## 4 Results and Discussion
### Parameter Evolutionary Behaviour  
Figure 15 shows the power against efficiency plot for all blades that met the design constraints requirements. The graph shows a clear pattern of inverse proportionality, as well as the effect of the difference in weighting within the fitness function of these two parameters. The majority of designs were tending towards maximum efficiency, while still avoiding low power values. The graph highlights the effect of high penalisation fitness functions, with the genetic pool autonomously developing its own safety factor to prevent frequent fitness drops due to slight design changes. An ideal curve could be drawn to derive an empirical equation for power in function of efficiency, however, given the high dimensionality of the results, it would be an excessive approximation with limited practical use. Median leading-edge thickness for rotor (red data points) and stator (black data points) scatter plots against fitness is shown in Figure 16. In terms of stator data analysis, it is clear that best fitness values correspond to thicknesses between 0.3 mm and 0.45 mm. Rotor data is divided in two different genetic types: best fitness values are found at 0.73 mm or at 0.42 mm. This could be interpreted as the genetic pool developing into two separate species, with different characteristics. High thickness  
Figure 14: Visual comparison between preliminary blade (left) and optimised blade (right) designs. Figure 15: Power against efficiency for all assessed configurations within design objective constraints. elements feature slightly lower efficiencies, and greatly increased power. Lower thickness element, like the final result, feature significantly less power and marginally higher efficiency. This phenomenon occurred as a consequence of the multi-objective nature of the optimisation, and it is statistically likely that more parameters evolved into multiple species. Figure 17 shows the elite member rotor leading edge thickness behaviour over the course of the optimisation. From this graph, one can observe the hub values convergence to higher values compared to the preliminary design analysis, to accommodate for the need of a higher rotor safety factor. Values for the median layer were initially increased, only to be minimised at a later stage of the optimisation. This behaviour is a consequence of the genetic pool prioritising low turbine failure rates, increasing influential parameters to ensure constraints compliance. In this case, the safety factor constraint was likely the cause for this increase. As blade parameters get optimised, failure rates sharply decreased, leading higher fitness elements with lower thicknesses to be more prominent. Tip values were influenced by median values behaviour; however, they clearly were not as influential in design constraints compliance. Figure 16: Leading edge thickness at the median layer vs. fitness for rotor (red) and stator (black). Figure 17: Elite member rotor leading edge thickness against generation number. Figure 18 shows the evolution pattern of stator axial chord. As generation number increases, hub and median values are minimised, while tip values stabilise at a value close to the initial guess. This shows a tendency towards shorter blade as the evidently provide better results. Hub and median values tend to the lower end of their respective ranges, thus suggesting that theoretical values for axial chords are not based on accurate empirical equations. To provide a possible explanation to the phenomenon of unexpected stator axial chord, blade distance was plotted against generation number in Figures 18 and 19, respectively. Blade distance was set up as a function of axial chords, and the graph shows this value being overestimated in preliminary design. It is probable that this parameter is so influential, that having worse than optimal values for all the dimensions that are included in the function used to estimate it is still beneficial. Figure 20 is showing the rotor/stator stagger angle ratio at each layer.