An Inter-Comparison Exercise On the Capabilities of CFD Models to Predict the Short and Long Term Distribution and Mixing of Hydrogen in a Garage A.G. Venetsanos 1, E. Papanikolaou 1, M. Delichatsios 1,10, J. Garcia 2, O.R. Hansen 3, M. Heitsch 4, A. Huser 5, W. Jahn 6, T. Jordan 7, J-M. Lacome 8, H.S. Ledin 9, D. Makarov 10, P. Middha 3, E. Studer 11, A.V. Tchouvelev 12, A. Teodorczyk 13, F. Verbecke 10, M.M. Van der Voort 14 1 National Centre for Scientific Research Demokritos, Greece 2 Universidad Politécnica de Madrid, Spain 3 GEXCON AS, Norway 4 Gesellschaft für Anlagen-und Reaktorsicherheit (GRS)mbH, Germany 5 Det Norske Veritas, Norway 6 Forschungszentrum Juelich, Germany 7 Forschungszentrum Karlsruhe, Germany 8 Institut National de l’Environnement industriel et des RISques, France 9 Health and Safety Laboratory, UK 10 University of Ulster, UK 11 Commissariat à l’Energie Atomique 12 A.V.Tchouvelev & Associates, Canada 13 Warsaw University of Technology, Poland 14 TNO, The Netherlands

Slide 2 Outline  Scope of work  SBEP-V3 specifications  SBEP-V3 participation  SBEP-V3 results Evaluation methodology Blind phase Post phase  Conclusions

Slide 3 SBEPV3Scope of work  To investigate for small hydrogen releases (<1g/s) within confined spaces on the phenomena occurring during the: Release period (short term) Diffusion period, i.e. long after the end of the release (long term)  To test the predictive ability of models/codes/organizations related to the above phenomena by performing New experiments and in parallel Blind simulations of the new experimental set  To develop consensus for the reasons of discrepancies between: Different predictions using same models Predictions of given models and experiment data  To improve our predictive ability by performing non-blind post calculations of the new experimental data

Slide 4 SBEPV3 Specifications Plastic sheet Enclosure size: 7.2 x 3.78 x 2.88 m H2 mass flow rate: 1 g/s Nozzle diameter: 20 mm Exit velocity:38.4 m/s Release duration: 240 s Test duration:5400s Ambient temperature:10 °C Target concentration: 3.53% Height 265mm Diameter:120mm Release chamber

Slide 5 SBEPV3 Participants  12 HYSAFE partners: CEACommissariat à l’Energie Atomique, France DNVDet Norske Veritas, Norway FZJForschungszentrum Juelich, Germany FZKForschungszentrum Karlsruhe, Germany GXCGEXCON AS, Norway HSLHealth and Safety Laboratory, UK INERISInstitut National de l’Environement industriel et des RISques, France NCSRDNational Center for Scientific Research “Demokritos”, Greece TNODefence, Security and Safety Process Safety and Dangerous Goods, The Netherlands UPMUniversidad Politécnica de Madrid, Spain UUUniversity of Ulster, UK WUTWarsaw University of Technology, Poland  2 non-HYSAFE partners: AVTA.V.Tchouvelev & Associates Inc., Canada GRSGesellschaft für Anlagen-und Reaktorsicherheit, Germany

Slide 6 SBEPV3 CFD codes  10 CFD codes applied: ADREA-HF CAST3M CFX CFX 10.0 FDS 4.0 FLACS 8.1 FLUENT 6.2 GASFLOW KFX PHOENICS 3.6

Slide 7 SBEPV3 Turbulence models  8 turbulence models applied: Simple models  LVELLVEL model  MLGeneralized mixing length Two equations models:  KEStandard k-ε  RNGRNG k- ε  REALRealizable k- ε  SSTSST model LES models  Smagorinski subgrid  RNG subgrid

Slide 8 Case Turbulence model CFD Code Blind calculations simulation time (s) Post calculations simulation time (s) Analytical-240 LVEL_AVT LVEL PHOENICS A s LVEL, s laminar LVEL_NCSRDADREA-HF5400 ML_CEAMixing lengthCAST3M KE_DNV_a Standard k-  with buoyancy effects FLACS KE_DNV_bKFX240 KE_FZJCFX A 5400 KE_FZKGASFLOW KE_GRSCFX A KE_GXCFLACS KE_NCSRDADREA-HF5400 KE_TNOFLUENT KE_UPMFLUENT k- , laminar REAL_WUT Realizable k-  FLUENT785 RNG_AVT RNG k-  PHOENICS A s RNG k- , s laminar SST_GRS SST CFX s, A 905 SST_HSLCFX s, CFX 10.0 LES_NCSRDLES SmagorinskyFDS VLES_UULES- RNGFLUENT s, LES Smagorinski SBEPV3Participation matrix

Slide 9 SBEPV3Evaluation methodology Statistical measures: Mean relative bias Mean relative square error Averaging over all SBEP participant predictions for given sensor Predicted mean molar concentration (time averaged) Observed mean molar concentration (time averaged) Duijm et al. (1996) Journal of Loss Prevention in the Process Industry, Vol 9 Ideal values:

Slide 10 SBEPV3 BlindExample prediction Blind prediction (NCSRD) Release phase: 0-240s Diffusion phase: s

Slide 11 SBEPV3 BlindRelease phase Time series averaging period s Large spread for sensors along the jet Large spread for sensors close to the ground and at large lateral distances from jet All sensors

Slide 12 SBEPV3Release Phase Sensorz/L Mo RegionC Bouss (%)C (%)C o (%) BJ BP BP BP Paranjpe (2004) Buoyant jets: Buoyant plumes:Chen and Rodi (1980) Comparison of data with existing correlations for sensors along jet axis Relatively good agreement Boussinesqu approximation overestimates concentrations

Slide 13 SBEPV3 Blind Release phase Sensor 16 Group of LVEL_NCSRD and LVEL_AVT Mixing length too much mixing LES-RNG too much mixing LES-Smagorinski (Cs=0.2) too low mixing KE_FZJ strangely low KE_DNV_b strangely high Group of KE_UPM, KE_NCSRD, KE_GRS RNG_AVT and REAL_WUT Group of KE_GXC, KE_DNVa, KE_FZK SST_GRS, SST_HSL and INERIS data

Slide 14 SBEPV3 BlindDiffusion phase Time series averaging period s All sensors Mixing overestimated: Lower concentrations closer to the ceiling Mixing overestimated: higher concentrations close to the ground

Slide 15 SBEPV3 BlindDiffusion phase Sensor 12 Group of KE_GXC, KE_DNV_a, KE_FZJ Lower mixing is required

Slide 16 SBEPV3 Diffusion phase SensorCo (%) Averaging time period s Average flammable cloud boundary

Slide 17 SBEPV3 BlindDiffusion phase Risk assessment parameters Too much mixing. Transition to homogeneous conditions. Group of LVEL_NCSRD, ML_CEA, KE_UPM, RNG_AVT, SST_GRS, VLES_UU Stratification. Group of LVEL_AVT, KE_FZK, KE_NCSRD, KE_GXC, KE_DNV_a, KE_FZJ, SST_HSL

Slide 18 SBEPV3 PostImprovement steps  Numerical options Grid  Improved vertical grid resolution Some partners used the GEXCON grid Time step  Reduced for both release and diffusion phases Convective discretization scheme  Higher order schemes used  Physical models LES  Smagorinski constant set to Turbulence switched manually off short after release  RNG_AVT and LVEL_AVT Turbulent Schmidt number  Consistent use of the 0.7 value

Slide 19 SBEPV3 Post Release phase Sensor 16

Slide 20 SBEPV3 Post Diffusion phase

Slide 21 SBEPV3 Post Diffusion phase

Slide 22 SBEPV3 Release phase SensorCo (%) BlindPost MRBMRSEMRBMRSE Averaging time period s

Slide 23 SBEPV3Diffusion phase SensorCo (%) BlindPost MRBMRSEMRBMRSE Averaging time period s

Slide 24 SBEPV3 Conclusions Release phase  The effect of the turbulence model is clearly important.  In the jet region the standard k-ε model when applied without previous knowledge of the experimental data (blind prediction) generally tended to overestimate the concentrations. This was shown to be rectified either: using a low turbulent Schmidt number (0.3) in combination with a first order upwind scheme or using the usual value of 0.7 for turbulent Schmidt combined with a smaller time step and higher order convective scheme. From the two approaches the second is recommended.  RNG k- ε and Realizable k- ε models showed tendency to overestimate the concentrations.  LVEL model generally tended to underestimate concentrations.  The SST model was found to produce hydrogen concentrations in the jet region lower than the standard k-  model and in better agreement with the present experiment.  The LES Smagorinski model was found in good agreement with measured concentrations when the Smagorinski constant was set equal to 0.12

Slide 25 SBEPV3 Conclusions Diffusion phase  Experiments showed that a layer of hydrogen exists close to the ceiling, which is horizontally quasi homogeneous and vertically stratified.  Blind predictions showed two types of physical behaviour, either approximately constant stratification or fast transition to homogeneous hydrogen (non-flammable) distribution in the room.  Improvement of the predictions and reduction of spread between models was achieved in the post phase mainly by: applying time step restrictions reduction of vertical grid spacing increase of the order of the convective scheme  The option of “manually” turning the turbulence model off although improved predictions in some cases cannot be suggested as a general recommendation.  Comparison between predicted and observed concentrations shows that the models generally tend to overestimate turbulent mixing Work funded by EC