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Helicopter rotor blades are usually aerodynamically limited by the severe conditions present in every revolution: strong shock wave boundary layer interaction on the advancing side and dynamic stall on the retreating side. Therefore, different flow control strategies might be applied to improve the aerodynamic performance.

The present research is focussed on the application of passive rod vortex generators (RVGs) to control the flow separation induced by strong shock waves on helicopter rotor blades. The formation and development in time of the streamwise vortices are also investigated for a channel flow.

The proposed RVGs are able to generate streamwise vortices as strong as the well-known air-jet vortex generators. It has been demonstrated a faster vortex formation for the rod type. Therefore, this flow control device is preferred for applications in which a quick vortex formation is required. Besides, RVGs were implemented on helicopters rotor blades improving their aerodynamic performance (ratio thrust/power consumption).

A new type of vortex generator (rod) has been investigated in several configurations (channel flow and rotor blades).

Relative to in-service aero-engines, the bypass ratio of future civil architectures may increase further. If traditional design rules are applied to these new configurations and the housing components are scaled, then it is expected that the overall weight, nacelle drag and the effects of aircraft integration will increase. For this reason, the next generation of civil turbofan engines may use compact nacelles to maximise the benefits from the new engine cycles. The purpose of this paper is to present a multi-level design and optimisation process for future civil aero-engines.

An initial set of multi-point, multi-objective optimisations for axisymmetric configurations are carried out to identify the trade-off between intake and fancowl bulk parameters of highlight radius and nacelle length on nacelle drag. Having identified the likely optimal part of the design space, a set of computationally expensive optimisations for three-dimensional non-axisymmetric configurations is performed. The process includes cruise- and windmilling-type operating conditions to ensure aerodynamic robustness of the downselected configurations.

Relative to a conventional aero-engine nacelle, the developed process yielded a compact aero-engine configuration with mid-cruise drag reduction of approximately 1.6% of the nominal standard net thrust.

The multi-point, multi-objective optimisation is carried out with a mixture of regression and classification functions to ensure aerodynamic robustness of the downselected configurations. The developed computational approach enables the optimisation of future civil aero-engine nacelles that target a reduction of the overall fuel consumption.

Aerodynamic shape optimisation is complex because of the high dimensionality of the problem, the associated non-linearity and its large computational cost. These three aspects have an impact on the overall time of the design process. To overcome these challenges, this paper aims to develop a method for transonic aerodynamic design with dimensionality reduction and multifidelity techniques.

The developed methodology is used for the optimisation of an installed civil ultra-high bypass ratio aero-engine nacelle. As such, the effects of airframe-engine integration are considered during the optimisation routine. The active subspace method is applied to reduce the dimensionality of the problem from 32 to 2 design variables with a database compiled with Euler computational fluid dynamics (CFD) calculations. In the reduced dimensional space, a co-Kriging model is built to combine Euler lower-fidelity and Reynolds-averaged Navier stokes higher-fidelity CFD evaluations.

Relative to a baseline aero-engine nacelle derived from an isolated optimisation process, the proposed method yielded a non-axisymmetric nacelle configuration with an increment in net vehicle force of 0.65% of the nominal standard net thrust.

This work investigates the viability of CFD optimisation through a combination of dimensionality reduction and multifidelity method and demonstrates that the developed methodology enables the optimisation of complex aerodynamic problems.