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On the Use of the PALM Coupler for CFD Applications

On the Use of the PALM Coupler for CFD Applications. By Florent DUCHAINE CERFACS. availability of many performant codes to simulate different physical phenomenon. to reduce predicting errors, the interaction between physics is a key point.

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On the Use of the PALM Coupler for CFD Applications

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  1. On the Use of the PALM Coupler for CFD Applications By Florent DUCHAINE CERFACS

  2. availability of many performant codes to simulate different physical phenomenon • to reduce predicting errors, the interaction between physics is a key point  the first idea would be to rewrite a single mutli-physic code BUT • not preserve the development efforts • not preserve the knowledge on existing codes • not flexible and evolutive at all • hard to realize due to the different approaches inferred from the physics  Why not keeping existing codes and make them communicate ? • interface between the codes become a central point • where can I find a coupler which will allow me to make my codes exchange data in a performant and evolutive way without too much efforts ? Emergence of coupler needs:

  3. Code 1 Code 2 Code 1 Code 2 • Aim for the designers : optimization processes Control parameters Optimization processes or Objective function Emergence of coupler needs: • Distinction between coupling and chaining Very different in term of implementation, computing efforts and results

  4. Session program: • Presentation of the PALM coupler : • Where does PALM come from ? • Main characteristics of PALM • Applications using PALM in the context of CFD : • Management of an Integrated Platform for auTomatic Optimization • Extensions of the use of MIPTO • RANS / LES coupling • Unsteady Combustion / Radiative coupling

  5. Operational oceanography project Mercator • Operational data assimilation system in a real time, flexible and performant way for ocean forecast • Existing codes that have not the same philosophy:  grids, variables, modelisations, characteristic times, CPU times … ? Data exchange and processing Where does PALM come from ? The answer of Mercator : Projet d’Assimilation par Logiciel Multiméthode

  6. The need The constraints Where does PALM come from ? A complex system can be decomposed in parallel (and/or sequential and/or a mix of both) execution of elementary units that exchange information. • elementary operations for modularity • sequencing and launching of operations • communications between operations • fully independent operations, but multiple instances possible • minimum changes in user code • parallel operations / parallel tasks • performant communications • parallel communications with data remapping • toolbox for algebra operations • coherency controls at set up and run time • application monitoring • wide portability

  7. AlgebraUnit: predefined unit, directly usable in PALM • Branch: Sequences of units and instructions, with control structures (if, select, loops), and basic communications • Communications: MPI-2 Main characteristics of the PALM coupler: • Unit: a code, a part of a code – sequential of parallel. A unit is an operation which consume and produce Objects

  8. Main characteristics of the PALM coupler: • PrePALM: the PALM graphical pre-processor • Choose units • Describe internal parallelism in units • Describe the control algorithm: branches • Establish the communications: match the objects between different units

  9. Optimisation : the block, i.e. a set • of units sharing a common memory • space in a SPMD envelope • research in new methods  flexibility  performances • operational use Main characteristics of the PALM coupler: Two parallelism levels: • Flow branches • Distributed units • (Automatic remaping of object between two units running on a different number of processors)

  10. Example of optimization for reacting flows: Management of an Integrated Platform of auTomatic Optimization (MIPTO)

  11. Industrial context Industrial context: combustion chambers • Pressing demand for emission reduction have lead to very ambitious future NOx reduction targets of 80% • Existing design rules for conventional combustors cannot be applied for lean low emissions systems • NEED OPTIMIZATION TOOL COUPLED TO EXISTING CFD TOOLS Support and collaboration: • Collaboration with ONERA • Collaboration with TURBOMECA, Bordes • European project INTELLECT D.M.

  12. Industrial context MP Low NOx = reduce flame Temperature • lean combustion • up to 70% of air used to premixed with fuel • 30% of air for cooling and control exit temperature profile Dilution jets Outlet • CERFACS objective - optimize dilution jets positions and flux to : • minimize outlet temperature variations • maximize combustion efficiency

  13. A solution proposed by CERFACS : MIPTO Algorithmic features: • Optimizations have to be done on the operating point (by changing mass flow rates) and on design (by changing the shape of the domain and the corresponding mesh) • Optimization must be multiparameters and multiobjectives CFD & Optimization: an open issue • “Surrogate based method” Computer science: coupling with PALM  Coupling tool issued from the CERFACS’ Team Global Change is used: PALM (http://www.cerfacs.fr/~palm)

  14. Fct 2 Fct 2 Fct 2 Fct 1 Fct 1 Fct 1 Optimization and Pareto front search on surrogate models Construction of the surrogate models of the fitness functions Construction of the surrogate models of the fitness functions CFD computations for well chosen optimum points and Pareto points Overview of MIPTO Surrogate based Method coupled with high fidelity CFD Initial Database : Design Of Experiment or hot start N sample points = N CFD runs

  15. Overview of MIPTO Automatic CFD process : Pre-processing CFD run Post-processing Optimization process

  16. Outlet T(K) MIPTO applied to a 2D combustor Inlet : plenum Cooling system : film cooling Inlet : fuel and air premixed Reacting zone Cooling system : two dilution jets

  17. MIPTO applied to a 2D combustor Combustion efficiency Combustion efficiency Tmax-Tmin

  18. MIPTO applied to a 2D combustor

  19. MIPTO applied to a 3D combustor Main problem : as mesh deformation is very limiting remeshing becomes necessary. An automatic grid generator is required

  20. Extension of the use of MIPTO Incorporating more physics: radiation, wall heat transfer • CERFACS has already developed for SNECMA an automatic chain for thermal wall prediction of combustion chambers: fluid mechanics + radiation + wall heat transfer. All codes coupled with PALM Twall at convergence Twall at iteration 1

  21. Extension of the use of MIPTO NEXT STEP: optimization of 3D multi-physics simulation Control parameters Optimization processes Objective functions

  22. Other uses of PALM : RANS / LES coupling

  23. Other uses of PALM : RANS / LES coupling

  24. Other uses of PALM : Combustion et RAYonnement par LES

  25. Acknowledgements The author want to thanks : • L. Gicquel and T. Poinsot (CERFACS) for academic and scientific supports • T. Morel (CERFACS) for help, formation, discussions concerning PALM • S. Gratton (CERFACS) for mathematical supports • J. Muller (University of London) for its advices concerning optimization and mesh handling • N. Savary and C. Bérat (TURBOMECA), E. Mercier and C. Baudoin (SNECMA) for industrial support • R. Martin (Incka Simulog) for software support

  26. On the Use of the PALM Coupler for CFD Applications By Florent DUCHAINE CERFACS

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