CFD-Based Lagrangian Multiphase Analysis of Particulate Matter Transport in an Operating Room Environment

Maintaining air quality in operating rooms is critical for infection control and patient safety. Particulate matter, originating from surgical instruments, personnel, and external sources, is influenced by airflow patterns and ventilation efficiency. This study employs Computational Fluid Dynamics (CFD) simulations using Simcenter STAR-CCM+ 2410 to analyze airflow and particulate behavior in a surgical-grade operating room. A steady-state solver with the k–ε turbulence model was used to replicate airflow, while the Lagrangian multiphase method simulated particle trajectories (0.5 µm, 1 µm, and 5 µm). The simulation results demonstrated close agreement with the experimental data, with average errors of 17.3%, 17.7%, and 39.7% for 0.5 µm, 1 µm, and 5 µm particles, respectively. These error margins are considered acceptable given the device’s 10% measurement sensitivity and the observed experimental asymmetry—attributable to equipment placement—which resulted in variations of 17.2%, 18.0%, and 26.5% at corresponding symmetric points. Collectively, these findings support the validity of the simulation model in accurately predicting particulate transport and deposition within the operating room environment. Findings confirm that optimizing airflow can achieve ISO Class 7 cleanroom standards and highlight the potential for future studies incorporating dynamic elements, such as personnel movement and equipment placement, to further improve contamination control in critical environments.