gas dispersion

7/27/2019 gas dispersion

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INTRODUCTION

The Fire Dynamics Simulator FDS) computer model ha s been developed y the NationalInstitute of Standards nd Technology NIS'f). Although FDS was developed rimarilyfor simulation of fire phenomena l), (2), (3), (4), and (5), it is a more generalcomputational luid dynamics computer code suitable or application n a much widerrange of fluid dynamics problems. The FDS model is u nique n that it is liee to thepublic. and t enjoys ontinual unding support nd ech nical volution hrough he ef-fortsof NIST and other researchers. In recent years the FDS model has increased ourunderstanding f complex fire phenomena nd has even been used o model the early iredevelopment n the 911 ncident 6).

Although F'DS was developed or predicting ire dynamics, t has wider applicability. Ofspecific mportance with respect o this paper, FDS has been used o model dispersion ofgases nside and outside of b uildings. Mniszewski and Pape 7) have used FDS fb r puredispersion nalyses ithout combustion nd compared redicted esults o experimentsand analytical predictions. FDS has also been used or indoor air quality calculations byMusser, et al. (8) In the area of Computational Wind lrngineering, Rehm, McGrattan,and Baum, have ested DS 9) ( 0) .

The authors use the l.'DS model extensively or applications such as these. I'he F'DSmodel has been ested against experimental data fbr a variety of situations, however hepreponderance f such validation ests have becn conccrned with the prcdiction clf firceffects. This paper s concerned ith prediction of gas dispersion sing FDS. Severalexamples of dispersion modeling using FDS are presented. With proper validation, hismodeling technique should be of value in many gas industry applications, particularlythose nvolving public salbty tudies.

As FDS is free to the public, continually being improved and updated and user-lriendly,this sophisticated nd powerful computational luid dynamics modeling ool is availablefbr anyone who takes he time to leam t. in contr ast o other CIFDmodels which may bemore costly o learn and use.

DESCRIPTION OF THE FDS MODEL

FDS is a computational luid dynamics CFD) model developed t the National nstituteof Standards nd Technology NIST). Computational 'luiddynamics s the mathematicalsolution of the equations hat describe luid motion. [rDS stands or Fire Dynamics

Simulator. Although the FDS code has been developed or prediction of fire behavior, tis applicable or general fluid dynamics computations. uch as wind f'low aroundobstacles. he FDS code s a Navier-Stokes quation olver br low Mach numbers. TheFDS equations describe he motion of a fluid, such as air, and include conservation fmass, momentum, and energy relations. Analyses presented in this paper wereaccomplished sing Versions .0 hrough 4.0 of the code.


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The FDS computer code s described n detail in a number of references l), (2), (3), (4)and (5). As described n these documents, FDS solves he fluid dynamics equations orlow Mach number lows. The governing equations are he equations or conservation fmass, momentum, and energy. where energy conservation s included n the equation orflow divergence. The simplified equations hat are solved numerically are given below:

Mass:

Momentum:

c ) o: * Vr1 |

. p u 0

+ v V - ( p - p , ) g = f + V

( 1 )

, + + ( u ' V ) u

[)iversence Constraint:

t / / \

V.u=-1 . t .kvT '*v. Ilcn ,dT 'oD,yy,y. t ! , ro ' l* t : -L l+ (3)p ' , r \ , ) \ r * ' , T P, , ) t l r

where p is mass ensity, , is the ambient ensity, is time. u is velocity bold ndicatesvector quantities), I is the perturbation pressure. ,, is the background pressure, n isspecific heat. T is temperature. is thermal conductivity. D; is diffusivity or specie , Y1is the mass fraction for specie I, g is gravitational acceleration, is the body force(excluding ravity),and r is the shear tress. "o r he ow Mach Numbcr brm. prcssure swritten as the average background pressure added o the hydrodynamic pressure and aflow-induced perturbation pressure, V. The cquation of state n the model is the idealgas aw.

The FDS model has two solution options for capturing turbulence. These are directnumerical imulation DNS) and arge eddy simulation LES). All simulations resentedin this report used he LIJS approach. ,argc cddy simulation allows direct numericalsolution of the larger scale luid motion (including arge urbulent eddies) bu t greatlyreduces he required computational ime by calculating he sub-grid scale viscosity usingan eddy viscosity based in FDS) on th e Smagorinsky iscosity model. (ll) (12) Theability to use larger grid elements and account fbr the sub-grid mixing using th eSmagorinsky viscosity allows solution of complex three-dimensional roblems inpractical computational imes and memory requirements. arge eddy simulation s nowan option n many CFD codes, as well as FDS.

Diflusion s treated imilarly br all ga s species n the model. where diffusioncoefficientsare he same. This ends o pu t nto question he usefulness f the model n quiescentapplications. However, t is reassuring hat in most fuel-gas eakage cenarios, he masstransfer of the subject gas ends o be dominated by the bulk movement rom the gasrelease, urbulentmixing and buoyancy ff'ects, ot diffusion. Thus. t is expected ha t nmost cases. he physics f the model will approximate he real world reasonably ell.

(2)


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The primary imitation of the code s its validity for low Mach numbers. This requiresthat he maximum flow velocities be well below the speed of sound n the medium beinganalyzed. When considering he fact that he speed f sound n air at ambient conditionsis about 340 m/s (1100 ils). his s not really a practical estriction or a wide variety ofproblems, particularly nvolving lire development, ispersion f gases nd wind flowaround structures. For dispersion nalyses, he ow Mach number estriction may besignificant f it is necessary o model he details f a high velocity gas et very ncar aleak, but generally he detailed eak low right at the source s not mportant s ong as heoverall eak flow rate s accounted or.

'l'he geometries l-structures n IrDS simulations must bc represented s composites adeof rectangular olidblocks. This s sometimes isted s a linritation f the FDS codebecause urved surfaces re approximated y a stair-step rrangement. However, whenthis restriction s balanced gainst he simplifications and consequent fficiency hatresults. he block structure s well worth t.

F'igures md 2 are examples f results rom IiDS analyses 1'lire (what FDS wasoriginal designed or). Figure I is the simple burning of an itcm under a hood, showingthc flow of hot gases sing raccr particlcs nd hcating of a ncarby urface. Figurc 2shows a kitchen ange rre n a townhouse. Flame plumes are shown spreading hroughthe rooms. Many options are available o allow for displaying quite a number ofparameters, ncluding emperature, moke density, heat elease, as concentrations, tc.

FDS VALIDATION

A great deal of effort has been expended y NIST in the last several ears n thevalidation of the FDS model nvolving fire phenomena. The currcnt edition of the FDS'l'cchnicalRel-crencc uidc 4) provides long ist ref'ercnccs iom many sourccs itingvalidation ases nd application echniques. Much of the validation work has beenconcemed with fire phenomena. Mniszewski and Pape 7) have ested F'DS or puredispersion nalyses without combustion and compared redicted esults o experimentsand analltical predictions. Musser. t al. (8 ) have used FDS br indoor ai r qualitycalculations. Rehm, McGrattan, nd Baum, have ested DS (9 ) ( 0) lbr prediction fwind flow around buildings.

The FDS version lJser 's iuidc (13) states hat Although rDSwas designedspecifically br frre simulations. t can be used or o ther luid flow simulations ha t do notinclude ire or heat addition of aury ind". This guide also presents n example of arelease f helium nto a compartment illed with air. Dr. McGratten of NIST is the mainarchitect f th e FDS software. Ie has encouraged hc authors n the use of thc model ordispersion pplications, nd has provided useful guidance n how to implement tproperly.


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Figure l. Idealized Fire Experiment Simulation.

ffiffir,Y.f*{ffi

wry*RFigure 2. Example of FDS or Fire Development nalysis.

Suggested Additional Experimental Validations. Although there has been sometesting of the FDS computer code or dispersion nalysis, or gas ndustry applications twould be desirable o conduct number of highly nstrumented xperimental alidationsinvolving some ypical natural as eak scenarios. One suggested pproachmightinclude:

l. Indoor/ ypical esidential ingle-family ome/ 2 story with basement leakscenario nvolving a failed lexible connector t the kitchen ange


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2. Indoor commercial acility - leak scenario nvolving a ruptured %" gas pipe3. Outdoor Scenario - leak scenarios nvolving underground ipe rupture atvarious low rates

While there are safety concerns n using undiluted natural gas or such esting, he use ofdiluted gas esting or use of an appropriate imulant gas may help qualm public conceman d allow testing n real buildings. With natural as source oncentrations ept belowthe LEL at perhaps 50% LEL for safety, he mass ransfer phenomena hould bereasonably imilar to sources t undiluted concentrations. f a simulant gas were used,molecular weight and diffusion characteristics ould have o be considered nd properscaling f results valuated. A reasonable rrayof gas sensors ould be neccssarythroughout ach esting olume. Infiltration would need o be considered n indoortesting o some degree. Such additional esting, with corresponding alidation analysesusing FDS, would increase onf.idence n the predictions of FDS for such cases.

Propane eak scenarios an be considered imilarly.

EXAMPLES OF DISPERSION ANALYSES USING FDS

Several xamples l gas dispersion imulations ere discussed reviously y Mniszewskiand Pape n (7). 'I'hecases iscussed t that ime (not repeated ere) nclude hefollowing:

o Comparison ith One Room Model Perl-ect ixing Theory

Perfbct mixing theory predictions were compared o FDS simulation esults brdispersion f gas nside a single oom. Calculations ere completed br dispersionwithin thc room with and without oom fbrced ventilation. Whcreas erl-cct ixingtheory s based n formation f two distinct ayers. DS predicts more gradualtransition rom the concentrations ithin the upper spaces f the room and he lowerspaces.

o Comparison ith' l 'heory br Vapor Dispersion n a Wind

Predictions f dispersion n an imposed wind o1'vapors eaking iom a component na chemical process lant (e.g. a valve or pump) were compared o concentrationprofilesproduced iom an dealized oint source f vapors. or which here wa s an

analytic olution. Except near o the source, where geometry ffbctar e significant.the FDS results compared uite good o the deal point source solution.

o Comparison ith Experiment br Propane Migration n a Room

FDS was used o simulate an experiment br which there appeared o be a gooddescription of the setup and results n a paper n the iterature. The experimentinvolveddispersion f a 50:50 mixture of propane nd carbon ioxide n a room with

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air infiltration. FDS over-predicted he experimental as concentrations, hich mayhave esulted rom an oversimplification of the distribution of air infiltration .

Dispersion f Vapors iom a Gasoline Spill in a Room

Several experiments were performed nside an enclosure imulating a closed garage witha water heater n a corner. In the center of the floor, there was a gasoline spill or a releaseof a simulant carbon ioxide). Initially. he enclosure as kept closed. ither with orwithout oom orced ventilation. t six minutes nto the experiment, brced ventilationwas ntroduced hrough a slot at f'loor evel at the opposite end of the enclosure,simulating cracking open a garage oor with ou tside wind. Figure 3 shows heconcentrations f gasoline apors efore and after he outside wind was ntroducedthrough he slot. The FDS predictions f time lbr flammable oncentrations o reach hewater heater ombustion hamber matched he time to explosion n the gasoline estsreasonably ell.

. , i

I

Figure 3. Gasoline Spill in Room With Water Heater.

Natural Gas Dispersion n a Pizza Restaurant

'l'his example nvolves an underground atural gas eak caused y extemal orces,adjacent o an old commercial building with a granite block foundation. Iterativemodeling was utilized o establish he rate of leakage nto the basemenl. sing he knowntiming between eak nitiation and hc explosion. nd hc probable gnition source(furnace pilot) location as constraints. Figure 4 is a ver tical slice of gas concentrationsfor one eak rate scenario howing concentration istribution of natural gas hroughoutthe building. l'he ga s concentration s shown o be highest ear he source f the outsideleak n the basement, hile open stairway oors allow ga s o rise and ill grade evelareas.


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Figure 4. Gas Dispersion n a Pizza Restaurant.

Gas Plumes rom Undereround eakage

'fhis example nvolves he possible se of modeling o estimate he abovc ground gasplume available iom a variety ol-undcrground eak sizes an d wind conditions. igure 5shows an example of results rom a 1270 CFtl natural gas eak distributed over a squaremeter, with a wind speed f 2.24 mp h (0.1 m/s). Such esults may allow a field engineerto estimate eakage ate below by simply measuring ome points within the ga s plumeand wind conditions.

Natural Gas Versus Propane Dispersion n a Shipping/Receiving rea

An explosion ccurrcd nside he shipping/rcceiving rea of a fbod processing acility.The shipping/receiving rca wa s covered y a peaked oof, bu t t was otherwise pen othe outdoors and wind penetration. Figure 6 shows he facility with the white roofed atthe middle covering he shipping/rece iving rea. Figure 7 shows he ayout of the facilitywith the roof removed. T'he hipping/receiving re ahad wo lorklift trucks n the rear eftcorner and he propane ank on one was being changed. One possible ause cenarioinvolved an overfilled propane ank rupturing. A second cause scenario hat wasevaluated nvolved a natural gas eak emanating rom a floor crack at the right-hand sideof th e shipping/receiving rea, ehind a plywood partition. Figure 8 shows he results orthe natural gas case, and Figure 9 shows he results or thc propanc ank rupturc. Clearly,the propane ank rupture was capable of producing a large flammable cloud whereas henatural gas eak produced oncentrations n the space well below the lower explosionlimit.


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Figure 5. Dispersion of Gas From An Underground Leak.

Figure 6. Food Processing acility.


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Figure 7. Facility Layout.

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Figure 8. Natural Gas Leak Scenario.

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Figure 9. Propane Tank Rupture Scenario.

Odorant Transport

'fhe final case o be discusscd was done o evaluate he propensity or odorant o separatefrom natural as during dispersion n air. A simple cubical enclosure as considered.small sectit-rn f the 'loor was given a100o/o oncentration f methane, ut no lbrced lowinto the enclosure. Odorant was applied o the methane t concentrations p to l% byvolume. Irigure 0 shows he result br this case, with the methane as ising to theceiling as a plume by natural convection due o its low dcnsity. When he methanesource was at thc ceiling t.iust collccted cncath he cciling. When hc sourcc was on theside wall, a wall plume osc o the cciling. In all cases, dorant on ccntration asmonitored. l'he odorant concentration emained dentically at the fraction of the gasconcentration t which it was njected, without deviation n any case. fhere was noseparation f the odorant iom the carrier gas.

CONCLUSIONS

Based n the varietyof gas dispersion nalyses hat have been onducted. he ollowingconclusions re eached:

oo

FDS s valid for conducting dispersion analysesSome of the validations f FDS or dispersion nd examples f dispersionapplications sing FDS have been presented n this paper.More validation f FDS br dispersion roblems s needed.Suggestions re provided br more detailed experimental alidation.Benefits o the Gas ndustry rom these efforts will includebetter analysis oolsfo r public safety tudies.

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S m n k P Vi P w 4 n 4 N n v 1 6 T n n d

Figurc 10. Methane Plume With Odorant njected

REFERENCES

McGrattan, K.B, et al. "Fire Dynamics Simulator-Technical Reference Guide",NISTIR 6467, National nstitute of Standards nd Technology, anuary 2000Mc(irattan, K.B, et al, "liire Dynamics Simulator Version 2) -'l'echnical tefcrenceGuide", NISTIR 6783. National Institute of Standards nd Technology. November2001McGrattan, K.B, et al, "Fire Dynamics Simulator (Version 3) -Technical ReferenceGuide", NIS'flR 6783 2002 Ed., National Institute of Standards nd Technology,November 2002.McGrattan, K.B, "fiire Dynamics Simulator (Version 4) -Technical ReferenceGuide", NIST Special Publication 1018, National Institute of Standards andTechnology. uly 2004.McGrattan. K., "Computational Fluid Dynamics and Fire Modeling,"(ftp.nist.gov/pub/bfrl/mcgratta/fds3/MANUALS/class2002.pdf) all 2001."Progress Report on the Federal Building and Fire Salbty nvestigation of the WorldTrade Center Disaster." IST Special Publication 000-5. une 2004.

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7. Mniszewski, K.R., and R. Pape, "The Use of FDS for Estimation of FlammableGasAy'apor oncentrations," 'o Technical Symposium on Computer Applications nFire Protection Engineering, ociety of Fire Protection Engineers, 2-13 September2 0 0 1 .

8. Musser, A., K.B. McGrattan, and J. Palmer, "Evaluation of a F'ast, SimplifiedComputational luid Dynamics Model for Solving Room Airflow Problems, NISTIRn6760. National nstitute of Standards nd Technology. Gaithersburg, aryland, un e2 0 0 1 .

9. Rehm, R.G., K.8., McGrattan, and H.R. Baum, "An Efficient Large Eddy SimulationAlgorithm for Computational Wind Engineering: Application to Surface PressureComputations n a Single Building."NISl ' lR 6371.

10. Rehm, R.G., K.8.. McGrattan, nd H.R. Baurn, L.arge rddy Simulation 1' FlowOver a wooded Building Complex," Wind and Structures, Vol. 5 no. 2-4 (2002) 291-300.

1 . Smagorinsky. .. "General Circulation Experiments with Primative I,.quations,"Month lyWeuther ev iew.91 . umber , 1963 . p .99-164 .

12. Smagorinsky, ., S. Manabe, and J.L. Holloway, "Numerical results iom a Nine-Levef General Circulation Model of the Atmosphere," Monthly ll/eather Review,93,Number 2 .1965, p .727-768 .

13. McGrattan, .B. et al "Fire Dynamics Simulator version ) lJser 's Guide", NISTSpecial Publication 1019, National Institute of Standards nd T'echnology, ebruary2005

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