A case study illustrating the use of airflow modeling software in the design of a pharmaceutical cleanroom.

THE CASE STUDY SHOWN HERE was carried out by Tanvec and illustrates the use of FLOVENT® airflow modeling software to investigate and optimize the design of a complex pharmaceutical cleanroom. The end user was seeking to optimize the design of a cleanroom containing vial filling machines, lyophiliser loading, and automated transport systems. The pharmaceutical regulatory requirements demand the following cleanliness classes for different parts of the operation (see Table).

The main issue investigated was the size of unidirectional airflow clean zone required to protect exposed product as it is loaded from the transporter into the lyophiliser. In addition, it was necessary to identify an appropriate way to segregate this critical zone from the surrounding cleanroom area with non-unidirectional flow. The investigation was carried out in two distinct stages. The first stage was a broad investigation of basic room airflow configuration options. The second stage involved investigating detailed areas of airflow over critical product and material transfer locations where contamination control and regulatory compliance was essential. The two stage approach was adopted because it is difficult to predict all the issues and problems that will arise until some overall modeling has been developed, the solution run, and the data evaluated. This approach also reveals another advantage of airflow modeling — it is possible and often advantageous to look at a simplified representation of the macroscopic room level issues, as well as the more detailed flows around specific areas of interest. Conventional "Rule of Thumb" analysis of a conceptual design capable of achieving the required cleanliness classes above suggested that the corridor should have a filtered ceiling to achieve unidirectional airflow. The use of airflow modeling, however, allowed investigation into alternative methods of introducing air into the space.

Figure 1 shows the airflow modeled with a filtered ceiling across the full width of the corridor. The visualization technique shown is akin to a smoke test on a physical mock-up, but with three advantages. First, the computational smoke can be given a lifetime so that the room does not fill-up with smoke as it would do on a physical model. Second, the visualization can be colored according to parameters such as air speed, temperature, contamination level, etc. In the figures shown, the smoke is actually colored accordingly to y- (vertical component) velocity, with the color scale indicating downward direction velocities of >1m/s in blue and horizontal or upward flow >0m/s in red.

Finally, this type of visualization can be done without the need for a physical mock-up of the space. This means that it is inexpensive and quick to do even at the conceptual stage of the design. With this design, a small recirculation region of air just in from of the top half of the lyophiliser was noticed. This was caused by air hitting the top of the lyophiliser and "bouncing" forming this vortex.