The present study aims to examine the effects of medical staff’s turning movements on the number of particles falling onto the patient. A simplified computational fluid dynamics (CFD) model of the operating room was developed and validated based on the published data. An RNG k-ε turbulence model based on the Reynolds-Averaged Navier-Stokes (RANS) equations was used to simulate the airflow, while a discrete phase model was used to simulate the movement of the airborne particles. The medical staff’s turning movements were controlled by integrating a user-defined function (UDF) code and using a dynamic mesh method. Results show that medical staff’s turning movements have a significant influence on the airflow velocity distribution and particle concentration around the patient. A turning movement generally causes more particle deposition; and bending arms also increase the particle depositions when compared to straight arms.

本研究旨在检查医护人员转弯运动对落到患者身上的微粒数量的影响。根据发布的数据，开发并验证了手术室的简化计算流体动力学（CFD）模型。基于雷诺平均Navier-Stokes（RANS）方程的RNGk-ε湍流模型用于模拟气流，而离散相模型用于模拟空气中颗粒的运动。医务人员的转弯动作是通过集成用户定义的功能（UDF）代码并使用动态网格方法来控制的。结果表明，医务人员的转弯动作对患者周围的气流速度分布和颗粒浓度有重大影响。旋转运动通常会导致更多的颗粒沉积。