{"id":{"repo_id":"uic","oai_identifier":"oai:figshare.com:article/31451440"},"canonical_url":"https://search.dev.ndltd.org/etd/uic/oai:figshare.com:article/31451440","repository":{"repo_id":"uic","name":"University of Illinois - Chicago","base_url":"https://api.figshare.com/v2/oai"},"display":{"title":"Simulation of a Singular Cough Event in an Enclosed Breakroom","abstract":"In the wake of the COVID-19 pandemic, there has been an increased interest in the behavior of infectious aerosols and droplets, with the goal of better understanding transmission events in various situations of prolonged personal exposure. This study simulates the evolution of a singular cough event in a computer modeled breakroom. In addition, another model is created to simulate the inlet conditions. This model is a detailed simulation of the inlet flow through a perforated plate covering the vent, using a k-omega SST model. This model serves as the inlet boundary conditions for the primary breakroom model. The breakroom's continuous phase is simulated using k-epsilon realizable, which accurately models boundary layers as well as open sections of the breakroom. After this, a discrete phase injection, which serves as a virtual human cough, is tracked throughout the room for 10 minutes. The discrete phase injection uses a distribution of droplets with different diameters to capture the physical behavior of a singular cough event. Four cases are analyzed, with different computational manikin positions in each case. The results are analyzed to determine important particle behavior in the breakroom. It was found that the position of the initial cough with respect to the vents was significant. In particular, when the cough was nearer to the inlet vent, where turbulence was higher, the particles dispersed throughout the room quicker, but the amount of particles left in the room after ten minutes was also lower. In contrast, coughing near the outlet vent did not correspond to less particles in the domain after ten minutes as the turbulence was lower in this region of the breakroom. This study demonstrates that the dominant factor in particle dispersion and particle residence time is air turbulence in the area of a cough. Hence, higher air intake flow rates may lead to faster particle dispersion but also to lower amounts of infectious particles in a room.","abstract_html":"In the wake of the COVID-19 pandemic, there has been an increased interest in the behavior of infectious aerosols and droplets, with the goal of better understanding transmission events in various situations of prolonged personal exposure. This study simulates the evolution of a singular cough event in a computer modeled breakroom. In addition, another model is created to simulate the inlet conditions. This model is a detailed simulation of the inlet flow through a perforated plate covering the vent, using a k-omega SST model. This model serves as the inlet boundary conditions for the primary breakroom model. The breakroom's continuous phase is simulated using k-epsilon realizable, which accurately models boundary layers as well as open sections of the breakroom. After this, a discrete phase injection, which serves as a virtual human cough, is tracked throughout the room for 10 minutes. The discrete phase injection uses a distribution of droplets with different diameters to capture the physical behavior of a singular cough event. Four cases are analyzed, with different computational manikin positions in each case. The results are analyzed to determine important particle behavior in the breakroom. It was found that the position of the initial cough with respect to the vents was significant. In particular, when the cough was nearer to the inlet vent, where turbulence was higher, the particles dispersed throughout the room quicker, but the amount of particles left in the room after ten minutes was also lower. In contrast, coughing near the outlet vent did not correspond to less particles in the domain after ten minutes as the turbulence was lower in this region of the breakroom. This study demonstrates that the dominant factor in particle dispersion and particle residence time is air turbulence in the area of a cough. Hence, higher air intake flow rates may lead to faster particle dispersion but also to lower amounts of infectious particles in a room.","abstract_has_math":false,"creators":["Isaac Banes (23291695)"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12-01T00:00:00Z","date_published":"2025-12-01T00:00:00Z","updated_at":"2026-07-27T21:34:27Z","subjects":["Computational Fluid Dynamics"],"languages":[],"rights":["In Copyright"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.25417/uic.31451440.v1","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Isaac Banes (23291695)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-12-01T00:00:00Z"]},{"key":"dc:relation","label":"Dc Relation","values":["https://figshare.com/articles/thesis/Simulation_of_a_Singular_Cough_Event_in_an_Enclosed_Breakroom/31451440"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computational Fluid Dynamics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10.25417/uic.31451440.v1"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In the wake of the COVID-19 pandemic, there has been an increased interest in the behavior of infectious aerosols and droplets, with the goal of better understanding transmission events in various situations of prolonged personal exposure. This study simulates the evolution of a singular cough event in a computer modeled breakroom. In addition, another model is created to simulate the inlet conditions. This model is a detailed simulation of the inlet flow through a perforated plate covering the vent, using a k-omega SST model. This model serves as the inlet boundary conditions for the primary breakroom model. The breakroom's continuous phase is simulated using k-epsilon realizable, which accurately models boundary layers as well as open sections of the breakroom. After this, a discrete phase injection, which serves as a virtual human cough, is tracked throughout the room for 10 minutes. The discrete phase injection uses a distribution of droplets with different diameters to capture the physical behavior of a singular cough event. Four cases are analyzed, with different computational manikin positions in each case. The results are analyzed to determine important particle behavior in the breakroom. It was found that the position of the initial cough with respect to the vents was significant. In particular, when the cough was nearer to the inlet vent, where turbulence was higher, the particles dispersed throughout the room quicker, but the amount of particles left in the room after ten minutes was also lower. In contrast, coughing near the outlet vent did not correspond to less particles in the domain after ten minutes as the turbulence was lower in this region of the breakroom. This study demonstrates that the dominant factor in particle dispersion and particle residence time is air turbulence in the area of a cough. Hence, higher air intake flow rates may lead to faster particle dispersion but also to lower amounts of infectious particles in a room."]},{"key":"dc:title","label":"Title","values":["Simulation of a Singular Cough Event in an Enclosed Breakroom"]}]}],"canonical_facts":{"dc:creator":["Isaac Banes (23291695)"],"dc:date":["2025-12-01T00:00:00Z"],"dc:description":["In the wake of the COVID-19 pandemic, there has been an increased interest in the behavior of infectious aerosols and droplets, with the goal of better understanding transmission events in various situations of prolonged personal exposure. This study simulates the evolution of a singular cough event in a computer modeled breakroom. In addition, another model is created to simulate the inlet conditions. This model is a detailed simulation of the inlet flow through a perforated plate covering the vent, using a k-omega SST model. This model serves as the inlet boundary conditions for the primary breakroom model. The breakroom's continuous phase is simulated using k-epsilon realizable, which accurately models boundary layers as well as open sections of the breakroom. After this, a discrete phase injection, which serves as a virtual human cough, is tracked throughout the room for 10 minutes. The discrete phase injection uses a distribution of droplets with different diameters to capture the physical behavior of a singular cough event. Four cases are analyzed, with different computational manikin positions in each case. The results are analyzed to determine important particle behavior in the breakroom. It was found that the position of the initial cough with respect to the vents was significant. In particular, when the cough was nearer to the inlet vent, where turbulence was higher, the particles dispersed throughout the room quicker, but the amount of particles left in the room after ten minutes was also lower. In contrast, coughing near the outlet vent did not correspond to less particles in the domain after ten minutes as the turbulence was lower in this region of the breakroom. This study demonstrates that the dominant factor in particle dispersion and particle residence time is air turbulence in the area of a cough. Hence, higher air intake flow rates may lead to faster particle dispersion but also to lower amounts of infectious particles in a room."],"dc:identifier":["10.25417/uic.31451440.v1"],"dc:relation":["https://figshare.com/articles/thesis/Simulation_of_a_Singular_Cough_Event_in_an_Enclosed_Breakroom/31451440"],"dc:rights":["In Copyright"],"dc:subject":["Computational Fluid Dynamics"],"dc:title":["Simulation of a Singular Cough Event in an Enclosed Breakroom"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T21:34:27Z"}