Indoor Environment Ventilation is critical for keeping air safe in hospitals and offices. When a person sneezes, they release thousands of tiny water drops called aerosols. These drops can carry viruses and bacteria. Large drops fall to the floor quickly because of gravity. However, small drops stay in the air for a long time. This is dangerous because other people can breathe them in. The ventilation system (HVAC) must remove these contaminated drops to stop diseases from spreading. Engineers need to know how air moves to design better rooms. Testing with real viruses is too dangerous. Therefore, we use CFD simulation to model the sneezing process safely on a computer. We use ANSYS Fluent to track every single drop.

In this report, we perform a detailed CFD analysis of aerosol dispersion. We use the Discrete Phase Model (DPM) to see how droplets fly, evaporate, and leave the room. We simulate a hospital room with a patient bed and medical equipment. We also use a special UDF code modeling sneezing profile to make the sneeze velocity realistic. This Indoor Environment Ventilation fluent simulation helps designers position air vents correctly to clean the air fast. For more details on air systems, please explore our HVAC tutorials: https://cfdland.com/product-category/application/hvac-cfd-simulation/

• Reference [1]: Kumar, Sunil, and Maria D. King. “Numerical investigation on indoor environment decontamination after sneezing.” Environmental Research213 (2022): 113665.

Figure 1: 3D Geometry of the hospital room showing the HVAC supply diffuser, exhaust vent, and patient position for the Indoor Environment Ventilation study. [1]

Simulation process: DPM Modeling with UDF Sneeze Profile

This Indoor Environment Ventilation CFD Simulation models a realistic hospital room with a patient bed, chair, and monitor. The room volume is about 16 cubic meters. We generated a high-quality mesh using 833,917 polyhedral cells. Polyhedral cells are excellent because they have many faces and capture complex flow patterns accurately with fewer cells. We refined the mesh near the walls and the patient’s face to catch small droplets. We set up the ventilation system to change the air 6 times per hour (6 ACH), which is standard for hospitals. We also added an air curtain near the door to stop droplets from escaping.

To simulate the sneeze, we used the Discrete Phase Model (DPM) in ANSYS Fluent. This model tracks individual droplets using a Lagrangian approach. We injected 6.3 milligrams of droplets from the patient’s mouth. The droplet sizes followed a Rosin-Rammler distribution. A key part of this simulation was the UDF code modeling sneezing profile. This custom code made the sneeze velocity change over time, starting at zero, hitting a peak of 20 m/s, and stopping after 0.24 seconds. We enabled Unsteady Particle Tracking to follow the drops over real time. We also turned on physical models for Drag Force, Saffman Lift Force, Secondary Breakup (TAB model), and Evaporation. These models ensure the aerosol Dispersion CFD simulation is physically accurate as droplets shrink and move through the air.

Figure 2: Room geometry schematic showing the dimensions and the location of the air curtain inlet near the door.

Figure 3: Transient velocity profile of the sneeze implemented via UDF, showing the rapid increase in speed up to 20 m/s used in the aerosol Dispersion boundary condition. [1]

Post-processing: Aerosol Trajectory and Ventilation Efficiency Analysis

This section analyzes the engineering data to understand how the ventilation removes the sneeze cloud. We interpret the contours and the mass balance table to verify the safety of the HVAC design. First, we analyze the DPM Evaporation Contour in Figure 4. The red and orange dots represent droplets that are evaporating quickly. The data shows that the droplets form a dense cloud above the bed. The ventilation system pushes this cloud toward the exhaust vent. The evaporation model is working correctly because the table below shows that 1.099 mg of mass evaporated. This is about 16.7% of the total sneeze mass. These evaporated droplets become tiny nuclei. These are dangerous because they stay in the air for a long time. The simulation also reveals where the heavy droplets go. The table shows that 3.987 mg of droplets were trapped on the bed. This is a huge amount, about 60.7% of the total mass. This happens because the bed is large and sits directly under the sneeze. This is a critical finding for hospital safety protocols. It proves that cleaning the air is not enough; the staff must also disinfect the bed surfaces immediately after a sneeze event.

Figure 4: DPM evaporation contours showing the dispersion of sneeze droplets colored by evaporation rate (kg/s), revealing the spread of the aerosol cloud.

Figure 5: Velocity streamlines visualizing the complex airflow patterns and recirculation zones created by the ventilation system in the ANSYS Fluent simulation.

Next, we look at the Velocity Streamlines in Figure 5 and Velocity Contours in Figure 6. These images show how the air moves the particles. The streamlines show large circular patterns called vortices in the middle of the room. These vortices mix the aerosols into the room air. The velocity contours show that most of the room has a low air speed between 0.05 and 0.20 m/s. However, there are stagnant zones (dead zones) in the corners where the velocity is near zero. Droplets that enter these dead zones get trapped and do not leave. The most important number for the HVAC designer is the removal rate. The table shows that 2.877 mg of droplets escaped through the exhaust. This means the ventilation system successfully removed 43.8% of the contaminated mass. This is a strong engineering achievement. It proves that the position of the exhaust vent is effective. The Indoor Environment Ventilation CFD Simulation confirms that a standard 6 ACH rate works, but the design could be improved by moving the air supply to eliminate the dead zones in the corners.

Figure 6: Velocity contours on vertical and horizontal planes showing the distribution of air speed and identifying stagnant zones in the room.