Case Study - Simulation of Cleanroom Ventilation
This case study shows how Aerotak™ is able to simulate and map the airflow within a cleanroom estimating exchange rates and residence times of the air.
Accurate prediction and visualization of maximum residence times and regions of minimum air exchange within the cleanroom. It is required of the ventilation system, that all air should be exchanged after a maximum of 1000 seconds.
For simulating the airflow within the cleanroom, a full-scale setup composed of three detached rooms are drawn up with a ceiling height of 2.5 meters. Geometrically simplified objects such as doors, closets, tables, and vents are added to the cleanroom. The cleanroom is shown in Figure 1 on the right. Each ceiling vent (marked in red) are given a volume flow rate of 400 cubic meters per hour enabling a nominal air exchange rate of 17 times per hour. A slight swirl is imposed on the inlet flow to simulate the real flow behavior of such ventilation system.
A k-omega SST turbulence model is adopted for capturing the mixing of fresh and old air. Using a steady-state flow assumption and 2.9 million mesh cells, a fully developed flow is obtained for analysis within a few hours of simulation time.
The results of the simulation are presented below. For the purpose of investigating regions of limited air exchange and high residence times, a passive scalar along with massless particles are tracked through the velocity field. Maximum velocities of 2.3 m/s are observed near the vents as indicated in red in Figure 2, where the velocity field is visualized using a line integral convolution technique.
Passive scalar concentration is visualized in animation 1, using a scalar isosurface of a passive scalar value of 0.95. Regions of the cleanroom not colored contain more the 95% clean air. Blue color indicates 0% ventilated air. Figure 3 shows the remainder of the isosurface after 1000 seconds of ventilation, for which not all of the air has been ventilated. Despite a safety factor of 4.5 in sizing of volume flow rate of the vents, the system is still not able to comply with the defined requirements. Hence, efforts to improve the layout of the cleanroom shuld be taken based on the unique insights obtained from the CFD simulation.
Tracking of massless particles is a powerful tool for prediction of complex flow behavior from the steady-state simulation. Visualizations below are shown for the second largest room, with particles colored by residence time.
Ventilation of a cleanroom containing physical objects has been simulated by Aerotak™ for mapping of complex airflow patterns and identification of limited air exchange regions. The setup and simulation technique can be applied for improved ventilation effectiveness as well as evaluation of thermal comfort for occupants and increased energy efficient building layout and design. The low computational cost of the setup allows for the CFD tool to be applied in both early and late stages of the design phase, for ensuring robustness of cleanroom operation.