GASFLOW Parallelization

Transkript

1 GASFLOW Parallelization Jianjun Xiao and Jack Travis Karlsruhe Institute of Technology Organized by SIMAPS on behalf of Karlsruhe Institute of Technology 03 November 2014

2 Content Status of GASFLOW parallelization Successful engineering applications of GASFLOW-MPI Features of GASFLOW-MPI Parallel scalability of GASFLOW-MPI Code and data structures of GASFLOW-MPI Testing strategy of GASFLOW-MPI Conclusions

3 Status of GASFLOW-MPI Development GASFLOW has been parallelized successfully using MPI and domain decomposition. The GASFLOW-MPI is currently under intensive internal testing and validation. The backward compatibility is the top priority. GASFLOW-MPI has successfully reproduced the simulations of large scale engineering projects: EPR, ITER, KONVOI (GKN II) and THAI. Very good speed-up were obtained. Established long term goal: a leading CFD code for thermal hydraulics and safety analysis in the nuclear containment and other large scale industrial facilities.

4 Timeline of GASFLOW-MPI Development July : start development GASFLOW features and models, improve post-processor Release of GASFLOW-MPI Parallelization of GASFLOW core Optimization, Internal testing, V&V, and documentation Further development

5 Motivation GASFLOW currently has more than 22 licenses in the worldwide. GASFLOW user community is still expanding rapidly. Germany (4), China (12), South Korea (2), Mexico (2), France (1), Hungary (1) and Czech republic (1).

6 GASFLOW Users

7 GASFLOW Development Team Thomas Jordan Group leader Jianjun Xiao Developer: parallel version, physics models, V&V and documentation Jack Travis Developer: serial version, physics models, V&V and documentation Anatoly Svishchev Peter Royl Application and Validation Gottfried Necker Code custodian, HPC, post-processing and release Gerold Halmer Consultant and Post-processing User support

8 Configuration of the GASFLOW Server Ubuntu LTS (GNU/Linux generic x86_64) CPU: E GHz, 3.1 MB L3 Cache per CPU core 8 nodes. 2 CPU sockets on each node. 8 cores on each CPU socket. GASFLOW-MPI-dev, PETSc Courtesy of A. Svishchev

9 Configuration of the GASFLOW Server (cont d) Infiniband Node 9 No 10 N Node 13 N 14 No 15 N 16 1 Gbit/s Internal network Interface computer RAID System Shared user home Courtesy of A. Svishchev

10 To Obtain a Decent Parallel Performance with GASFLOW-MPI A fast, low-latency interconnect. High per-core memory performance. Each core needs to have its own memory bandwidth of roughly 2 or more Gigabytes/second. This is because the speed of sparse matrix computations is almost totally determined by the speed of the memory, not the speed of the CPU. Number of floating point instructions is less than number of memory references, so matrix vector multiply kernel is memory bound. W. Gropp, D. Kaushik, D. Keyes, and B. Smith. Toward Realistic Performance Bounds for Implicit CFD Codes (1999). W. Gropp, D. Kaushik, D. Keyes, and B. Smith. Understanding the Parallel Scalability of An Implicit Unstructured Mesh CFD Code (2000). W. Gropp, D. Kaushik, D. E. Keyes, B. Smith. Performance Modeling and Tuning of an Unstructured Mesh CFD Application (2000) An absolute minimum of 10,000 ~ 20,000 cells in each sub-domain is highly recommended. There must be enough work for each process to overweigh the communication time. Output data only when it is necessary. Currently GASFLOW-MPI only supports sequential output to netcdf data format.

11 Successful Cases of GASFLOW-MPI Blind calculation of AREVA-EPR Cylindrical, 32*122*85 = 331,840 Mass and energy diffusion, turbulence, conjugated heat and mass transfer, twophase, radiation, recombiner, Xenon decay Physical time of the accident: 15,000 s Speed-up: 4.81 times faster than SX8 NOTE: Courtesy of H. Dimmelmeier 1. SX8 was the fastest vector machine worldwide ( costing 8 Million Euros ); 2. GASFLOW server used for parallel computing is average (or below average) worldwide (costing 35,000 Euros, price ratio: 230); 3. GASFLOW-MPI has not yet fully optimized; 4. Such a speed-up can be further increased using more powerful cluster and fully optimized GASFLOW-MPI.

12 Successful Cases of GASFLOW-MPI (cont d) Blind calculation of KONVOI (GKN) Cartesian, 65*65*45 = 190,125 Conjugated heat and mass transfer, heat conduction, radiation, two-phase, recombiner, Xenon decay Physical time of the accident : 9608 s Computing time of serial GASFLOW on SX8: 110 hours (4.58 days) Computing time of GASFLOW-MPI on GASFLOW server: hours (0.71 day) NOTE: Speed-up: 6.45 times faster than SX8 1. SX8 was the fastest vector machine worldwide ( costing 8 Million Euros ); 2. GASFLOW server used for parallel computing is average (or below average) worldwide (costing 35,000 Euros, price ratio: 230); 3. GASFLOW-MPI has not yet fully optimized; 4. Such a speed-up can be further increased using more powerful cluster and fully optimized GASFLOW-MPI. Courtesy of P. Royl

13 Successful Cases of GASFLOW-MPI (cont d) ITER Cartesian, 156*122*46 = 875,472 Physical time of the accident : 200 s Computing time of serial GASFLOW on iketgftr: 715,160 s (198.7 hours, 8.3 days) Computing time of GASFLOW-MPI on GASFLOW server: 55,028 s (15.3 hours) Speed-up: 13 (iketgftr) NOTE: 1. Load balancing becomes the bottleneck of the parallel scalability. Load balancing

14 GASFLOW-MPI Parallel Scalability Testing case for parallel scalability 3-D H 2 bubble in mixtures of air, steam and liquid droplet. Mass and energy diffusion, momentum diffusion. Heat conduction of the slab on the boundary and radiation. Buoyant laminar flow. Initial velocity: 0 m/s. 2 nd Van Leer scheme. Initial time step: s. Convergence criterion: 1e-8. Cells number: 200*200*200 = 8,000,000. No load balancing problem. To test the efficiency, robustness and scalability of the linear solver under big time step.

15 Wall clock time (s) GASFLOW-MPI Parallel Scalability (cont d) Speed-up Speed up of GASFLOW-MPI GASFLOW-MPI serial-gasflow T Number of processes Number of processes Wall clock time Speed-up (1-128 procs) Sub-linear scalability is obtained. The maximum speed-up is 56 when using all of 128 cores on the GASFLOW server.

16 Speed-up GASFLOW-MPI Parallel Scalability (cont d) Speed-up Speed up of GASFLOW-MPI D GASFLOW-MPI Linear scaling Number of processes Number of processes Speed-up (1-16 procs) The calculation is dominated by the memory bandwidth per core. Speed-up based on 16 procs Super-linear scalability is observed if the wall clock time of 16 processes is used as the base to calculate the speed-up.

17 speed-up GASFLOW-MPI parallel scalability (cont d) Speed up of GASFLOW-MPI node core GASFLOW-MPI Total number of cores = cores per node srun -n16 --nodes=1 --ntasks-per-node=16 xgf-mpi cores per node srun -n16 --nodes=2 --ntasks-per-node=8 xgf-mpi Number of cores per node 4 cores per node srun -n16 --nodes=4 --ntasks-per-node=4 xgf-mpi Speed-up (fixed total number of processes: 16) If the calculation is not dominated by the memory bandwidth, such as 2 cores per node, GASFLOW-MPI can reach linear speed-up. 2 cores per node srun -n16 --nodes=8 --ntasks-per-node=2 xgf-mpi The speed-up can be different using the same number of cores. This is because the speed-up of is not only dependent on the number of cores, but also on the available memory bandwidth per core. Careful tuning is needed to obtain best parallel efficiency.

18 Features of GASFLOW-MPI Flexible structured mesh capability available plan Cartesian Cylindrical Non-uniform mesh Multi-block Immersed boundary CAD Flexible geometrical modeling capability Obstacles Walls and rupture discs Holes Fractional Area/Volume Object Representation (FAVOR) Geometric modeler Flexible boundary conditions Global BC Pressure boundary condition Velocity boundary condition Mass flow rate boundary condition Periodic boundary condition Proven technology of solving N-S equations and accurate numerics ICE d ALE 1 st order upwind 2 nd order Van Leer Higher order schemes Cutting-edge, scalable and powerful high performance computing capabilities PETSc Third-party pre-conditioners and solvers GPU Load balancing

19 Features of GASFLOW-MPI (cont d) available Under development plan Turbulence modelling Algebraic κ-ε, κ-ω and SST κ-ω LES Heat and mass transfer, radiation model Conjugate 1-D heat conduction Radiation 3-D heat conduction heat transfer (slab, wall, sink) model (slab, wall, sink) Multiphase flow Homogeneous equilibrium model Lagrangian Discrete multiphase model Eulerian multiphase model Simplified chemical kinetics Data format to Third-party One-step two-step Visit post-processing tools Material properties 25 Gas species 20 solid materials

20 Features of GASFLOW-MPI (cont d) Unique features for large scale industrial applications available Under development plan Hydrostatic Aerosol pressure model Ignitor model Recombiner model Sump model Fan model Pre-expansion model Static film model Spray model based on HEM Xenon decay model Sigma and DDT criteria for H2 explosion risk analysis Aerosol model Lagragian dust transportation Spray model based on Eulerian Multiphase model Dynamic water film model Dust modeling based on Discrete Multiphase model Spray model based on Discrete Multiphase model Pre-processor, Post-processor and data export Data format to Third-party pyscan netcdf Visit post-processing tools Pre-processor and GUI

21 GASFLOW-MPI Code Structure Input Setup ICE d ALE Output PETSc Domain decomposition Parallelization Initial condition Boundary condition Mesh & Geometry Physics models Linear solver and preconditioners Grid management: matrix, vector & index Computation and communication kernels: MPI, BLAS and LAPACK

22 GASFLOW-MPI Data Structure Data structure for fluid dynamics Cell-centered variables Face-centered variables Variables for multi-species Parallel sparse matrix Overlapping computation and communication Cylindrical coordinate and periodic boundary conditions Data structure for heat conduction Slab: 3-D, one-sided heat conduction Wall: 2-D, two-sided heat conduction Sink: 3-D, one-sided symmetrical heat conduction Data structure for Lagrangian particle model D1 D2 wall

23 GASFLOW-MPI Testing Unit testing Integration testing System testing Acceptance testing Highly qualified GASFLOW testers are the key to the success of the code!!!

24 Success Criteria of GASFLOW-MPI Testing General goal: the GASFLOW-MPI MUST be accurate, robust, effective and parallel scalable. The calculation results of GASFLOW-MPI MUST agree well with the benchmarks which have been well accepted by the CFD community. The calculation results of GASFLOW-MPI MUST be identical to the results of the GASFLOW serial version. Any difference MUST be clarified and explained. The calculation results of GASFLOW-MPI MUST be not sensitive to the numbers of processes. For symmetrical problems, symmetry MUST be perfectly preserved. Good parallel scalability MUST be able to achieve for the scalable problems.

25 Unit and Integration Testing of GASFLOW-MPI Dimensions and axis (7) 1D (x/y/z), 2D (xy/xz/yz) and 3D (xyz) Coordinates (2) Number of combinations Cylindrical and Cartesian infinity (I mean huge) Numerical schemes (2) 1 st order upwind and 2 nd order Van Leer Various combinations of boundary conditions ( >10 ) Global : periodic BC, no-slip BC, free slip BC, continuous BC and pressure BC Local: mass flow rate BC, velocity BC, pressure BC, outflow Diffusion terms (3) Momentum diffusion, mass diffusion and energy diffusion Turbulence model and wall functions (5) Laminar, algebraic model, k-e model and various wall functions Material properties (14) specific internal energy (ieopt: 4), specific heat capacity (icopt: 4) and transport properties (itopt: 6) Gravitational force (6) ±gx, ±gy, ±gz Various options for physics models and features

26 Unit and Integration Testing of GASFLOW-MPI (cont d) Models and features (300 new testing cases, totally 550 small testing cases) Analytical velocity boundary condition Chemical kinetics Euler equation FAVOR: areardef Diffusion: mass, momentum, energy Geomodel Conjugated heat transfer Hydrostatic pressure Recombiner and ignitor Rupture disc Sigma and DDT criteria Sortam Spray Turbulence models and wall functions Xenon decay Commonly tested Symmetry Dimensions: 2D and 3D Coordinates: cartesian and cylindrical Material property options Numerical schemes Various options of physics models Various number of processes

27 Unit and Integration Testing of GASFLOW-MPI (cont d) An example for 3-D slab heat transfer testing (currently 26)

28 V&V of GASFLOW-MPI Sod s shock tube analytical solution Solving compressible Euler equations in GASFLOW-MPI, no diffusion G.A. Sod (1978), A survey of Several Finite Difference Methods for Systems of Nonlinear Hyperbolic Conservation, Journal of Computational Physics, vol. 27, pp (Cited by 1529) Lid-driven cavity flow experimental benchmark Solving compressible N-S equations in GASFLOW-MPI, momentum diffusion (laminar) U. Ghia (1982), High-Re solutions for incompressible flows using the Navier-Stokes equations and a multigrid method, Journal of Computational Physics, 48, (Cited by 2642) Low Mach number thermal flow numerical benchmark Solving compressible N-S equations in GASFLOW-MPI, momentum and energy diffusion (laminar) A. Beccantini et al., Numerical simulations of transient injection flow at low Mach number regime. Int. J. Numer. Meth. Engng 2008; 76: (Cited by 7) Turbulent plane mixing layer experimental benchmark Solving compressible N-S equations, momentum diffusion (turbulent) J. Delville, Analysis of Structures in a Turbulent, Plane Mixing Layer by Use of a Pseudo Flow Visualization Method Based on Hot-Wire Anemometry, in: Advances in Turbulence 2, eds: H.-H. Fernholz and H. E. Fiedler, 1989, pp (Cited by 18) Turbulent helium horizontal jet in MISTRA 2009 campaign experimental benchmark Solving compressible N-S equations, mass, momentum and energy diffusion (turbulent)

29 V&V of GASFLOW-MPI Cases Advection Pressure propagation Momentum diffusion Mass and Energy diffusion Sod s shock tube Y Y Explicit/implicit N N Lid-driven cavity Y Y implicit Y laminar N Low Mach number thermal flow Y Y implicit Y laminar Y Turbulent mixing layer Y Y implicit Y turbulent N MISTRA 2009 campaign Y Y implicit Y turbulent Y

30 V&V Shock Tube Sod s shock tube ( 0~5 m high pressure, 5~10 m low pressure ) Initial conditions The flow is laminar and inviscid. The calculations were performed using the ICE d ALE algorithm. The case was run to a maximum time of seconds (as in the classical case considered by Sod G.A., A survey of Several Finite Difference Methods for Systems of Nonlinear Hyperbolic Conservation, Journal of Computational Physics, 1978 vol. 27, pp ). 0 m ~ 5 m 5 m ~ 10 m 1bar, 1.0 kg/m3, K 0.1 bar, kg/m3, K

31 V&V Shock Tube (cont d) Testing cases for Sod s shock tube (time = s) 1-D: Cartesian, x/y/z, uniform/non-uniform, 1 st upwind 2-D: Cartesian, x-y/x-z/y-z, uniform/non-uniform, 1 st upwind 3-D: Cartesian, uniform/non-uniform, 1 st upwind All the calculations were performed by GASFLOW-MPI with one processor Cases Dimension Axis Mesh Cells number Cell size (cm) 1 / 2 / 3 1-D X / Y / Z Uniform / 5 / 6 1-D X / Y / Z Non-uniform 1000 See below 7 / 8 / 9 / 10 1-D X Uniform 750 / 500 / 250 / / 2 / 5 / / 12 / 13 2-D 14 / 15 / 16 3-D nkx=2, X-Y / Y-Z / Z-X X-(YZ) / Y-(ZX) / Z-(XY) xl(1)= 0.0, xc(1) = 500.0, nxl(1)= 500, nxr(1)= 0, dxmn(1)= 0.5, xl(2)= 500.0, xc(2) = 500.0, nxl(2)= 0, nxr(2)= 500, dxmn(2)= 0.5, xl(3)= , Uniform 1000*100 1 Uniform 1000*100*10 1

32 velocity (m/s) pressure (bar) density (kg/m3) V&V Shock Tube (cont d) Calculation results of GASFLOW-MPI (case 1-6, 1D, various axis and meshes) case 1 case 2 case 3 case 4 case 5 case 6 analytical case 1 case 2 case 3 case 4 case 5 case 6 analytical X (m) case 1 case 2 case 3 case 4 case 5 case 6 analytical X (m) Forschungszentrum Karlsruhe 6 GmbH X (m)

33 density (kg/m3) pressure (bar) density (kg/m3) V&V Shock Tube (cont d) Calculation results of GASFLOW-MPI (case 1, 7-10, 1D, various cell sizes) case 1 (1000 cells) case 7 (750 cells) case 8 (500 cells) case 9 (250 cells) case 10 (100 cells) analytical case 1 (1000 cells) case 7 (750 cells) case 8 (500 cells) case 9 (250 cells) case 10 (100 cells) analytical X (m) case 1 (1000 cells) case 7 (750 cells) case 8 (500 cells) case 9 (250 cells) case 10 (100 cells) analytical X (m) und Universität X (m) Karlsruhe (TH)

34 velocity (m/s) pressure (bar) density (kg/m3) V&V Shock Tube (cont d) Calculation results of GASFLOW-MPI (cases 11-16, various dimensions) case 11 (2D, X-Y) case 12 (2D, Y-Z) case 13 (2D, Z-X) case 14 (3D, X-Y-Z) case 15 (3D, Y-Z-X) case 16 (3D, Z-X-Y) analytical case 11 (2D, X-Y) case 12 (2D, Y-Z) case 13 (2D, Z-X) case 14 (3D, X-Y-Z) case 15 (3D, Y-Z-X) case 16 (3D, Z-X-Y) analytical X (m) case 11 (2D, X-Y) case 12 (2D, Y-Z) case 13 (2D, Z-X) case 14 (3D, X-Y-Z) case 15 (3D, Y-Z-X) case 16 (3D, Z-X-Y) analytical X (m) Forschungszentrum Karlsruhe 5 6 GmbH X (m)

35 V&V Pressure Wave Propagation from the Center 1D symmetrical Sod s shock tube -10 m ~ -5 m -5 m ~ 5 m 5 m ~ 10 m 0.1 bar, kg/m3, K 1bar, 1.0 kg/m3, K 0.1 bar, kg/m3, K 2D pressure wave from the center (Sod s shock tube type, the same initial condition as the 1D case)

36 V&V Pressure Wave Propagation from the Center (cont d) Testing cases Cartesian, uniform, 1 st upwind Cases Dimension Axis Mesh Cell number Cell size (cm) 17 / 18 / 19 1-D X / Y / Z Uniform / 21 / 22 2-D XY / XZ / YZ Uniform 400*400 5 Motivation To check if the symmetry is preserved for a symmetrical problem

37 pressure (bar) V&V Pressure Wave Propagation from the Center (cont d) Calculation results of GASFLOW-MPI (cases 17~22, symmetry checking) case 17 (1D, X, 1000) case 18 (1D, Y, 1000) case 19 (1D, Z, 1000) case 20 (2D, XY, 400*400) case 21 (2D, YZ, 400*400) case 22 (2D, XZ, 400*400) analytical X (m)

38 density (kg/m3) V&V Pressure Wave Propagation from the Center (cont d) Calculation results of GASFLOW-MPI (cases 17~22, symmetry checking) case 17 (1D, X, 1000) case 18 (1D, Y, 1000) case 19 (1D, Z, 1000) case 20 (2D, XY, 400*400) case 21 (2D, YZ, 400*400) case 22 (2D, XZ, 400*400) analytical X (m)

39 velocity (m/s) V&V Pressure Wave Propagation from the Center (cont d) Calculation results of GASFLOW-MPI (cases 17~22, symmetry checking) case 17 (1D, X, 1000) case 18 (1D, Y, 1000) case 19 (1D, Z, 1000) case 20 (2D, XY, 400*400) case 21 (2D, YZ, 400*400) case 22 (2D, XZ, 400*400) analytical X (m)

40 V&V Pressure Wave Propagation from the Center (cont d) Calculation results of GASFLOW-MPI (pressure, cases 20, 2D, X-Y, symmetry checking)

41 V&V Pressure Wave Propagation from the Center (cont d) Calculation results of GASFLOW-MPI (density, cases 20, 2D, X-Y, symmetry checking)

42 V&V Pressure Wave Propagation from the Center (cont d) Calculation results of GASFLOW-MPI (velocity, cases 20, 2D, X-Y, symmetry checking)

43 Sample Calculation Pressure Wave Propagation from the Center 3D pressure wave from the center (Sod s shock tube type) The computational domain is (-10m ~ 10m), (-10m ~ 10m), (-10m ~ 10m) with 200 (X) * 200 (Y) * 200 (Z) cells. The initial air conditions in the lower pressure part are 0.1 bar, kg/m3 and K. The initial air conditions in the higher pressure part are 1 bar, 1.0 kg/m3 and K. A cube higher pressure air is in the center of the domain (- 5m ~ 5m), (-5m ~ 5m) and (-5m ~ 5m).

44 Sample Calculation Pressure Wave Propagation from the Center Calculation results of GASFLOW-MPI (3D, iso-surface, pressure=0.15 bar) (2D pressure contours)

45 Sample Calculation Pressure Wave Propagation from the Center pressure (bar) Calculation results of GASFLOW-MPI (3D, 200*200*200) GASFLOW (3D, 200*200*200) analytical X (m)

46 V&V - Lid-driven Cavity Flow (Re=1000, Ma 0) Physical problem Isothermal incompressible laminar flow in a 2D cavity (2m*2m) Top boundary: moving wall at u = 1 m/s; Other boundaries: no-slip primary central vortex and secondary vortices at the corners evaluation of different discretization schemes: first order upwind and second order Van Leer Ghia, U., Ghia, K. N., and Shin C.T., (1982), High-Re solutions for incompressible flows using the Navier-Stokes equations and a multigrid method", J.Comput.Phys, 48,

47 V&V - Lid-driven Cavity Flow (Re=1000, Ma 0) GASFLOW-MPI simulation mesh (80*80, Van-Leer) Mesh for GASFLOW-MPI Results of GASFLOW-MPI

48 V&V - Lid-driven Cavity Flow (Re=1000, Ma 0) GASFLOW-MPI simulation velocities: U and W (Van-Leer) Results of GASFLOW-MPI Results of GASFLOW-MPI

49 V&V - Lid-driven Cavity Flow (Re=1000, Ma 0) GASFLOW-MPI simulation stream line (Van-Leer) Results of GASFLOW-MPI Courtesy of Ghia, 1982

50 V&V - Lid-driven Cavity Flow (Re=1000, Ma 0) Horizontal velocity (U) along vertical centerline (Z); Vertical velocity (W) along horizontal centerline (X) Effect of numerical schemes (1 st upwind and 2 nd Van-Leer in GASFLOW-MPI)

51 V&V Low Mach Number Thermal Flow 2-D laminar low Mach number flow Solving compressible N-S equations in GASFLOW-MPI, momentum and energy diffusion (laminar) A. Beccantini et al., Numerical simulations of transient injection flow at low Mach number regime. Int. J. Numer. Meth. Engng 2008; 76: Comparisons have been done in our group using open source CFD codes: GASFLOW, OPENFOAM, FDS and CFDLib. Good agreements were obtained. Number of cells: 120 * 120

52 V&V Low Mach Number Thermal Flow Contours of temperature MPI GASFLOW (Van_Leer) Courtesy of Beccantini Serial GASFLOW (Van_Leer)

53 V&V Low Mach Number Thermal Flow Contours of velocity in horizontal direction (m/s) Serial GASFLOW (Van_Leer) MPI GASFLOW (Van_Leer)

54 V&V Low Mach Number Thermal Flow Uy (cm/s) Comparison of GASFLOW serial and parallel version Uy, Y=350 cm (GASFLOW serial version) Uy, Y=350 cm (MPI-GASFLOW) Uy, Y=350 cm (Beccantini, 2008) X (cm)

55 V&V Low Mach Number Thermal Flow T (K) Comparison of GASFLOW serial and parallel version T, Y=350 cm (GASFLOW serial version) T, Y=350 cm (MPI-GASFLOW) T, Y=350 cm (Beccantini, 2008) X (cm)

56 V&V Plane Turbulent Mixing Layer E300 open loop wind tunnel of the C.E.A.T. Poitiers Geometry model for GASFLOW-MPI

57 U (m/s) V&V Plane Turbulent Mixing Layer k (m 2 /s 2 ) Initial conditions for the turbulent mixing layer (MPI-GASFLOW) Exp. data (J. Delville, 1988) 12 ( MPI-GASFLOW) Exp. data (J. Delville, 1988) X (mm) X (mm)

58 U (m/s) U (m/s) V&V Plane Turbulent Mixing Layer U (m/s) U (m/s) Mean velocity profile (MPI-GASFLOW) Exp. data (J. Delville, 1988) (MPI-GASFLOW) Exp. data (J. Delville, 1988) cm 20 cm X (mm) (MPI-GASFLOW) Exp. data (J. Delville, 1988) (MPI-GASFLOW) Exp. data (J. Delville, 1988) X (mm) cm cm X (mm) X (mm)

59 Reco tests Thermohydraulic tests System Testing - GASFLOW Validation Library Rerun all the cases in the validation library with GASFLOW-MPI (P. Royl) Facility Test HDR T31.5 (ISP23) E11.2 (ISP29) GF Reference Analysis Publications ( ) [1],[2] ( ) [3],[4] TOSQAN ISP [5], [6] MISTRA ISP [6] ThAI TH [5] TH [5] TH [4],[6] TH13 (ISP47) 2006 [8] Battelle GX6 ( ) [2],[7],[8],[9] GX7 ( ) [7], [8], [9] [1] P. Royl, C. Müller, J. R. Travis, T. Wilson, Validation of GASFLOW for Analysis of Steam/Hydrogen Transport and Combustion Processes in Nuclear Reactor Containments, Procs 13th Conference on Structural Mechanics in Reactor Technology, August 13-18, 1995 Porto Alegre, RS, Brazil [2] J. W. Spore, P. Royl, J. R. Travis et al.: GASFLOW: A Computational Fluid Dynamics Code for Gases Aerosols, and Combustion, Volume 3 Assessment Manual, LA M, FZKA-5994, October 1998 [3] P. Royl, J. R. Travis, E. A. Haytcher, and H. Wilkening, "Analysis of Mitigating Measures during Steam/Hydrogen distributions in Nuclear Reactor Containments with the 3D Field Code GASFLOW," presented at the OECD/NEA CSNI Workshop on the Implementation of Hydrogen Mitigation Techniques, Winnipeg, Canada, May 13 15, [4] P. Royl, J. R. Travis, W. Breitung, Benchmarking of the 3D CFD Code GASFLOW with Containment Thermal Hydraulic Tests from HDR and ThAI, procs IAEA- OECD CFD4NRS Conference Munich September 5-7, 2006 [5] P. Royl, J. R. Travis, W. Breitung, Analyses of Containment Experiments with GASFLOW, procs Nureth-10 Conference, Seoul, Korea, October 2003 [6] H.J. Allelein et al.: International Standard Problem ISP-47 on Containment Thermal Hydraulics, OECD -final report draft July 28 th 2006 [7] P. Royl, J. R. Travis, Simulation of Hydrogen Transport with Mitigation Using the 3D Field Code GASFLOW, Procs. 2nd International Conference on Advanced Reactor Safety, June 1-4, 1997, Orlando, Florida [8] P. Royl, G. Necker, J. W. Spore, J. R. Travis, 3D Analysis of Hydrogen Recombination Experiments in the Battelle Model Containment with the GASFLOW Code. Procs Jahrestagung Kerntechnik, Munich May 26-28, 1998 [9] P. Royl, J. R. Travis, W. Breitung, Modelling and Validation of Catalytic Hydrogen Recombination in the 3D CFD Code GASFLOW II, procs IAEA-OECD CFD4NRS Conference Munich September 5-7, 2006

60 Conclusions The parallelization of GASFLOW is proved to be successful. GASFLOW-MPI solves the generalized 3-D transient compressible Navier- Stokes equation in finite-volume form with the proven semi-implicit pressure-based algorithm (ICE d ALE) for all flow speeds (Hirt CW, Amsden AA, Cook JL. An arbitrary Lagrangian Eulerian computing method for all flow speeds. Journal of Computational Physics 1974; 14(3): ). GASFLOW-MPI is currently under active physics model development and internal testing. GASFLOW-MPI will be released in GASFLOW development team will provide sustainable and prompt technical support services to our GASFLOW code users. Parallelization of GASFLOW is the starting point to develop the leading CFD platform for thermal hydraulic and safety analysis in nuclear containment and other large scale industrial facilities.

61 Thank you for your attention! If you are interested in GASFLOW-MPI, please contact: Dr. Dirk Feuchter License Manager of KIT For technical support, please contact: