A tool to create parametric aerodynamic shapes using intuitive design variables based on class shape transformation curves is presented. To enable this, a system has been developed which accepts arbitrary constraints and automatically derives the analytical expressions which describe the corresponding class shape transformation curves. Parametric geometry definitions for fan cowl and intake aero-lines were developed using the generalized method. CFD analysis of the fan cowl shows that despite the simple geometry definition its performance characteristics are close to what would be expected of a finished design. The intake geometry was generated in a similar way and met the typical performance metrics for conventional intakes. This demonstrates the usefulness of the tool to quickly and robustly produce parametric aero-lines with good aerodynamic properties, using relatively simple intuitive design variables.

A parametric geometry definition for a generic turbofan nacelle was developed for use in preliminary design, based on Class-Shape Transformation curves. This takes as input a set of six intuitive variables which describe the main dimensions of a nacelle. This set is the same set of inputs as required by a preliminary nacelle design method to which the aerodynamic properties of resulting shapes were compared. An automated computational fluid simulation process was developed and implemented which generates meshes and quickly conducts an analysis of the resulting nacelle shapes using a commercial code. Several geometries were generated and analysed using this process to show whether the aerodynamic properties of the generated shapes are in line with the expected performance of a fan cowl of equal dimensions. It was found that the aerodynamic performance of the parametric fan cowls significantly exceeds predictions from an established preliminary fan cowl design method and is very close in performance to existing designs. The drag of an equivalent parametric fan cowl can therefore be used as a predictor of nacelle performance with greater accuracy than established preliminary design methods. It is therefore suited as a tool to develop improved preliminary design methods, and for studies of the design space for preliminary nacelle design.

A tool to create parametric aerodynamic shapes using intuitive design variables based on class shape transformation (CST) curves is presented. To enable this, a system has been developed which accepts arbitrary constraints and automatically derives the analytical expressions which describe the corresponding class shape transformation curves. Parametric geometry definitions for fan cowl and intake aero-lines were developed using the generalized method. Computational fluid dynamics (CFD) analysis of the fan cowl shows that despite the simple geometry definition, its performance characteristics are close to what would be expected of a finished design. The intake geometry was generated in a similar way and met the typical performance metrics for conventional intakes. This demonstrates the usefulness of the tool to quickly and robustly produce parametric aero-lines with good aerodynamic properties, using relatively simple intuitive design variables.

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A multi-objective optimisation method is demonstrated using an evolutionary genetic algorithm. The applicability of this method to preliminary nacelle design is demonstrated by coupling it with a response surface model of a wide range of nacelle designs. These designs were modelled using computational fluid dynamics and a Kriging interpolation was carried out on the results. The NSGA-II algorithm was tested and verified on established multidimensional problems. Optimisation on the nacelle model provided 3-dimensional Pareto surfaces of optimal designs at both cruise and off-design conditions. In setting up this methodology several adaptations to the basic NSGA-II algorithm were tested including constraint handling, weighted objective functions and initial sample size. The influence of these operators is demonstrated in terms of the hypervolume of the determined Pareto set.