IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Experience in mathematical optimization Automatic shape optimisation parameterized geometry Wells-Tool

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Optimisation Methods Directe optimisation “Response Surface” method –Estimation of an continous approximate function by Neuronal net Polynomial approach Spline –Search for the optimum of the approximate function

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Parameter Qualitätsfunktion berechnete Werte Optimierung an der Response Surface Response Surface Methode

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS assumed optimum search direction cost function relaxation Gradient type algorithmus, with search direction Opjective funktion is locally approximated and the minimum is calculated along the search direction EXTREME

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Self Adaptive Evolution (SAE) Start with a randomly chosen population New population is obtained by –Mutation –Crossover –Survival of the fittest –Live time of each individual is exactly 1 generation (Comma Strategie) Evolution methode

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Parallel Optimisation simultaneous simulation on different resources each simulation is run in parallel Research: Asynchronous, parallel optimisation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Parallel Optimisation Grid Compting

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Applied Algorithm randomly chosen initial parameter sets CFD survival of the fittest new sets by discrete operation, e. g. mirror new sets randomly with weighting CFD grid portal

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Example Guide vane shape

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Guide vane geometry Inlet angle, Outlet angle, chamber line angle, Weighting factor inlet, Weighting factor outlet, Overlapping, Profile a, Profile b, Trailing edge thickness Geometry Parameterisation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Automatic block structured mesh Automatic Grid Generation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Simulation Results: Flow patterns (e. g pressure distribution) Overall quantities (e. g. efficiency, losses) Restrictions (e. g. cavitation) Typical computational time for one geometry: 1-4 h on a Cluster of HPC

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS 9 free parameters: - 45 different designs (individuals) per generation - 8 generations - in total 360 calculations Guide vane shape optimized with evolution strategy

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Convergence

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Optimised Geometrie

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Test example: Draft tube cone Assumption: Cone length Optimisation: Outlet diameter L D in D out

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube efficiency D_out/D_in Test example: Draft tube cone randomly chosen starting points Cone length: 6 D_in

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube efficiency D_out/D_in Test example: Draft tube cone survivors of the first generation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube efficiency D_out/D_in Test example: Draft tube cone survivors of the second generation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube efficiency D_out/D_in Test example: Draft tube cone survivors of the third generation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube efficiency D_out/D_in Test example: Draft tube cone computed points survivors of the seventh generation

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS The draft tube contour can only be changed slightly. Optimization of the area distribution Draft tube area distribution Application: Refurbishment of an existing power plant

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS area distribution Area distribution represented by B-Spline curves Inlet and outlet kept constant other cross sections scaled up Draft tube area distribution

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube area distribution Investigated area distribution during the optimisation Design point

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS Draft tube area distribution Design point Obtained area distribution original draft tube maximum efficiency minimum efficiency draft tube efficiency increase: 8% overall efficiency increase: 0.4%

IHS-Präsentation, 2008 Ruprecht University of Stuttgart Institute of Fluid Mechanics and Hydraulic Machinery, Germany IHS minimum efficiency Overload design point part load original draft tube Draft tube area distribution