2005
DOI: 10.1177/0731684405052187
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Optimization of a Composite Rotor Blade using a Genetic Algorithm with Local Search

Abstract: The material and ply angles of a fiber-reinforced plastic (FRP) rotor blade of a helicopter are optimized using a genetic algorithm (GA) with local search. The variation of the structural stiffness with material and ply angle is investigated. The aim of the optimization is to find an optimal stacking sequence that minimizes twist deformation. An optimum rotor blade is obtained using the ply angles as variables; failure, natural frequency, and minimum moment of inertia are used to constrain the optimization. Th… Show more

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Cited by 7 publications
(5 citation statements)
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“…The GA was considered because many of the classical gradient-based methods encounter difficulties when handling complex problems such as optimising composite layups and several other researchers have used GA based optimisation strategies in schemes for composite layups [4,13,16,31,32]. GAs are capable of handling both continuous variable and integer variable optimisation problems.…”
Section: The Genetic Algorithmmentioning
confidence: 99%
“…The GA was considered because many of the classical gradient-based methods encounter difficulties when handling complex problems such as optimising composite layups and several other researchers have used GA based optimisation strategies in schemes for composite layups [4,13,16,31,32]. GAs are capable of handling both continuous variable and integer variable optimisation problems.…”
Section: The Genetic Algorithmmentioning
confidence: 99%
“…Thus, the Genetic Algorithm (GA) was chosen as it can satisfy all these requirements. The GA has been used by several authors [30,27,8,9,31] in composite ply optimization tasks proving its attractiveness and credibility. The process of GA involves applying mutations to the ply angle configuration and evaluating whether the blade can achieve the required angle at the tip.…”
Section: Genetic Algorithm Based Optimizationmentioning
confidence: 99%
“…Both the GA and the FE solver were coded in the commercial numerical processing software Matlab™. Although it is possible to couple the GA with an existing commercial FEM solver as attempted by several authors in similar research [1,27,5,6,9], a coupled fully in-house solver is seen as a future proof approach. This is due to the inherent freedom the user has within such a solver and capability of improvement and further streamlining in the future.…”
Section: Genetic Algorithm Based Optimizationmentioning
confidence: 99%
See 1 more Smart Citation
“…While maximizing stiffness, buckling strength, damping, natural frequency, etc. by modifying fiber orientations, material or thickness distribution, a static failure theory may be used 2,5,44,75,160,176,198,219,226,228,244,247,255,266,291,321,339,353,386,439,508,580,581,621,631,719,822,831,937,951,960,961 to guard against static failure. During weight minimization of pressure vessels, a lower limit may be imposed on the burst pressure.…”
Section: Introductionmentioning
confidence: 99%