Observations on the Topology of Pareto Frontiers with Implications for Design Decision Making

Daskilewicz, Matthew J.; German, Brian

doi:10.2514/6.2012-148

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…Then, Eq. (12) is decomposed to form ωDQ hb R hb (13) where D E −1 ME, and E is a transformation matrix transformingQ andR to Q hb and R hb . The diagonal of D is 0 and pseudo time marching can then be applied to the harmonic balance equation,…”

Section: Methodsmentioning

confidence: 99%

“…However, this can still be a difficult task if the number of design variables is high and if the properties of the Pareto subset are not properly analyzed. More information about this can be found in the paper by Daskilewicz and German [13]. Much research has been carried out in developing and comparing various evolutionary optimization techniques and can be found in the following literature [14][15][16].…”

Section: B Optimizationmentioning

confidence: 99%

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Optimizing Rotor Blades with Approximate British Experimental Rotor Programme Tips

Johnson

Barakos

2014

Journal of Aircraft

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This work presents a framework for the optimization of certain aspects of a British Experimental Rotor Programme-like rotor blade in hover and forward flight so that maximum performance can be obtained from the blade. The proposed method employs a high-fidelity, efficient computational fluid dynamics technique that uses the harmonic balance method in conjunction with artificial neural networks as metamodels, and genetic algorithms for optimization. The approach has been previously demonstrated for the optimization of blade twist in hover and the optimization of rotor sections in forward flight, transonic aerofoils design, wing and rotor tip planforms. In this paper, a parameterization technique was devised for the British Experimental Rotor Programme-like rotor tip and its parameters were optimized for a forward flight case. A specific objective function was created using the initial computational fluid dynamics data and the metamodel was used for evaluating the objective function during the optimization using the genetic algorithms. The objective function was adapted to improve forward flight performance in terms of pitching moment and torque. The obtained results suggest optima in agreement with engineering intuition but provide precise information about the shape of the final lifting surface and its performance. The main computational cost was associated with the population of the genetic algorithms database necessary for the metamodel, especially because a full factorial method was used. The computational time of the optimization process itself, after the database has been obtained, is relatively insignificant. Therefore, the computational time was reduced with the use of the harmonic balance method as opposed to the time marching method. The novelty in this paper is twofold. Optimization methods so far have used simple aerodynamic models employing direct "calls" to the aerodynamic models within the optimization loops. Here, the optimization has been decoupled from the computational fluid dynamics data allowing the use of higher-fidelity computational fluid dynamics methods based on Navier-Stokes computational fluid dynamics. This allows a more realistic approach for more complex geometries such as the British Experimental Rotor Programme tip. In addition, the harmonic balance method has been used in the optimization process.

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Section: Methodsmentioning

confidence: 99%