| Summary: | Space domain awareness and the issue of space congestion have become critical topics, particularly with the proliferation of private companies launching large LEO constellations (LLCs), or mega-constellations, including SpaceX’s Starlink and Amazon’s Kuiper. This rapid expansion has led to increased concerns about space debris, potential collisions, and the possibility of reaching a critical threshold known as Kessler syndrome. To study and address these challenges, advanced modeling and simulation techniques are essential. There are largely two methods to for modelling and simulation: particle-in-box (PIB) methods and Monte Carlo techniques. Historically, the simulation tools developed have been closed source due to governments and companies wanting to maintain information security or ensure a profit. However, recently MIT’S ARCLab introduced MOCAT and MOCAT-MC, opensource toolboxes designed to propagate and model the LEO RSO population. This thesis focuses on MOCAT-MC- MIT’s Orbital Capacity Analysis Toolbox Monte Carlo. MOCATMC propagates individual space objects while accounting for various probabilistic factors common to LEO RSOs including mission failure, collision and space weather while open to new capabilities. Utilizing MOCAT-MC, this thesis presents population and density analyses which reveal exponential growth in object populations, particularly at higher altitudes of the LEO regime where Kessler’s critical density is projected to be exceeded. Collision analyses are also performed, highlighting an alarming increase in potential collisions. The results presented even impact active satellites capable of conducting collision avoidance maneuvers (CAMs). Additionally, a brief study on Anti-Satellite (ASAT) test implications reveals that a singular ASAT explosion contribute marginally to debris counts due to the existence of collisions from other sources. This thesis outlines a comprehensive approach to utilizing the MOCAT-MC toolbox and its data outputs in order to reveal some of its many capabilities in studying the LEO orbital population and stability. Overall, this research underscores the urgency of space domain awareness and sustainability. By leveraging MOCAT-MC, the paper provides quantitative insights into LEO object density trends, collision probabilities, and ASAT implications. The findings highlight the escalating risks in space operations and emphasize the need for proactive measures to mitigate space congestion and ensure long-term space sustainability.
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