PARALLEL GENETIC ALGORITHM IMPLEMENTATION IN MULTIDISCIPLINARY ROTOR BLADE DESIGN

An adaptation of genetic algorithms as an optimization tool for large- scale multidisciplinary design problems is described. The design of a hingeless composite rotor blade is used as a test bed for this class o f problems, where the formulation of the objective and constraint func tions requires the consideration of disciplines of aerodynamics, perfo rmance, dynamics, and structures. A rational decomposition approach ba sed on the use of neural networks is proposed for partitioning the lar ge-scale multidisciplinary design problem into smaller, more tractable subproblems. A design method based on a parallel implementation of ge netic algorithms is shown to be an effective strategy, providing incre ased computational efficiency, and a natural approach to account for t he coupling between temporarily decoupled subproblems.