Aerodynamic shape optimisation is complex due to the high dimensionality of the problem, the associated nonlinearity 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 develops a method for transonic aerodynamic design with dimensionality reduction and multi-fidelity techniques. It 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 CFD calculations. In ...
This is the author accepted manuscript. The final version is available from UKACM via the link in th...
Aerospace industry is increasingly relying on advanced numerical flow simulation tools in the early ...
A multi-objective optimiZation method is demonstrated using an evolutionary genetic algorithm. The a...
To reduce specific fuel consumption, it is expected that the next generation of aero-engines will op...
For many aerodynamic design tasks, a key challenge is the balance between the non-linearity of the t...
Purpose Relative to in-service aero-engines, the bypass ratio of future civil architectures may inc...
There are significant environmental and economic drivers for the development of more fuel-efficient ...
Genetic algorithms are a powerful optimisation technique for the design of complex engineering syste...
Future turbo-fan engines are expected to operate at low specific thrust with high bypass ratios to i...
It is expected that future civil aero-engines will operate at low specific thrust and high-bypass ra...
Future turbofan engines will operate with larger engine bypass-ratios and lower specific thrust than...
The design of a civil aeroengine nacelle is a complex multi-objective constrained problem, where sev...
An optimisation method consisting of the non-dominated sorting genetic algorithm (NSGA-II) and compu...
AbstractThe paper addresses an application of the software product OPTIMENGA_AERO to a real-life des...
The continuous increase in the number of flights in the last decades caused a steepgrowth of aviatio...
This is the author accepted manuscript. The final version is available from UKACM via the link in th...
Aerospace industry is increasingly relying on advanced numerical flow simulation tools in the early ...
A multi-objective optimiZation method is demonstrated using an evolutionary genetic algorithm. The a...
To reduce specific fuel consumption, it is expected that the next generation of aero-engines will op...
For many aerodynamic design tasks, a key challenge is the balance between the non-linearity of the t...
Purpose Relative to in-service aero-engines, the bypass ratio of future civil architectures may inc...
There are significant environmental and economic drivers for the development of more fuel-efficient ...
Genetic algorithms are a powerful optimisation technique for the design of complex engineering syste...
Future turbo-fan engines are expected to operate at low specific thrust with high bypass ratios to i...
It is expected that future civil aero-engines will operate at low specific thrust and high-bypass ra...
Future turbofan engines will operate with larger engine bypass-ratios and lower specific thrust than...
The design of a civil aeroengine nacelle is a complex multi-objective constrained problem, where sev...
An optimisation method consisting of the non-dominated sorting genetic algorithm (NSGA-II) and compu...
AbstractThe paper addresses an application of the software product OPTIMENGA_AERO to a real-life des...
The continuous increase in the number of flights in the last decades caused a steepgrowth of aviatio...
This is the author accepted manuscript. The final version is available from UKACM via the link in th...
Aerospace industry is increasingly relying on advanced numerical flow simulation tools in the early ...
A multi-objective optimiZation method is demonstrated using an evolutionary genetic algorithm. The a...