Ventilation in Laboratories

Using CFD to Optimize Air-Change-Driven Labs

Labs use significant amounts of energy due to their makeup air requirements driven by the air changes needed to protect lab personnel from exposure to airborne hazards. There is currently a big push in the industry to improve energy efficiency and decarbonize lab facilities. One way to do this is to scrutinize air change rate requirements by relying less on established rules of thumb and more on analysis based on the unique needs of the facility.

One such analysis tool is computational fluid dynamics, or CFD, which can be used to assess how many air changes are needed to meet air quality goals of specific types of labs.

When assessing air quality in labs with fume hoods, it is useful to distinguish between primary and secondary containment. Primary containment deals with pollutants generated within the fume hood, while secondary containment deals with pollutants generated outside of a fume hood, such as an accidental spill.

Primary containment depends strongly on adequate face velocity across the sash opening of a fume hood (80–100 fpm according to ANSI/ASSP Standard Z9.5-2022, Laboratory Ventilation). Secondary containment, however, is more strongly tied to room air motion. All this assumes proper diffuser selection and placement since high-velocity air from a diffuser placed too close to a fume hood sash opening can compromise primary containment.

We created a CFD model of a large teaching lab (figure 1) to explore how air change rate affects primary and secondary containment. The lab contains 18 VAV fume hoods, has 19 occupants and is conditioned with 2-by-4-foot laminar flow diffusers in the ceiling.

Figure 1. Teaching lab CFD model

The lab is negatively pressurized with a flow offset of 10% of the maximum exhaust air volume that is distributed across the gaps in the doors (100 cfm per door) and the two transfer grilles above the doors. We can simulate three air change rate scenarios by closing specific fume hoods so that they are operating at their minimum airflow, while assuming other fume hoods are fully open. All other simulation inputs are summarized in table 1.

Table 1. Simulation Inputs for the Studied Scenarios

To quantify primary and secondary containment, two neutrally buoyant pollutants are added to the model and are active in all three scenarios: one inside selected fume hoods (4 L/min, equivalent to boiling) and one on selected countertops (1 L/min, equivalent to a liquid spill).

The diffuser airflow patterns (figure 2) demonstrate a typical nonaspirating airflow that accelerates slightly as the airflow reaches the floor due to the temperature difference between the cold supply air and the warm room air.

A close-up view of the air going into a fume hood is shown in figure 3, highlighting the complex airflow pattern that is formed around the user of the fume hood. The user obstructs the air path, and a nonuniform velocity is created through the sash opening before being channeled into the interior and toward the multiple exhaust points.

Figure 3. Close-up view of airflow through fume hood sash opening

Concentration plots are shown in figure 4 for the fume-hood-generated pollutant (primary containment) and in figure 5 for the benchtop-generated pollutant (secondary containment). The concentrations are essentially zero for all airflows in figure 5, which means that primary containment is maintained and that the supply air does not disrupt fume hood operation.

Figure 4. Primary containment – concentration of pollutants 43 inches above the floor

Figure 5. Secondary containment – concentration of pollutants 43 inches above the floor

For secondary containment, the situation is quite different, and the sources of the pollutants and how they spread are clearly visible in figure 5. The concentrations decrease with increasing air change rate due to dilution, and the overall spread of these pollutants is smaller at the highest air change rate.

Key takeaways:

• Good diffuser layout (and airflow pattern) ensures the proper operation of fume hoods and full primary containment.
• Air changes in the space don’t affect primary containment but have a positive effect on secondary containment.
• The airflow pattern around the fume hood is complex due to the blockage effect of the user standing in front of it.

To learn more about Predict, or if you come across a project you believe is well suited to a CFD analysis, reach out to our team at info@PredictCFD.com.