Master thesis and internship[BR]- Master's thesis : Methodology Development for In-Orbit Resources Optimization for SmallSats in Sun-Synchronous Orbits - through extensive use of NASA's GMAT and Multi-Objective Value Analysis[BR]- Integration Internship : LuxSpace S.

Abstract

The present thesis provides an adaptable methodology for in-orbit satellite resources optimization in terms of propulsive and power generation configurations; it is applied to LuxSpace's Triton-X missions.

Triton-X is a family of SmallSat platforms for High-Performance Earth Observations (H\#EO) applications in Sun-Synchronous Orbits. It presents three different size classes, namely Light, Medium and Heavy. With the purpose of providing the best services for different mission objectives, it requires modularity and scalability of all parts and subsystems that need to be tailored to the client's individual needs. The present thesis and all methodologies, therefore, have to be as payload-agnostic as possible.

A useful combination of NASA's General Mission Analysis Tool (GMAT), Mathwork's Matlab, and Microsoft Excel is employed to allow for the complete automatization of the methodology, overcoming the limitations of the GMAT software while still taking advantage of its powerful resources. The process is able to respond to pre-set mission constraints and customizable user inputs to provide an optimized solution to the customer.

Satellites in low earth orbit are subject to relevant perturbations requiring correction maneuvers. In particular, gravitational anomalies tend to move the satellite away from the Sun-Synchronous conditions, while the atmospheric drag and solar radiation pressure cause the orbit to lose energy and decay. A spacecraft must be able to respond to such perturbations by employing propulsive maneuvers that require on-board fuel and power. Due to the limited dimension of SmallSats and the ever-growing commercial request for maximization of payload resources, the propellant stored on board must be minimized as much as possible while ensuring the mission's fulfillment; however, this must not be achieved at the expense of the customer's requirements. On the other hand, the system must be able to respond to the energy requisites of all subsystems. Both goals call for an optimization method that does not only take into account the mission objectives but their effect on the overall system and budgets as well.

The introductory part of the thesis includes the first two chapters, introducing the framework and state-of-the-art necessary for a better understanding of the work. Chapter 3 explains the GMAT software, together with the interactions and interface allowing it to communicate with Matlab.

The first part of the thesis then describes a method for multi-objective optimization of propulsive resources; these include the mass of the propulsive system, the fuel mass, the availability for the mission, the price, and the needed dv for the corrections maneuvers. The constraints and conditions guiding the application stem from the ranges of applicability and commercial targets of the platform. The orbits considered are frozen SSOs at Low Earth altitude, from 400 to 800 km, with any Local Time of the Ascending Node (LTAN) - prioritizing the analysis of the dusk-dawn and 10:00-14:00 regions. This part is divided into three chapters, describing respectively the general workflow, the details of the studies performed, and the outputs of the analysis. A catalogue of the available thrusters as of May 2023 has been created thanks to the information provided by the representatives of companies active in the field of SmallSats propulsion.

On the other hand, the second part performs the optimization of the solar array configuration to maximize the power generation while keeping at bay the complexity of the solution. This requires an accurate study of the solar fluxes, which exploits the powerful capabilities of GMAT. The potential for power generation is explored in three different case studies characterized by the same orbital parameters but different values of LTAN. The same division as for the first part is applied here.

Lastly, future developments and possible streams of improvement of the thesis are presented in the last part.

In both topics, the tool employed for the multi-purpose optimization is the Multi-Objective Value Analysis, which allows considering both quantitative and qualitative evaluation measures. The results are adherent to theoretical predictions and demonstrate the tool's adaptation capacity to the case-specific requirements and inputs.