOAM v8 is used in this study to model the airborne transmission of aerosol generated when breathing, speaking, and coughing in a closed setting, as well as its dispersion under various artificial ventilation conditions. Scenarios are created based on the demand for airflow in the room, allowing researchers to quantify the actual and realistic flow and dispersion of aerosol particles in a room. For a better understanding, several permutation combinations of fan and air conditioner (AC) are simulated, and comparisons of speaking and coughing scenarios with and without a mask are investigated. All the situations are created using current safe distance (1.8 meters) guidelines. In all scenarios, tracking of aerosol particles on room surfaces is attempted. The behaviour and propagation of aerosol produced during speaking and coughing are modelled using an open-source CFD tool OpenFOAM. The subsequent sections discuss the mathematical model, the detailed validation, and the numerical setup used in this study. Navier-Stokes equations are the fundamental set of equations used to build a mathematical model in this study for the airflow in a room which are numerically implemented by the OpenFOAM v8. The continuity and momentum equations used in the model are defined by Eq. (1) and Eq. (2) (Openfoam, 2014) . (1) where, is the effective viscosity, p is the pressure in pascal, S is the external force of the body. µ The suffices a and b denote the b direction on a surface normal to a direction. Using a Lagrangian approach, the discrete phase modelling (DPM), which relates to the processes of aerosol particles dispersion throughout the required computational domain, is calculated as a sequence of differential equations. For the motion of isothermal particles, the following set of ordinary differential equations was solved, which gave the kinematic relationship between the speed of the aerosol particle with the corresponding position in Eq. (3) and Eq. (4). (3) = is the position of a particle, is the speed of particles, is the mass of particles and is the force acting on the particles. Newton's second law of motion assumes that all relevant forces acting on a particle, such as drag, gravitational and buoyancy forces, and pressure forces, are taken into account, which can be represented by Eq. (5). (5) = ∑ = + + Among all the forces, drag is the most important force (about 80% of the total force) which is measured in terms of the drag coefficient . The drag force can be presented by Eq. (6). is the fluid density, is the diameter of a particle. The SST k-ω turbulence model was employed to perform the OpenFOAM simulations under the various boundary conditions. All the model equations used for the simulation and description have been referred from peer-reviewed publications (Spalart, 1997; Menter, 1994; Menter and Kuntz, 2003; Jones and Launder, 1972) . The SST k-ω model was used owing to its ability to demonstrate a precise depiction of the indoor airflow (Stamou and Katsiris, 2006; Zhang et al. 2009; Issakhov et al., 2020) . To validate the simulated results of the DPM model, a test case was simulated and compared with the result of Han et al. (2019) for the ventilation in a room. Further, the results were also validated with an onsite sample collection in a SARS-CoV-2 dedicated hospital performed by Dubey et al. (2021) . A test case was designed as per the data given by Han et al. (2019) to perform a ventilation scenario for the validation and the data calculated by Nielsen et al. (2010) after experimenting was taken as the basis of the present study test case. A 3D model was created which consisted of an enclosed room having one inlet and outlet as shown in Fig. 1 . The detailed description of the 3D model parameters and the physical parameters used for a test case is mentioned in Table 1 . All the parameters used to simulate the test case have been given by Han et al. (2019) . The reason for choosing such a type of computational grid is to improve the accuracy of the fluid flow and ease in the comparison with experimental data. Air material with its conditional parametric values for a closed room with ventilation is chosen. Fig. 1 is showing some cross-sectional area (x=H and y=1/2a) where the air velocity was calculated. The study has proceeded for the further and most important validation. The sample collection of aerosols containing SARS CoV-2 RNA has been performed by Dubey et al. (2021) The study was conducted in the various ward of COVID dedicated hospital. It was not possible to create geometry and simulate a model for the entire hospital ward. For the validation, an area of the "Medicine Ward" was taken containing a patient with mask, patient's bed, surrounding walls, and 2 air conditioners and a sampler as can be seen in Fig. 2 DPM modelling has been performed throughout the cases for the present study with an SST k-ω turbulence model to track the particles expelled by a person. There is total of twelve cases are simulated with different ventilation and boundary conditions with and without the mask. All the cases are considered by the same room but varying ventilation conditions. The room having dimensions 5.8 m × 4 m × 3 m consists of a ventilation window, AC, fan and a window to allow air inside the room. Two human bodies are considered in the room, one was set as an active man through which particles are injected in the room and the other was set as an inactive man with no respiratory-related activities. The detailed dimensions of all the objects are discussed in Fig. 4 . The 'blockMesh' utility of OpenFOAM is used to create a room with all required dimensions followed by another utility 'snappyHexMesh' which is used to recreate the block mesh. In this study, 3D CAD (Computer-Aided Design) models of human bodies, fan, AC, window, and outlet patch have been overwritten by this utility. The overlook of some objects after meshing used in this study can be seen in Fig. 5 . The grid independence for the modelling has been achieved at 145 × 100 × 75 refinements of the blockMesh. There is a total of three scenarios (Scenario 1, 2 & 3) simulated with twelve permutation combinations of with and without mask consisting of speaking and coughing. In Scenario 1, a five minutes simulation is carried out for speaking by an active person standing on the left (in every case) and five times repeated coughing is considered by an active person in the case of coughing. The particle size distribution for the speaking has been set to 0.1 μm to 200 μm. On the other side, in the case of coughing the diameter is set in the range of 0.1 μm to 1000 μm Duguid, 1945; Duguid, 1946; Gerone et al., 1966; Loudon and Roberts, 1997; Fennelly et al., 2004; Johnson and Morawska, 2009; Chao et al., 2009) has been set the same as that of the AC room case. The type of scenarios with detailed room ventilation and respiratory activities are described in Table 2 . The grid independence test for the present study has been carried out by refinement of the study area in the direction of airflow. The test is carried out by considering a domain grid with velocity magnitudes at , . All the points for grid independence study are selected = 2.6 = 3.9 along with the wall patch of the boundaries of the inlet and outlet so that maximum fluctuation can be obtained with all the types of meshing. There is three level of meshing performed depending upon the airflow criterion of the model named as coarse, medium and fine with fine, finer and finest refinement respectively. The domain with all the requirements selected for the grid independence study can be illustrated in Fig. 6 . The total number of elements produced in all types of meshing is discussed in Table 3 . According to the Richardson extrapolation theory, the refinement ratios must be greater than 1.3 (Roache, 1994) From Fig. 7 and obtained results, it is confirmed that the convergence has been achieved with a different types of mesh types which is a key criterion and basic steps to assure that the simulations performed in this study are correct. The particles produced by speaking and coughing are considered as particles with real size distributions without any chemical composition and chemical interaction. Although the current study is based on a simplified and ideal case scenario, it does not consider several affecting factors such as humidity, particles evaporation, and temperature. Validation scenario of the airtight room would be eligible for another flowing pattern. It is important to understand that these are the circumstances under which the modelling and simulations have been done. With the inclusion of all the mentioned environmental and physical factors the study can improve and findings will be more accurate. As a result, the current study has certain limitations which may be resolved in future studies and multiple parameters as indicated above may be considered and interactions related to those parameters will be studied in detail. Simulations of coughing and speaking personnel have been performed with and without a mask by considering necessary environmental and physical parameters. All the scenarios with boundary conditions used for simulations are mentioned in Table 2 . Outcomes of this work explore the fact that aerosol containing deadly SARS-CoV-2 RNA spreads over the entire room under reallife conditions having well enough ventilation and can suspend in the air for a long time. The above fact holds for all the respiratory activities such as coughing and speaking. The particle size (diameter) played important role in dispersion and has been simulated for varied conditions. In ventilation validation, the velocity contour of a test case obtained is compared with the result obtained by Han et al. can be seen in Fig. 8 . can be said that the room ventilation requirement is met and that the boundary condition can be utilized to simulate airflow with particles. The results obtained in the present study depicted by Fig. 10 with the spread of aerosol particle in an area is considered for the validation. Figure showing a sampler on which particles are stuck due to suction and due to the circulation of air between the surrounding wall of bed most of the particles are stuck on the walls as well and back wall of the patients. The sampler used for the particle collection was on a vacuum motor with a varying flow rate of 1.5, 16.7 and 27 LPM and was set at 1 meter and 3-meter distance from the patient's head. Due to different flow rates, the number of particles stuck on the sampler are also varying. Fig. 10 illustrates the number of particles received by the sampler with varying flow rate. The particle tracked by the sampler with the corresponding flow rate is shown in Fig. 11 . The number of particles interacting with the sampler increased with the suction capacity of the sampler and it was found to be directly proportional to the volumetric flowrate of the sampler. According to the hospital data, the percentage of particles tracked on a sampler with the current particle tracking sampler used in validation is 100% for all the flow rates when sampler is kept at 1-meter distance from the patient's head end. While for the distance of 3 meters, the percentage is found to be 0%, 17% and 50% for the flow rate 1.5, 16.7 and 27 LPM of the sampler. The present study is following a similar ratio of a varying number of particles with the percentage of people getting an infection at 1 meter and 3 meters respectively. It has been concluded that the propagation of particles within the air in a ventilated room is valid. The post-processing tool examines the air velocity profiles produced by artificial thrust sources such as air conditions and fans. The purpose of analyzing air flow profiles within a room is to have a better understanding of particle flow and dispersion within the space under forced draft conditions. The airflow patterns created by an AC patch with an inlet velocity of 0.5 m/s in the positive X and negative Z directions are shown in Fig. 12 . Another airflow profile is examined as a result of the fan patch with a 0.5 m/s inlet velocity along the negative Z direction, as shown in Fig. 13 . On XZ and XY plane slices, velocity profiles are captured. Particle emitted by speaking and coughing of active person is simulated with and without a mask by considering stagnant conditions in the room. All the forces acting on the particles are due to gravity, buoyancy and drag. As there is no air circulation inside the room, the start time of particle injection was set after 10 sec of simulation. There are two cases are simulated in each scenario, one is for speaking and the other for coughing. Both the cases have been analyzed with and without putting the mask on the face of an active person. The case is considered with an active man spreading aerosols by the respiratory activities and interacts with a passive man standing over there with no activities with a safe distance of 1.8 meters (WHO, 2019). In a coughing scenario, the dispersion of particles of all sizes can be seen with mask (3.B.1) and without mask (3.B.2.) conditions. Due to the vortex formation in the centre of both the bodies, the particles having lesser diameter did not travelled on the other side but they dispersed in half of the room and were found on the back and side wall, and ventilation window. All scenarios considered in the present study discussed the the particles are found on the surfaces (front wall, back wall, side wall and ventilation window) of the room by speaking and coughing respectively. In speaking scenarios, the particles are found on a front wall which is 3.8 meters away from the active person is higher in scenario 2 compared to scenarios 1 & 3. In the ventilation window which acted as an outflow air patch in all the cases, there is no particle tracked in scenario 1 indicating that poor ventilation conditions i.e., without AC/fan and no inflow of air, stagnant the particles in air creating a worse scenario for COVID-19 preventions. In case of speaking the distribution of particles for mask conditions remained in a ratio which is similar to without mask conditions for both the cases of ventilation i.e. using AC and fan. In Fig. 21 (coughing scenarios), there are very few particles tracked on the front wall in all scenarios with mask condition but in without mask condition, the quantity of particles is found about 450 in scenario 2 only. Similarly, on the back wall, side walls and ventilation window, the particles are found in low numbers (about 2 to 9) with mask conditions in all the scenarios. From all the graphs, it is evident that without a masked person can spread many particles in the ventilated environment and can be more dangerous to health of others during the pandemic (Bherwani et al., 2021d; Bherwani et al., 2021e; Kaur et al., 2021) . Thus, it is indicated that mask conditions are much better and mask should be worn at all time while speaking or coughing. However, it is been observed that the particles coming from the gap of the mask and can also spread to a long-range using air as a medium of transport. Hence it is necessary that proper wearing of mask should inform to the citizens so that the particles do not get release from the gap of the mask. the activities performed by individual which an active person is doing. The dispersion of particles is found different by speaking different words (Silwal et al., 2021) . Indoor experiments and numerical simulations are performed to understand the dispersion and travelling of aerosol particles by considering case studies and concluded that particles having a small diameter can suspend in the air for a long time Shah et al., 2021) . However, the aerosol particles used in this study are artificial solid particles devoid chemical composition and reaction (inert) that are sized and weighed according to standard ranges. Some environmental conditions, such as temperature and humidity, may influence the particles in real life situations which is not considered in our modelling exercise. The current research focuses on particle dispersion and movement inside the room, as well as the effects of various air input sources on particle motion. The findings of this study can dispel any worries about the right usage of a mask and safe distancing. From the findings of this paper, it can be said that the dispersion and spreading of aerosol particles depend upon the ventilation conditions where the active person is standing and doing respiratory activities. This study shows the spread of aerosol particles beyond the current government and WHO guidelines (1.8 meters) and can also spread not only along the ejection direction (in straight) but also at a certain height of ceilings and ventilation windows. Many particles have reached towards the ventilation window (2 meters where people are used to gathering in a large quantity. The present work used CFD modelling to investigate the transport and scattering of particles of various sizes (0.1 to 200 μm and 0.1 to 1000 μm) that occurred when a person speak and cough. The process of injecting particles into the indoor environment by an active person was used to simulate a realistic process of speaking and coughing with velocities 3.22 m/s and 20 m/s respectively. Validation is carried out to satisfy the room ventilation condition with an inlet airflow over the room and is found in a good manner with the experimental data and simulation results. Hence the modelling setup can be considered useful for generating other scenarios. Another validation on particles tracking with airflow conditions according to distance mentioned in the literature has been performed to make sure that dispersion and propagation of particles with air considered for the simulation of the present study fall in the correct manner. Computational studies of the transport and distribution of particles have been performed during speaking and coughing in a closed room with various ventilation conditions. In without mask scenarios of all the ventilation conditions, it is noted that the particles having larger size fell on a body and transported over short distances and the particles having smaller size propagated over long distances. It should also be noted that the person speaking only for 5 minutes without the mask is enough to spread the large number of particles containing deadly SARS Co-V-2 RNA. By consideration of active and inactive persons with masks, the spread of particles without ventilation condition (no external airflow in a room) is quite enough to spread the infection, but it is not possible to have zero ventilation in a closed room with the presence of humans. In an AC room with a ventilation window, the dispersion of the particles is found in the entire room even after wearing a mask. Spread of low size of particles (0.1 -20 μm for speaking and 0.1 -200 μm for coughing) have occurred in all directions and are detected on the walls and the ceiling of the room. In the case of a room with a fan, window for inlet airflow, and ventilation window for outflow of air, the particles dispersion quantity is in similar quantity as that of AC room but the area confined by the particles are approximately half. Due to the maximum vortices formed with a fan inlet patch and an air window, the low size particles are restricted to travel over an area where an active person is standing. One of the primary problems, due to the prevalence of COVID-19 in most regions of the world, is the correlation between environmental parameters such as rising air temperatures and the rapid spread of coronavirus. The studies stated that the maximum relative humidity, maximum temperature, and wind speed can be responsible for the spreading of the corona virus while some of the studies also stated that with increasing temperature, the spreading of coronavirus disease has decreased. In a WHO article, it is also mentioned that the low pH, sunlight, and heat make it easier to kill the coronavirus. Although, there is no direct relation between the environmental factors that one can say increasing temperature results in an increase in positive cases there may be an impact of environmental factors on the spreading of the virus. Outdoor and microclimatic modelling with environmental factor have been carried out in several studies (Bherwani et al., 2021b; Mirza et al., 2021; Bherwani et al., 2021c) , by creating corelation between outdoor environmental factors and indoor ventilation conditions which are used in existing study can establish the better platform to understand the spreading of corona virus (Bherwani et al., 2020b) . However, we have not considered discussed interaction into our study and this becomes a part of future studies. 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