Modeling Jet Fans Using FDS - Part 1

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Posted: February 17th, 2015

This post discusses modeling jet fans using FDS/PyroSim, with the eventual goal of modelingparking garages. It starts with some background information that was useful to me in helping meunderstand the problem. In preparation for a parking garage simulation, we first focus on a freejet, comparing the results of a mesh convergence study with the experimentally derivedcorrelations for centerline velocity decay. This and the future garage simulation should help youdecide whether PyroSim is applicable to your jet fan application.

First the basics. FDS (the Fire Dynamics Simulator developed at NIST) solves the Navier-Stokesequations using the Large Eddy Simulation (LES) method. In the LES approach, eddies on thescale of the cell size are resolved and the effect of smaller eddies are approximated. This meansthat the solution is transient and will vary with time at any point. This compares to the ReynoldsAveraged Navier-Stokes (RANS) approach which provides a time averaged solution.

As will be demonstrated, the mesh size required to accurately match the experimental data for afree jet from a duct are smaller than can be realistically incorporated in a typical designapplication, such as a parking garage. The question then becomes, Are there approaches thatallow us to reasonably simulate a jet fan in a design calculation, while still being able to solve theproblem in realistic time frames? In the next post we will attempt to provide some guidance tothis issue.

In this post we simulate a free air jet with increasing mesh resolution to validate that the FDSsolution does converge to the experimental data as mesh is refined.

Jet Fan BackgroundSeveral papers have helped me begin to understand some of the issues in modeling jet fans. I amnot an expert in jet fans, and this is far from an exhaustive list, but it at least provides a startingpoint for our discussion:

Modelling and simulation of a jet fan for controlled air flow in large enclosures, (Giesen etal., 2011) describes both experiments and a RANS computational fluid dynamics (CFD)simulation. The goal is to model the experiments described in this paper.Hazim Awbis book on Ventilation of Buildings (Awbi, 2003) is one source for abackground discussion of experimental data and equations that fit the data.Two papers, one by Joo Viegas (Viegas, 2010) and Joo Aveiro & Joo Viegas (Aveiro andViegas, 2010) demonstrate detailed simulation of ventilation for smoke control inunderground car parks using FDS.The NIST verification manual for FDS includes a jet fan calculation and referencescorrelations with experimental data (McGrattan, et al., 2013, Section 3.4 Jet CenterlineVelocity Decay).

A typical jet fan installation in a parking facility is shown. Brochures from manufacturers, such asthe FANTECH catalog Impulse Ventilation for Car Parks, provide possible arrangements of arraysof fans in application.

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Modeling Jet Fans using FDS - Part 1: Background and Convergence ... http://www.thunderheadeng.com/2015/02/modeling-jet-fans-part-1/

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Typical jet fan installation (Giesen et al.,2011)

A free air jet flows into an air space where there are no solid boundaries to influence the flowpattern. As described by Awbi (2003) the flow from a free circular jet can be divided into tworegions:

Schematic of a free circular jet (Awbi,2003)

Potential core region is the region immediately downstream of the supply opening wheremixing of the jet fluid with the surrounding fluid is not complete. The length of the core usually extends to 510 equivalent opening diameters. In this region the centerline velocityis constant and equal to the supply velocity.

Axisymmetric decay region is a region dominated by a highly turbulent flow generated byviscous shear at the edge of the shear layer. For three-dimensional jets this is usuallyreferred to as the fully developed flow region where the spread angle of the jet is aconstant whose value depends on the geometry of the opening. It is the predominant regionfor a jet discharging from a low aspect ratio (square or circular) opening where it extends toabout 100 equivalent diameters. Centerline velocity decreases inversely with the distancefrom the opening.

As described by Awbi (2003), Baturin (1972) provides the following fit to experimental data:

where: um is the centerline velocity, u0 is the supply velocity, x is distance from the supply, a is a

constant (0.076 to 0.080 for cylindrical tubes), and d0 is the supply diameter.

Another representation of jet fan experimental data is provided by Kmmel (2007) and isdescribed in the FDS Verification Guide (McGrattan, et al., 2013). For a square duct:

where: x0 is the length of the potential core, h is the side length of the square duct, and m is a

constant that varies between 0.12 and 0.20.

The Baturin and Kmmel equations are displayed below for a square 0.25 m duct (equivalentdiameter 0.2821 m) with an initial air velocity of 18 m/s (= 59.1 ft/s = 64.8 km/hr = 40.2miles/hr), the outlet velocity of the jet fan in the Giesen et al., 2011 paper. The bounds ofthe Kmmel equation show a significant variation in the length of the potential core region. TheBaturin correlation predicts centerline velocities that lie between the bounds of the Kmmelpredictions. When comparing the PyroSim/FDS results with the correlations, the mean values ofthe Baturin and Kmmel equation parameters are used.


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Analytic free jet centerline velocities.

FDS Simulation of Free JetBefore proceeding to simulate the parking garage experiment, we simulated a free jet usingvarying mesh refinements. The model consisted of a 0.25 x 0.25 m vent with a supply velocity of18 m/s, similar to the jet fan dimensions and performance that was tested by Giesen et al.(2011).

Figure 4 shows the free jet model. Five meshes were used, with the boundaries of each meshbeing an X length of 2.5 m and a height and width of 1.25 m. Only a single mesh is used near thevent, but four meshes are used away from the vent, since the diameter of the jet increases withdistance from the supply vent.

The free jet model. The total X length is 5 m.

The supply vent was square with each side length h=0.25 mand with a supply velocity of 18 m/s. The cell size (x) wasequal in X, Y, and Z and was varied as a fraction of the ventside dimension, as shown in the table. The number of cells inthe models ranged from 10E3 to 10E6.


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Results of FDS Free Jet SimulationsBecause FDS is a Large Eddy Simulation (LES) solution, the results vary with time. All modelswere run for 10 sec. The initial transient is complete by 2 sec and the primary turbulencefrequencies are sufficiently high that averaging the results from 2 to 10 sec gives a value thatrepresents a steady state measurement. The previous figure shows the locations of the Y=0 andX=4 m planes on which velocity contours will be presented.

To first visualize the effect of mesh size on the solution, we present two pairs of velocity contourson the Y=0 and X=4 m planes at 5 sec. These provide both a sense of how the mesh capturesturbulence and a measure of the size of the downstream jet. Clearly, the fine mesh shows a muchmore realistic development of the shear layer, while the coarse mesh result shows minimalturbulence.

Free jet velocity contours. The left column shows velocity on the Y = 0 plane (0

Calculated free jet centerline velocities.

SummaryIf a sufficiently refined mesh is used, FDS can accurately simulate a free jet. If the meshrefinement is too coarse, the solution will not capture the turbulence in the shear layer thatentrains the surrounding fluid and the predicted centerline velocity will not decay as shown beexperiment.

This is similar to the conclusion in the FDS Verification Manual, where a mesh of 1/16 the ventside was needed to obtain an reasonably accurate solution. The FDS Verification Manual free jettest problem has a Reynolds number of 1E5 (square duct side 0.8 m and a fluid velocity of 2 m/s).The parameters of the free jet in this post are more challenging and were chosen to approximate acommercial jet fan used for parking garages with a Reynolds number of 2.7E5 (square duct side0.25 m and a fluid velocity of 18 m/s). So the duct size is significantly smaller and the fluidvelocity is significantly higher.

In the next jet fan post we will look at how well PyroSim/FDS can simulate a parking garage jetfan and explore ways to speed the solution while still obtaining reasonable results.

Please send comments or suggestions on how to improve this post [email protected].

ReferencesAveiro, Joo L. & Viegas, Joo C. (2010). Smoke Control in an Underground Car Park withImpulse Ventilation, V European Conference on Computational Fluid Dynamics, ECCOMAS CFD2010, J. C. F. Pereira and A. Sequeira (Eds), Lisbon, Portugal, 1417 June 2010.

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

Baturin, V. V., (1972). Fundamentals of Industrial Ventilation, Pergamon, Oxford.

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.

Kmmel, (2007). Technische strmungsmechanik. Technical report, B.G. Teubner, 3. Auflage,2007. 25

McGrattan, K., McDermott, R., Weinschenk, C., Overholt, K., Hostikka, S., Floyd, J., (2013). FireDynamics Simulator Technical Reference Guide, Volume 2: Verification, Sixth Edition, NIST SpecialPublication 1018, National Institute of Standards and Technology.

Viegas, Joo Carlos (2010). The use of impulse ventilation for smoke control in underground carparks, Tunnelling and Underground Space Technology, 25 (2010) 4253.


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Back to PyroSim Home Page

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Modeling Jet Fans Using FDS - Part 1

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