An Intercomparison Exercise on the Capabilities of CFD Models to Predict Deflagration of a Large-Scale H 2 -Air Mixture in Open Atmosphere J. García, E. Gallego, E. Migoya, A. Crespo (UPM) A. Kotchourko, J. Yañez (FZK), A. Beccantini (CEA), O.R. Hansen (GexCon), D. Baraldi (JRC), S. Høiset (N-H), M.M. Voort (TNO), V. Molkov (UU)

Standard Benchmark Exercise Problems  SBEPs Objectives: – establishing a framework for validation of codes and models for simulation of problems relevant to hydrogen safety, – identifying the main priority areas for the further development of the codes/models. SBEPs in HySafe

The experiment was performed by the Fraunhofer Institut Chemische Technologie (Fh-ICT), Germany in m diameter polyethylene hemispheric balloon (total volume 2094 m3). Homogeneous stoichoimetric hydrogen-air mixture. Experiment description

Initial conditions: – Pressure: 98.9 kPa – Temperature: 283 K. Pressure dynamics was recorded using 11 transducers, installed on the ground level in a radial direction at different distances from the centre. The deflagration front propagation was filmed using high-speed cameras. Experiment description

Variation of flame front contours with time. Experiment results

The flame front radius vs. time Experiment results

Organisations and codes participating Participant OrganisationsCodes CEA, Commissariat à l’Energie Atomique, France CAST3M FZK, Forschungszentrum Karlsruhe, Germany COM3D GexCon, GexCon AS, Norway FLACSv8.1 JRC, Joint Research Centre, European Commission Reacflow NH, Norsk Hydro ASA, Norway FLACSv8.0 TNO, The Netherlands AutoReaGas v3.0 UU, University of Ulster, UK FLUENTv6.1.18

Participant & Code Turbulence model Chemical model CEA CAST3M -CREBCOM combustion model GexCon FLACS v8.1 k-  standard Beta flame model Reaction rate based on one step model with burning velocity from flame-library FZK COM3D k-  standard CREBCOM combustion model. Adjustable parameter C f, governing the rate of chemical interaction and therefore a visible flame speed. JRC Reacflow k-  standard Modified Eddy Dissipation combustion model NH FLACS v8 k-  standard Beta flame model TNO AutoReaGas v3.0 k-  standard Combustion rate depends on the mean composition of the mixing region. Flame speed correlates via empirical relations with the calculated turbulence parameters UU FLUENT v LES (RNG)Gradient method Models

Participant & Code Resolution method & discretisation scheme Grid Computer & CPU time CEA CAST3M Operator splitting technique. First order 1D spherical domain Cell size 0.1 m Not available GexCon FLACS v8.1 SIMPLE Second order 3D-Cartesian Cell size: 0.5 m 1 CPU PCs Gb RAM Linux 4h CPU FZK COM3D Solver coupled with turbulence & chemical models. 3D cartesian grid Cell size: 0.3 m combustion 0.59 m pressure Cluster of 7 Athlon PC - 2 CPU each. Linux ≈ 14 days /with 14 processors JRC Reacflow Explicit scheme Second order 3D unstructured adaptive grid 0.15 m Linux cluster 26.5 to142 h CPU NH FLACS v8 SIMPLE Second order 3D-Cartesian Cell size: 0.67 m 6 days CPU (1 s experiment) TNO AutoReaGas SIMPLE First order 3D Cartesian cells UU FLUENT Explicit method 2 nd order 3D unstructured tetrahedral grid (a): 0.4 m (b): 0.2 m 2/6 CPU 4/12 Gb RAM 142/197h CPU (0.32/0.63 s experiment)

All experimental results were known before the calculations. Comments about results The influence of the polyethylene film and wire net was supposed negligible. Sensors at 2, 8 and 18 m have to be influenced by combustion because they do not recover ambient pressure.

Dynamics of the flame front radius with time

Pressure dynamics at R= 2 m Flame front reaches the sensor

Pressure dynamics at R= 5 m Flame front reaches the sensor

Pressure dynamics at R= 8 m Flame front reaches the sensor

Pressure dynamics at R= 18 m Flame front reaches the sensor

Pressure dynamics at R= 35 m

Pressure dynamics at R= 80 m

Video: FzK

Video: GexCom Flame velocity Pressure

Video UU

The flame velocity is reproduced quite well in most of the calculations. The pressure dynamics obtained numerically are in good agreement with the experiments for the positive values. Negative pressures are more sensitive to far field boundary condition, this can be avoided using larger domains and finer grids. More benchmarks will be necessary to calibrate and improve the codes. Conclusions