Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range

Abstract

We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method (called the profile optimization method) is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages: (a) it prevents severe degradation in the off -design performance by using a smart descent direction in each optimization iteration, (b) there is no random airfoil shape distortion for any iterate it generates, and (c) it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler ow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA393685

Entities

People

  • Luc Hyuse
  • Sharon Padula
  • Wu Li

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Programming
  • Drag Reduction
  • Equations
  • Euler Equations
  • Linear Programming
  • Mach Number
  • Mathematical Models
  • Models
  • Optimization
  • Parallel Computing
  • Parallel Processing
  • Shell Scripts
  • Simulations
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Fluid Mechanics and Fluid Dynamics.