Towards optimal design of patient isolation units in emergency rooms to prevent airborne virus transmission: From computational fluid dynamics to data-driven modeling.

BACKGROUND: Patient isolation units (PIUs) can be an effective method for effective infection control. Computational fluid dynamics (CFD) is commonly used for PIU design; however, optimizing this design requires extensive computational resources. Our study aims to provide data-driven models to determine the PIU settings, thereby promoting a more rapid design process. METHOD: Using CFD simulations, we evaluated various PIU parameters and room conditions to assess the impact of PIU installation on ventilation and isolation. We investigated particle dispersion from coughing subjects and airflow patterns. Machine-learning models were trained using CFD simulation data to estimate the performance and identify significant parameters. RESULTS: Physical isolation alone was insufficient to prevent the dispersion of smaller particles. However, a properly installed fan filter unit (FFU) generally enhanced the effectiveness of physical isolation. Ventilation and isolation performance under various conditions were predicted with a mean absolute percentage error of within 13%. The position of the FFU was found to be the most important factor affecting the PIU performance. CONCLUSION: Data-driven modeling based on CFD simulations can expedite the PIU design process by offering predictive capabilities and clarifying important performance factors. Reducing the time required to design a PIU is critical when a rapid response is required.

Multi-zone simulation of outdoor particle penetration and transport in a multi-story building.

In areas with poor ambient air quality, indoor particle concentrations can be significantly affected by particulate matter originating outdoors. The indoor environments of multi-zone and multi-story buildings are affected differently by outdoor particles compared with single-family houses, because of the buildings' more complicated airflow characteristics. The objective of this study is to analyze outdoor particle penetration and transport, and their impact on indoor air, in a multi-zone and multi-story building using a CONTAMW simulation. For the airflow and particle transport analysis, the building leakage, penetration coefficients, and deposition rates were determined by on-site experiments. The results of airflow simulations for cold winters show that outdoor air infiltrates through the lower part of building and exfiltrates from the upper part. The results of the particle simulation also indicated that the airflow characteristics, combined with deposition rates, cause the lower floors of a multi-story building to be exposed to higher fine particle concentrations compared with the upper floors of the building. The study demonstrated that the CONTAMW simulation can be useful in analyzing the impact of outdoor particles on indoor environments through the identification of key particle transport parameters and validated airflow simulations.