Parallel Genetic Algorithm Implementation in Multidisciplinary Rotor Blade Design,

Abstract

The present paper describes an adaptation of genetic algorithms in the design of large-scale multidisciplinary optimization problems. A hingeless composite rotor blade is used as the test problem, where the formulation of the objective and constraint functions requires the consideration of disciplines of aerodynamics, performance, dynamics, and structures. A rational decomposition approach is proposed for partitioning the large-scale multidisciplinary design problem into smaller, more tractable subproblems. A design method based on a parallel implementation of genetic algorithms is shown to be an effective strategy, providing increased computational efficiency, and a natural approach to account for the coupling between temporarily decoupled subproblems. A central element of the proposed approach is the use of artificial neural networks for identifying a topology for problem decomposition and for generating global function approximations for use in optimization. (AN)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1995
Accession Number
ADA305771

Entities

People

  • Jongsoo Lee
  • Prabhat Hajela

Organizations

  • Rensselaer Polytechnic Institute

Tags

DTIC Thesaurus Topics

  • Aerodynamics
  • Algorithms
  • Composite Materials
  • Couplings
  • Decomposition
  • Dynamics
  • Efficiency
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Geometry
  • Heuristic Methods
  • Hingeless
  • Mathematics
  • Neural Networks
  • Optimization
  • Topology

Readers

  • Aerospace Engineering
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology