SOME ISSUES CONCERNING THE CFD MODELLING OF CONFINED HYDROGEN RELEASES Habib O. KONE3, Audrey DUCLOS1, Christophe Proust2,3 and F. Verbecke1 7th ICHS, September 11-13, 2017 – Hamburg, Germany 1 AREVA ENERGY STORAGE 2 INERIS 3 UTC

Introduction Modern computing resources CFD tools, especially commercial ones, offer the possibility to “everyone” to simulate real scale accidental scenarios...to make safety decisions, A number of benchmarking exercises were performed along the past decades, including lastly, SUSANA E.U. project, showing a good agreement between the simulations and the available data but : The experimental results where known before; The “modellers” were acknowledged experts in fluid mechaniscs. BUT what would happen if : No data are available ? The modeller is not an expert in the domain? The objective of the underlying project is to investigate the traps the modeller could find while attempting to model a full accidental scenario. This presentation is focussed on the « dispersion » phase.

The supporting project Aim : investigate the capabilities and limitations of “commercial” CFD codes to simulate real scale explosion scenario Development of a CFD numerical toolbox MERLIN incorporating the various submodels available in the targeted codes (EXSIM, FLACS, MG,..) Mostly uRANS formalism in finite volumes; Various numerical solvers (FCT, FVS, Roe,…); k-epsilon models; Subgridding of obstacles or body fitting; Various combustion model ( EBU; HM; CREBCOM,…). Comparison to representative situations for which data are available : Shock formation, propagation and interaction with walls; Massive leakage and cloud formation with and without in a confinment; Flame propagation and interaction with congestion.

Configuration : GAMELAN experiments Test Bore orifice (mm) He flowrate (Nl/mn) 1 5 180 2 20 10

Results : GAMELAN experiments Test 1 : 180 Nl/mn Test 2 : 10 Nl/mn

MERLIN : equations and solver (i) Roe Solver with the minmod limiter Explicit scheme for the time derivatives

MERLIN : equations and solver (ii) 1-Turbulence model : standard k-epsilon + wall approximation 2-Turbulence model : « low Reynolds » k-epsilon

MERLIN : initial, boundary conditions and convergence Location Conditions vent atmospheric pressure, only normal velocity injection atmospheric pressure, mass flowrate constant, enclosure atmospheric pressure, normal velocity at the wall = 0 where U<>0 Where U=0 12 M Cells 6 M Cells 1 MCells 14 MCells Anisotropic Mesh adapation

Results with the standard k-epsilon model (+log law) for test 1 Unrealistic stratification but correct max % He in the top

Results with the standard k-epsilon model (+log law) for test 2 Numerical simulations The trends are not captured, the discrepancies may be as large as 40%... WHY ?

Going back to the physics…. Buoyancy, viscous and inertial forces are at work and two zones may be distinguished : in the plume and in the rest of the box Non dimensional numbers: Low Reynolds numbers especially with the smaller flowrate. The loglaw might be a bad approximation since the boudary layer cannot be fully developed => testing the 2nd turbulence model

Results with the Low Reynolds k-epsilon model (+log law) Test 2 Test 1 Much better agreement now !

Conclusion Even in a rather simple looking situation obtaining a correct estimation using a CFD code might be challenging. A too-rapid choice of the turbulence model may end up with a 30% error… Quite a significant and structured knowledge of the fluid mechanics is required in this case although it remains simple on the mathematical side (very little influence of the solver and of the mesh topology which is not the case for shock wave problems for instance) Facing a new dispersion problem, the modeller has to look for representative experimental data which sometimes requires a “skilled” eye… Finally, the use of CFD codes by “standard” users in the field of safety at least is to be questioned.

THANK YOU FOR YOUR ATTENTION SOME ISSUES CONCERNING THE CFD MODELLING OF CONFINED HYDROGEN RELEASES THANK YOU FOR YOUR ATTENTION Audrey DUCLOS, PhD Student Research engineer AREVA Energy Storage Audrey.duclos@areva.com