## 3 Results
### Generate Market Scenarios and Run First Surplus Value Assessment  
From Equation (1) it can be noted that assessing the surplus value of the design options requires to make assumptions regarding the markets and missions of megaconstellation business scenarios. As presented in Section 2.2, the size of a megaconstellation is likely to depend on the trade-off between the need for coverage and the launch cost incurred to introduce the satellites in orbit [40]. The lower the altitude the more satellites have to be built to provide coverage. On the other hand, the higher the altitude, the higher each launch cost. For this reason, the industrial partners were interested to apply the surplus value model on three market scenarios, each distinguished by different mission and economical characteristics:  
* Market 1: this market considers the case of a more 'conservative' megaconstellation with a relatively small number (300) of heavy satellites to be operated in \"high-LEO\" orbits (1500 km). * Market 2: this market represents the case of a megaconstellation with high number (900) of medium-sized satellites that operate in \"medium-LEO\" orbits (1200 km). * Market 3: this scenario features a more advanced business scenario in which a very high number (4000) of small satellites operate in \"low-LEO\" orbits (800 km). Also, this market features the case of more favorable conditions in terms of launch cost (e.g., considering the case of a cheaper launcher being developed) and a more aggressive launch strategy with a higher number of satellites that can fit in a single launch. The input data characterizing each of these market scenarios are detailed in Table 1.  
For the first run of the surplus value model, the different options have been analyzed considering only Market 1. Figure 5 displays the surplus value over the lifecycle. The actual values for the surplus value have been omitted. For the first run of the surplus value model, six options have been considered. The reason for this is that in the flexible options (Option 3 and Option 4 in Figure 4) the xenon or krypton have been simulated separately. The model has been run for 30 years. In Figure 5, only the results for the first 15 years are visualized. The data regarding SV has been normalized to preserve company sensitive information. The value of each SV has been normalized based on the highest value (i.e., the highest SV corresponds to 1 in the normalized scale). To further comprehend the results of the surplus value model, the tradespace between lifecycle costs (LCC) and SV is shown in Figure 6. The data regarding SV and LCC have been normalized. The values of each SV and LCC have been normalized based on the highest value (i.e., the highest SV and LCC corresponds to 1 in the normalized scale). The results indicate:  
* Option 1 (single development xenon) presents highest surplus value and lowest LCC. * The high test and qualification costs (i.e., non-recurring costs) involved in the development a high-performance and reliable krypton option (equal to a mature xenon option available today) does not overweight its benefits. * Developing a flexible option (compatible with both xenon and krypton) in an efficient way (with lower test and qualification costs than a high-performance xenon and krypton option, Figure 6) does not overweight its benefits, due to the lower performance levels and lower reliability levels involved in this option. * Increasing the reliability levels on the flexible option by adding a redundant thruster and TSU does not overcome its benefits, as additional costs and weight are introduced due to the addition  
Figure 5: Surplus value (SV) for the different options, considering Market 1. The data regarding surplus value have been normalized to preserve company sensitive information. of these new components. Also, the test and qualification are increased with this alternative, as the TSU needs to be developed, tested and qualified.