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Industrial Context:

1.0. 0.9. Objective. 0.8. Initial guess. 0.7. 0.6. Optimization. 0.5. 0.4. 0.3. 0.2. 0.1. 0.0. -30. -20. -10. 0. 10. 20. 30. FRT (%). Optimisation code. Interpretation code. INTELLECT D.M. Automatic Optimization Loop Based On a CFD RANS Code. FP6 - 502961

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Industrial Context:

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  1. 1.0 0.9 Objective 0.8 Initial guess 0.7 0.6 Optimization 0.5 0.4 0.3 0.2 0.1 0.0 -30 -20 -10 0 10 20 30 FRT (%) Optimisation code Interpretation code INTELLECT D.M. Automatic Optimization Loop Based On a CFD RANS Code FP6 - 502961 STRP project within the 6th Framework program of the European Union Florent Duchaine - PhD-student 2004-2007 Industrial Context: • Design of combustion chamber must be tuned so as to satisfy pre-requisites on the temperature profile at the outlet of the chamber • Another constraint for low NOx systems is related to the fuel evaporation and mixing inside LPP injection system. Fuel - Air injection Cold air Turbine Today: dilution system design necessitates a lot of engineer know-how and time to converge toward a desired exit temperature profile. Aim: reduce engineering costsby performing an automaticsearch of the optimal design. Combustion chamber Overview of the tool: Tool’s Requirements: • Modularity: easily change the optimization algorithm and CFD CODE • Parallelism intasks and codes, exchange of 3D grid and fields • Optimization on the operating point (Boundary Conditions) and geometry(automatic meshing, grid deformation, grid smoothing …) • Performant optimization algorithm (LBFGS, genetic …) • Determinant choice of the objective function Mesh + boundary conditions Optimization parameters Parallel RANS Code: N3SNatur Estimation of the Objective Function Fluid solution The optimization tool: realization with PALM Validation test case: cooling of 2D channel LFB VFB - TFB - DFB - aFB PALM: a CERFACS coupler (http://www.cerfacs.fr/~palm) Fixed input: hot gas UCA - TCA - DCA • Modular device (ensure evolutivity) • Performant parallelism (MPI 2) • Control of parallel codes • Friendly GUI • Lots of functions (debug, algebra …) VFC - TFC - DFC - aFC LFC Cooling Velocity Temperature Diameter Angle 10 potential optimization parameters: • BC: VFB - TFB - VFC - TFC • Geometric: LBB - DFD - LBC - DFC - aFB - aFC Results: Optimization with LBFGS based on Surrogate (Kriging) Evolution of the surrogate model of the objective function due to enhanced knowledge Initialisation TT (y) : Target temperature profile (user input) TC (y) : Computed exit temperature profile (RANS solution) After few iterations Constants: UCA = 30 m/s TCA = 1500 K DCA = 0.06 m TFB = TFC = 300 K aFB = aFC = 0° Global minimum Optimization parameters: LFB = LFB DFB = DFC Flow RateFB = Flow RateTot – Flow RateFC CERFACS 42 Avenue Gaspard Coriolis F- 31057 Toulouse Cedex Tél. : (+33) 05.61.19.31.31 Fax : (+33) 05.61.19.30.00 secretar@cerfacs.fr http://www.cerfacs.fr

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