Presentazione a 11èmes journées du GDR Incendie, CSTB - Champs sur Marne, Paris (Fr), 17th -18th June 201

Borchiellini R.

Colella F.

Rein G.

Torero J.L.

Verda V.

English

Presentazione a 11èmes journées du GDR Incendie, CSTB - Champs sur Marne, Paris (Fr), 17th -18th June 201

COLELLA, FRANCESCO

VERDA, Vittorio

BORCHIELLINI, Romano

Torero J. L.

PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino)

05 August 2020POLITECNICO DI TORINORepository ISTITUZIONALEMultiscale analysis of tunnel ventilation flows and fires / Colella F.; Rein G.; Verda V.; Borchiellini R.; Torero J.L.. -ELETTRONICO. - (2010).OriginalMultiscale analysis of tunnel ventilation flows and firesPublisher:PublishedDOI:Terms of use:openAccessPublisher copyright(Article begins on next page)This article is made available under terms and conditions as specified in the  corresponding bibliographic description inthe repositoryAvailability:This version is available at: 11583/2370566 since:GDR CNRS n°2864     17‐18 June 2010 Multiscale analysis of tunnel ventilation flows and fires CFD 3D fire module 1-dimensional network Tunnel Portal Tunnel Portal 1-dimensional network Dr. Francesco ColellaDr Guillermo Rein.     Prof. Vittorio VerdaProf. Romano BorchielliniProf. Jose L. ToreroDipartimento di Energetica – Politecnico di Torino     Introduction ‐ Ventilation systemThe most widespread safety system in tunnels is the ventilation system ¾Normal operating conditionsi ibili• v s ty • pollutant concentrations  ¾Emergency conditions• Smoke management• safe evacuations• fire fighting    Dipartimento di Energetica – Politecnico di TorinoIntroduction ‐ Ventilation systemThe flow conditions within tunnels are dependent on the combined i fl fn uence o :¾Ventilation devices (axial and jet fans)l l ( l )¾Tunne   ayout  s opes¾Boundary conditions at the portals¾Blockages within the domain¾Fire size and Location ¾Comprehensive analysis has to consider the whole system and not simply a part of itDipartimento di Energetica – Politecnico di Torino1D Network model ‐ characteristics¾Fast simulations¾St i htf d d fi iti f b d ditira g orwar e n on o oun ary con ons¾Predict the global behaviour of coupled systemsW ll bli h d f d i¾ e esta s e or es gn purposesBUT¾Need calibration constants¾Provides only ballpark figuresDipartimento di Energetica – Politecnico di TorinoCFD model ‐ characteristics ¾Detailed flow field representation¾Well established for design verificationBUT¾Large computational time¾Not affordable for long tunnels or foranalysis of ventilation strategiesll l d l d¾Sti imite resu ts ue to uncertaintiesin modelling turbulence, combustion,radiation and pyrolysis of condensed fuels¾“Acceptable” accuracy for globalquantities (i.e. back‐layering distance)“ ” di i f l l fl fi ld d¾ Poor pre ct ons o oca ow e ataDipartimento di Energetica – Politecnico di TorinoCFD vs. 1D computing timeCFD modelstime AccurateIs theretional     anything in 1D modelmputatbetween?RoughComTunnel LengthDipartimento di Energetica – Politecnico di TorinoMultiscale model ‐ introductionTypical velocity contours in presence of jet fans1D region 3D region 1D regionT l P t l  1-dimensional network unne or aCFD model1D model Tunnel Portal CFD 3D jet fan module 1-dimensional network 1D modelDipartimento di Energetica – Politecnico di TorinoMultiscale model ‐ introductionTypical temperature contours in presence of fire1D region 1D region3D regionCFD model1D model1D modelDipartimento di Energetica – Politecnico di TorinoMultiscale – coupling procedurePhysical decomposition of the domain1D Regions¾ Low velocity/temperature gradients3D Regions¾ High velocity/temperature gradients¾ Mono‐dimensional models can be used¾ CFD models must be adopted1D region3D region1D regionDipartimento di Energetica – Politecnico di TorinoMultiscale – coupling procedure•Based on Dirichlet‐Neumann methods•Use non‐overlapping domain decomposition •Neumann‐type boundary condition     applied to the CFD sub‐domain interfaces •Dirichlet‐type boundary condition applied to the 1D sub‐domain interfaces. •The model guarantees the continuity of average pressure, velocity and x=a        temperature values at the 1D‐CFD interfacesΩ3D ΩΓa 1D x Dipartimento di Energetica – Politecnico di TorinoMultiscale – coupling procedureCoupling stages1 ‐ Full 1D model2 CFD model near field ‐      3.a – 1D model far field3.b ‐ CFD model near fieldK‐timesProceed to the next time step when some global convergence is reached Dipartimento di Energetica – Politecnico di TorinoMultiscale ‐ characteristics¾Dramatic reduction of the computational time (up to 2 ordersof magnitude for a 1.2 km long tunnel)¾As accuracy as CFD¾ Successfully used for parametric studiesBUT¾The placement of the 1D‐3D interfaces is an issue¾Higher set up time than CFD¾The CFD solver has to be accessed by the user during theiteration algorithm (i.e. compiled UDF for FLUENT)Dipartimento di Energetica – Politecnico di TorinoSimulation of tunnel ventilation flowsEast & West Dartford tunnels (UK) 250m 1055m 130m Essex(north)Kent(south)133m 1280m 157m Colella, F., et al (2010), Tunnel. Underg. Space Technol.Dipartimento di Energetica – Politecnico di TorinoColella F et al (2009) Building and EnvironmentSimulation of tunnel ventilation flowsEast & West Dartford tunnels (UK)¾≈1500 m long with hybrid ventilation system¾East tunnel diam 9.5 m (1980) ¾West tunnel diam 8.6 m (1963)¾2 supply & extraction ventilation stations in the vicinity of the portals¾28 jet fans in the West Tunnel¾11 reversible jet fans in the East ltunneColella, F., et al (2010), Tunnel. Underg. Space Technol.Dipartimento di Energetica – Politecnico di TorinoColella F et al (2009), Building and EnvironmentSimulation of tunnel ventilation flowsWest Tunnel Jet fan near fieldMultiscale arrangement L3D3456[m]456m]456m]K+3K+2 t+2t+3South Extraction shaft North Extraction shaft Tunnel Reference Section 2 Tunnel Reference Section 1LDsection 20 m012h [section 40 m0123h [msection 60m0123h [mNorth portalSouth portal ii-1 i-2 kK+11 Nt+1j j+1 j+2t‐2 0 2 4 6 8 10horizontal velocity [m/s]0 2 4 6 8 10horizontal velocity [m/s]0 2 4 6 8 10horizontal velocity [m/s]5656673D Sub‐domain Ω3D1D Sub‐domain Ω1,1D 1D Sub‐domain Ω1,1D  Γj Γi 100m10m234h [m]234h [m]2345h [m]Far field  Far fieldNear fieldsection 80 m010 2 4 6 8 10horizontal velocity [m/s]section 100 m010 2 4 6 8 10horizontal velocity [m/s]section 120 m010 2 4 6 8 10horizontal velocity [m/s]Dipartimento di Energetica – Politecnico di TorinoSimulation of tunnel fire scenarios¾1200 m long longitudinally ventilated¾10 pairs of jet fans (50m spaced, 34 m/s discharge air velocity)¾Fire located in the centre of the tunnel             ¾Fire max HRR: from 10 MW to 100 MWDipartimento di Energetica – Politecnico di TorinoSimulation of tunnel fire scenarios¾Ventilation scenarios¾Scenario 1: 3 jet fan pairs¾Scenario 2: 5 jet fan pairs¾Scenario 3: 10 jet fan pairsDipartimento di Energetica – Politecnico di TorinoSimulation of tunnel fire scenariosFire near fieldMultiscale arrangement South portalNorth portal K+3K 1K+1 K+2 K+4K+5it+3tt+1t+2 t+4t+5Ni+11D Sub‐domain Ω2,1D 1D Sub‐domain Ω1,1D ΓiL3D3D Sub‐domain Ω3DΓi+1 Far fieldNear fieldFar fieldDipartimento di Energetica – Politecnico di TorinoSteady state resultsComparison to full CFD solutions (30 MW fire)Scenario 1: 3 Jet fan pairsfull CFDMultiscaleHighly accurate results are achieved!Colella F et al Fire Technology (in press)Dipartimento di Energetica – Politecnico di Torino  .,    .,    ,    . Time dependent resultsVelocity30 MWHRRection15 MW/minDetetime4 min2 minDipartimento di Energetica – Politecnico di TorinoTime dependent resultsMultiscale results: 2 minutes330320 310n[m]6temperature: 300 320 340 360 380 400elevation50 100 150 200 25002470 m back –layering Longitudi al coordinate [m]e-0.6 -0.4 0.60.41on[m]46x-velocity: -1 - .8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 100Longitudinal coordinate [m]elevatio50 100 150 200 25002Dipartimento di Energetica – Politecnico di TorinoTime dependent resultsMultiscale results: 3 minutesS i 1 3 J t f i05100 m back –layering cenar o  :    e   an pa rs400 500 600 700Scenario 2: 5 Jet fan pairs400 500 600 7000570 m back –layering 50 m back –layering Scenario 3: 10 Jet fan pairsLongitudinal coordinate [m]400 500 600 7000≈ 0 m back –layering Dipartimento di Energetica – Politecnico di TorinoTime dependent resultsS i 1 3 J t f iMultiscale results: 5 minutes05cenar o  :    e   an pa rs400 500 600 700 800 900 1000 1100 1200Scenario 2: 5 Jet fan pairs400 500 600 700 800 900 1000 11000512005Scenario 3: 10 Jet fan pairs400 500 600 700 800 900 1000 110001200Dipartimento di Energetica – Politecnico di TorinoConclusions (1)Several numerical techniques have been used todeal with ventilation and fire induced flows in tunnels               • 1D and CFD models• Multiscale models¾ Dramatic reduction of the computational time (up to 2 orders ofmagnitude)¾ As accurate as full CFD¾ Results agree well with experimental measurements¾ Allow for full coupling of fire and ventilation system and completeanalysis of ventilation system response¾ Well suited to conduct parametrical studies, sensitivity analysis,d d t di d D t ti /A ti ti / ti blDipartimento di Energetica – Politecnico di Torinore un ancy s u es an e ec on c va on propaga on pro emsConclusions (2)Evaluation of Fire throttling effect(…. the additional fire induced pressure losses due to sudden air expansion, higher velocities, buoyant effects and localized losses in the plume region. …. amplified for larger fires and longer tunnels…)6R i l b l i l i45t fan pairs• equ re a g o a s mu at onof tunnel and ventilationsystem to be evaluated23 # jet•Can be significant for largefires (>100 MW) and longtunnels!01Fire size [MW]•The number of jet fan pairsrequired to achieve critical0 20 40 60 80 100 120velocity is highly dependentof the fire sizeDipartimento di Energetica – Politecnico di TorinoConclusions (3)Evaluation of the ventilation system response (Time required to remove back‐layering)350400ak [s] Scenarios 1, 2, 3; TD=2minScenarios 4 5 6; TD=2 5minDetection time 2.5 min200250300fire outbrea   ,  ,    .Scenarios 7, 8, 9; TD=1.5minDetection time 1.5 minDetection time 2.0 min100150d time from 0502 3 4 5 6 7 8 9 10 11 12 13 14elapse# active jet fan pairsSignificant impact of detection time on ventilation system response!Dipartimento di Energetica – Politecnico di TorinoList of publicationsAny questions?Dipartimento di Energetica – Politecnico di TorinoTunnel ventilation models ‐ NetworkDipartimento di Energetica – Politecnico di TorinoModelling techniques – 1D Network¾Computational domain splitted in branches and nodes¾Mass conservation in each node¾Momentum conservation in each branch¾Constitutive equations for components• Fire Modelled as source of heat (variable in time)• Fans modelled using a fan characteristic curveDipartimento di Energetica – Politecnico di TorinoModelling techniques – 1D Network12Jet fan characteristic curve810[pa]46pressure rise ‐2020 2 4 6 8 10 12avrg velocity [m/s]‐6‐4Dipartimento di Energetica – Politecnico di TorinoMultiscale – coupling procedureTime step: N Time step: N+1Multiscale iterations K           ‐0.0100.0001 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 193.003.50[kg/s] [Pa]   ‐‐0.030‐0.0202 002.50Total pressure at inletIntroduction: three‐stage coupling‐0.050‐0.0401.50.Mass flow rate at inlet‐0.070‐0.0600.501.00       ‐0.080 0.00Dipartimento di Energetica – Politecnico di Torino

Multiscale analysis of tunnel ventilation flows and fires

https://iris.polito.it/retrieve/handle/11583/2370566/52966/Presentazione_Colella.pdf

Multiscale analysis of tunnel ventilation flows and fires

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