This work presents a framework for the optimisation of various aspects of rotor blades in forward flight. The literature survey suggests that the quest for such a method is generating much research as more performance is obtainable from current designs. With increasing computational power and efficient methods, this can be of practical use to the helicopter industry. The proposed method employs CFD in conjunction with metamodels such as artificial neural networks (ANNs) and kriging interpolation, and a non-gradient based optimiser, in the form of genetic algorithms (GAs), for optimisation. The approach is demonstrated using several cases, including the optimisation of linear twist of rotors in hover (a steady case) and the optimisation of rotor sections in forward flight (an unsteady case); other cases include transonic aerofoils, wing and rotor tip planforms. For rotor tip planforms, first a simple rectangular rotor in hover was optimised. Then the developed method was used to optimise the anhedral and sweep of the UH60-A rotor blade in forward flight while constraining its hover performance and the final rotor optimisation was for a BERP-like rotor in forward flight, also constraining hover performance. For each case, a parameterisation method was defined, a specific objective function created using the initial CFD data and the metamodel was used for evaluating the objective function during the optimisation using the GAs. 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 results were checked by comparison with the Pareto subset of data and the metamodels were also validated with high-fidelity CFD data. Neither was sensitive to the employed techniques with substantial overlap between the outputs of the selected methods. The main CPU cost was associated with the population of the CFD database necessary for the metamodel. To improve this further, the Harmonic Balance alternative for obtaining the CFD data (as opposed to Time Marching) was used to increase efficiency and reduce clock time for the BERP-like tip optimisation. The novelty of this method is the use of a metamodel in conjunction with high-fidelity CFD data so that high-resolution performance improvements can be captured efficiently using a non-gradient based method.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:564238 |
| Date | January 2012 |
| Creators | Johnson, Catherine |
| Contributors | Barakos, George; Badcock, Ken |
| Publisher | University of Liverpool |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://livrepository.liverpool.ac.uk/7553/ |
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