ABSTRACT
The outbreak of COVID-19 has caused a worldwide pandemic. The widespread infection of the medical staff has caused great attention from all quarters of society. There is a particular concern when considering intubation treatment in the emergency operating room, where a significant amount of virus droplets are typically spread within the room, exposing the medical staff to a high risk of infection. Hence, there is currently a pressing need to develop an effective protection mechanism for the medical staff to prevent them from being infected during routine work. In order to understand the spread of droplets and aerosols when different oxygen supply devices are used for intubation therapy, this study uses particle image velocimetry (PIV) technology to analyze the airflow distribution between the medical staff and the patient. In the experiment, a simple version of the respirator was established to reproduce the breathing of human lungs. This model used oil to create smoke as a tracer aerosol, then a high-sensitivity camera was used to record the scattering light from this smoke (which is irradiated by the green laser sheet). Ultimately, after applying post-processing techniques, the airflow distribution is analyzed. PAO aerosol is the primary aerosol source in this experiment, and it is used to quantify the patient's breathing;the concentration of PAO aerosol was measured at three different points: head, trunk, and feet. In addition, flow field visualization can effectively present the flow field distribution of the entire operating room;also, the results can be mutually verified with the PAO concentration measurement results. Aerosol concentrations were measured for six different oxygen supply devices with various tidal volumes of the artificial respirator, and the results were ranked from high to low concentrations for different oxygen supply devices and their operational oxygen supply flowrates: HFNC (70 l/min) > CPAP (40 l/min) > HFNC (30 l/min) > nasal cannula (15 l/min) > NRM (15 l/min) > VAPOX (28 l/min). © 2022, The Author(s).
ABSTRACT
Under the global landscape of the prolonged COVID-19 pandemic, the number of individuals who need to be tested for COVID-19 through screening centers is increasing. However, the risk of viral infection during the screening process remains significant. To limit cross-infection in screening centers, a non-contact mobile screening center (NCMSC) that uses negative pressure booths to improve ventilation and enable safe, fast, and convenient COVID-19 testing is developed. This study investigates aerosol transmission and ventilation control for eliminating cross-infection and for rapid virus removal from the indoor space using numerical analysis and experimental measurements. Computational fluid dynamics (CFD) simulations were used to evaluate the ventilation rate, pressure differential between spaces, and virus particle removal efficiency in NCMSC. We also characterized the airflow dynamics of NCMSC that is currently being piloted using particle image velocimetry (PIV). Moreover, design optimization was performed based on the air change rates and the ratio of supply air (SA) to exhaust air (EA). Three ventilation strategies for preventing viral transmission were tested. Based on the results of this study, standards for the installation and operation of a screening center for infectious diseases are proposed.