Aerodynamic Stability Analysis and Design of a Re-Entry Capsule for a Demise Assessment Platform

From the beginning of the space age, the number of debris in Earth’s orbit has become a growing concern. This increase poses potential hazards both on Earth, due to the eventual decay of orbital debris, and in space, due to the risk of collisions between orbiting bodies. Understanding the re-entry and demise of space debris is crucial for improving predictive models and mitigating risks on ground. Additionally, there is a pressing need to minimize the generation of new debris by incorporating this consideration into the design phase of missions and satellites—an approach known as Design-for-Demise (D4D). The Destructive Re-entry Assessment Container Object (DRACO) mission aims to enhance our understanding of spacecraft debris re-entry through a dedicated flight experiment, addressing uncertainties in breakup processes. Given limitations in ground experiments and remote observations, DRACO will transmit data obtained from controlled breakup scenarios to improve predictive capabilities. This thesis is conducted within the framework of the DRACO project, focusing on the capsule’s aeroshape design that will store data during re-entry as part of the DRACO platform. The capsule will detach from the platform after the main breakup events and transmit gathered data to a satellite constellation during its descent. The capsule design must ensure passive stability to facilitate data transmission and proper parachute deployment. To achieve this, an initial literature review gathered information on common capsule shapes and their aerodynamic stability characteristics. Subsequently, a selection of capsule geometries with favourable performance and flight heritage was used to undergo further analysis using a modified Newtonian theory solver and a trajectory simulation tool. Ultimately, a single DRACO capsule design was proposed, incorporating optimal features identified from the initial capsule selections. Parametric optimisation using the same numerical tools ensured maximised performance and compliance with internal component allocation and mission constraints.