# Modeling Jet Fans, Part 3 (now replaced by new post): Applications

Posted: April 12th, 2015 in News

This post has been replaced by an updated post.

In this post we use FDS and the Dynamic Smagorinsky turbulent viscosity model to simulate both a full-scale jet fan experiment and clearing of smoke from a car park garage. The choice of the dynamic Smagorinsky model is based on the discussions in first two posts on modeling jet fans in which dynamic Smagorinsky viscosity enabled a reasonable solution with a relatively coarse mesh (Part 1: Background and Convergence Study and Part 2: An Engineering Approach). The focus will be on the full scale jet fan experiments described by Giesen et al. (2011). Videos showing the calculations can be found here, Jet Fan Videos.

### Caution:

This post uses the Dynamic Smagorinsky turbulent viscosity. This approach is not recommended since Dynamic Smagorinsky does not perform well for coarse simulations of fire (based on discussions with NIST).

## Geisen et al. Jet Fan Experiments

Geisen et al. (2011) describe jet fan experiments performed in a 34 x 32 x 6.5 m hall using a Novenco fan (diameter 290 mm, length 2.6 m, exhaust flow 1.0 m^3/s, exhaust velocity 18 m/s, and capacity 21 N). Air velocity measurements were made at distances of 0.5, 1, 2, 4, 8, 12 and 16 m from the exhaust. For the free jet the fan center was positioned 2.5 m above the floor.

The velocity profile at the exhaust from the actual fan is not uniform. A lower bound velocity of 15.1 m/s is obtained using the diameter and flow while a max centerline value of 18.9 m/s was measured in the experiments. In all the following calculations the fan outlet was assumed to be a 250 x 250 mm square with velocities of 16 m/s (1 m^3/s) or 18 m/s (1.125 m^3/s) as indicated.

The jet fan experiment model is shown below. The jet fan is simulated as an HVAC duct, so that smoke drawn into the inlet is conserved and blown out the outlet. Two mesh resolutions were used, with mesh sizes of 62.5 mm and 125 mm around the fan. The upstream boundary was OPEN while the downstream boundary has a 2.3 m wall a distance of 24 m from the jet fan outlet.

Velocity contours for the 125 mm case with an exit velocity of 16 m/s are shown in Figure 2.

The centerline velocity decay and the flow volumes are compared to experimental data in Figures 3 and 4. The Giesen experimental data was measured using the Novenco fan. The Kummel data is that used for validation of FDS. Results are presented for both the default Deardorff turbulent viscosity and for Dynamic Smagorinsky. The Deardorff results show less centerline velocity decay than the Dynamic Smagorinsky cases. The centerline velocity decay is a measure of the turbulent mixing and transfer of momentum to surrounding fluid. Figure 4 clearly shows the the Dynamic Smagorinsky model does a better job of correlating with measured flow volumes than the Deardorff model. For simulation of jet fan ventilation, the ability to simulate the volume flow is critical so this seems to be the preferred approach.

## Application to Parking Garage

The purpose of these posts has been to evaluate the applicability of FDS for jet fan simulations such as a parking garage. Based on what we have learned, we will use a relatively coarse mesh with the Dynamic Smagorinsky turbulent viscosity model. Figure 5 shows the design. This is a generic model with four fans with flows of 1 m^3/s (exhaust velocity of 16 m/s). The fans are arranged in a linear flow pattern with an 8 degree deflector angle down from the ceiling. An exhaust vent operates continuously at 6 m^3/s and there is one open supply vent. The total volume of the car park is 5400 m^3, for an air supply of 6 m^3/s the replacement time is 900 s.

The mesh size was 125 mm surrounding the fans and 250 mm away from the fans. Simple models of beams, columns, and cars were included.

The velocity contours of air flow are shown in Figure 7. The velocity vectors are drawn at a height of 1 m above the floor and the contours are drawn through vertical planes that intersect the jet fans. The contours show the flow from the fans. The =vectors show the complex turbulence induced in the flow around the cars, columns, and beams in the car park.

To visualize how smoke could be cleared from the car park, in the FDS simulation smoke was initially uniformly distributed throughout the interior. The external supply provided clear air, so as the solution proceeded, the air gradually replaced the smoke. Doing this can show approximately how the visibility in the car park will change with time as smoke is cleared. Figure 8 shows an interior view at around 1000 s. At this time the visibility ranges from about 15 to 30 m. By the end of the simulation visibility is about 30 m within the entire car park. Note that the smoke was not based on a true fire simulation, so the visibility numbers are only for comparison.

Figure 9 shows a plot of velocity vectors and smoke. This gives another view of how the flow eddies around the cars and columns.

## Summary

In a jet fan, turbulent mixing of the exhaust flow transfers momentum to the surrounding air.

• The preferred approach is to use a high resolution mesh and resolve the centerline velocity decay using the default FDS dynamic viscosity model (Deardorff).
• The Dynamic Smagorinsky model enhances turbulence and makes it possible to simulate jet fans with a relatively coarse mesh (h/dx=4). However, experience shows this turbulence model does not perform as well as the default Deardorff model for a broad range of problems. Specifically, using Dynamic Smagorinsky with a coarse mesh for flame calculations can lead to unrealistic flame behavior.
• Free jet simulations using the Dynamic Smagorinsky model show reasonable correlation with commercial jet fan experiments for the specific application described in this post.
• An example simulation showed how a car park could be modeled with this approach.

It is critical that the user verify that the model being used performs adequately for their application.

## Acknowledgements

All calculations were performed using the FDS and Smokeview software. PyroSim was used to create and run the FDS models.

## References

Awbi, Hazim B., (2003). Ventilation of Buildings, Second edition, Spon Press, 2003.

Giesen, B.J.M. v.d., Penders, S.H.A. , Loomans, M.G.L.C., Rutten, P.G.S., & Hensen, J.L.M. (2011).  “Modelling and simulation of a jet fan for controlled air flow in large enclosures,” Environmental Modelling and Software, 26(2), 191-200.

## Author

Daniel Swenson, Member Technical Staff, Thunderhead Engineering. swenson@thunderheadeng.com. The author would be glad to hear comments on alternative approaches to model jet fans.