Modeling the interaction between breathing jets and personalized ventilation jets for improved infection control in indoor spaces
Indoor environments play a critical role in maintaining the health and comfort of occupants, especially in places where people spend extended time in close proximity, like offices, classrooms, and airplanes. In such spaces, the risk of airborne transmission of pathogens in droplets and aerosols exhaled during regular breathing can be exacerbated by poor ventilation and inadequate air exchange.
Recent studies indicate that measures such as personalized ventilation systems can effectively reduce the risk of airborne disease transmission. However, the interaction between the exhalation jet and personalized ventilation jet can have a significant influence on virus-laden droplet dispersion and dissipation. Therefore, it is important to model this interaction to better predict droplet behavior and provide improved benchmarks for infection control strategies. The main objective is to develop and validate a model of flow interaction and analyzing dispersion patterns of small droplets in the interaction zone. The CFD procedure employs Large Eddy Simulation (LES) to capture detailed turbulence dynamics within the room, coupled with a multiphase particle-laden flow model to simulate droplets in the 0.3 to 5 µm range, accurately reflecting particle-laden jet characteristics in turbulent environments. LES is chosen for its ability to resolve the fine-scale turbulent structures critical to understanding droplet interactions with incoming jets, offering a high level of precision in predicting droplet trajectories in airflow. Euler-Lagrange Method methods have proven effective in capturing the complexities of turbulent, particle-laden jets, as demonstrated in studies investigating turbulent particle dynamics in similar scenarios. Experimental validation will use visual and quantitative measurement techniques: Schlieren imaging with high-speed cameras to observe jet interaction patterns in real-time, and particle measurement tools such aerodynamic particle sizer (APS) to capture the concentration and size of airborne particles in the interaction zone. Humidity sensors and omnidirectional anemometers will measure airflow velocities and moisture distribution at multiple points to ensure comprehensive data for model validation. Experimental variability of the personalized ventilation jet will introduce airflow angle and speed variations to test droplet dissipation under different realistic operation condition, establishing a robust dataset to inform model adjustments and provide meaningful benchmarks for infection control strategies. Expected results include insights into exhaled droplet behavior in indoor spaces their dissipation under certain conditions. Data from this study will provide benchmarks for designing personalized ventilation systems aimed at minimizing infection risks in enclosed environments, informing best practices for indoor air quality management, especially in high-density where infection control is critical.
Funding institution:
The German Academic Exchange Service (DAAD)
Project duration:
10/2024 - 9/2028
Contact person:
Ali Abuelnour, M.Sc.
Tel.: +49(0)3643/584830