Sensitivity Analysis - Dynardo GmbH

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Design variable 2 Design variable 2 Adaptive Response Surface Methods (Local) Design variable 1 Design variable 1 objective objective 1. Iteration © 2009 ANSYS, Inc. All rights reserved. 38 ANSYS, Inc. Proprietary objective 5. Iteration 3. Iteration
Adaptive Response Surface (ARSM) • The ARSM does not provide differentiable and smooth problems; very efficient for n < 15 design parameters • Starting solution is based on the best design of the EA • The design space is reduced to 20% around start solution © 2009 ANSYS, Inc. All rights reserved. 39 ANSYS, Inc. Proprietary
Page 1 and 2: Optimization and Robustness Evaluat
Page 3 and 4: Motivation Power Plant 1000 MW Effi
Page 5 and 6: Parameterization Process & Geometry
Page 7 and 8: Parameterization of the Geometry De
Page 9 and 10: Parameter Manager Parameter List In
Page 11 and 12: Workbench Interface to optiSLang ©
Page 13 and 14: Parameter Physics, Fluid Flow c0 r
Page 17 and 18: Latin Hypercube and Confidences •
Page 19 and 20: Coefficient of Importance, CoI CoI=
Page 21 and 22: Meta-Model of Prognosis, MoP Respon
Page 23 and 24: Coefficient of Importance, CoI vs.
Page 25 and 26: Anthill Plots Objective initial Goo
Page 29 and 30: Optimization Strategy Sensitivity A
Page 31 and 32: Evolutionary Algorithms (EA) Optimi
Page 33: Evolutionary Algorithms (EA) best d
Page 37 and 38: Initial vs. Optimized Design Input
Page 39 and 40: Initial vs. Optimized Design Isotro
Page 43 and 44: Variation of Robust Space • n = 1
Page 45 and 46: Define Objective Limits • Limit s
Page 47 and 48: Evaluation of Histogram Non-robust

Sensitivity Analysis - Dynardo GmbH

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