Speaker
Description
This thesis presents a stochastic assessment of destructive re-entry for Low-Earth Orbit (LEO) spacecraft, addressing the growing concern over space debris and uncontrolled re-entries. The study aims to improve the understanding of uncertainties in calculating ground risk, thereby ensuring compliance with Space Debris Mitigation (SDM) requirements.
One critical challenge addressed in this research is the lack of comprehensive studies on satellite re-entry, which leads to significant uncertainties often overlooked in verifying SDM requirements. Current guidelines do not fully account for variables such as atmospheric fluctuations, material degradation, and unpredictable re-entry trajectories. This gap raises concerns about whether satellites, assumed to be compliant, would still meet the requirements if these uncertainties were considered.
Monte Carlo simulations, using the pyDRAMA software extension, assess re-entry risks by modeling variations in initial conditions, material properties, and environmental factors, offering a deeper understanding of potential outcomes. This probabilistic approach informs the design of spacecraft components more likely to survive re-entry, such as reaction wheels, magnetorquers, tanks, batteries, and electronic units, reducing the threat to human life and property on the ground.
By incorporating stochastic methods, this research demonstrates how space systems can be designed to withstand unpredictable challenges, ultimately contributing to safer, more successful missions. It also emphasizes the need for further research to ensure compliance with SDM guidelines when uncertainties are fully accounted for.
