Robust Turbine Blade Optimization in the Face of Real Geometric Variations

Because of manufacturing variations, no real turbine blade exactly conforms to its nominal geometry. Even minimal deviations are known to affect aerodynamic performance, blade temperatures, and bla...

[1]  Francesco Montomoli,et al.  Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines , 2015 .

[2]  Marcus Meyer,et al.  Probabilistic CFD Analysis of High Pressure Turbine Blades Considering Real Geometric Effects , 2013 .

[3]  R. Iman,et al.  A distribution-free approach to inducing rank correlation among input variables , 1982 .

[4]  D. Xiu,et al.  Modeling uncertainty in flow simulations via generalized polynomial chaos , 2003 .

[5]  Indraneel Das,et al.  ROBUSTNESS OPTIMIZATION FOR CONSTRAINED NONLINEAR PROGRAMMING PROBLEMS , 2000 .

[6]  B. Iooss,et al.  A Review on Global Sensitivity Analysis Methods , 2014, 1404.2405.

[7]  Andy J. Keane,et al.  Cokriging for Robust Design Optimization , 2012 .

[8]  Andy J. Keane,et al.  Engineering Design via Surrogate Modelling - A Practical Guide , 2008 .

[9]  Andy J. Keane,et al.  Comparison of Several Optimization Strategies for Robust Turbine Blade Design , 2009 .

[10]  Jack P. C. Kleijnen,et al.  Metamodel-Based Robust Simulation-Optimization: An Overview , 2015 .

[11]  Dirk P. Kroese,et al.  Kernel density estimation via diffusion , 2010, 1011.2602.

[12]  John D. Duffner The effects of manufacturing variability on turbine vane performance , 2008 .

[13]  Paul F. Beard,et al.  Effect of Combustor Swirl on Transonic High Pressure Turbine Efficiency , 2014 .

[14]  David L. Darmofal,et al.  Impact of Geometric Variability on Axial Compressor Performance , 2003 .

[15]  Kirill A. Vinogradov,et al.  Robust Optimization of the HPT Blade Cooling and Aerodynamic Efficiency , 2016 .

[16]  Shahrokh Shahpar,et al.  PADRAM: Parametric Design and Rapid Meshing System for Complex Turbomachinery Configurations , 2012 .

[17]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[18]  Andy J. Keane,et al.  Multi-Objective Optimization Using Surrogates , 2010 .

[19]  Marcus Meyer,et al.  Analysis of High Pressure Turbine Nozzle Guide Vanes Considering Geometric Variations , 2016 .

[20]  Geoffrey T. Parks,et al.  Robust Compressor Blades for Desensitizing Operational Tip Clearance Variations , 2014 .

[21]  Andy J. Keane,et al.  Design in the Presence of Uncertainty , 2005 .

[22]  Andy J. Keane,et al.  Computational Approaches for Aerospace Design: The Pursuit of Excellence , 2005 .

[23]  Marcus Meyer,et al.  A parametric model for probabilistic analysis of turbine blades considering real geometric effects , 2014 .

[24]  Peter W. Glynn,et al.  Stochastic Simulation: Algorithms and Analysis , 2007 .

[25]  J. P. van Buijtenen,et al.  Optimization of a Centrifugal Compressor Impeller for Robustness to Manufacturing Uncertainties , 2016 .

[26]  Grigorii Popov,et al.  Effect of Manufacturing Tolerances on the Turbine Blades , 2014 .

[27]  Marcus Meyer,et al.  A Curvature Based Algorithm for Treatment of Cooling Holes in Polygon Meshes of Turbine Blades , 2015 .

[28]  P. Spalart A One-Equation Turbulence Model for Aerodynamic Flows , 1992 .

[29]  Kwon-Hee Lee,et al.  A Global Robust Optimization Using Kriging Based Approximation Model , 2006 .

[30]  L. He,et al.  Impact of Wall Temperature on Heat Transfer Coefficient and Aerodynamics for Three-Dimensional Turbine Blade Passage , 2017 .

[31]  Matthias Voigt,et al.  Principal component analysis on 3D scanned compressor blades for probabilistic CFD simulation , 2012 .

[32]  Shahrokh Shahpar,et al.  Aerodynamic Optimization of High-Pressure Turbines for Lean-Burn Combustion System , 2013 .