Uncertainty Quantification of Pollutant Generation During Uncontrolled Re-entry with an Open Source Re-entry Simulator

In space sustainability the so-called “design for demise” (D4D) approach is advocated as the most sustainable option for the end-of-life of Low Earth Orbit (LEO) spacecraft, the goal being that a minimal footprint of re-entering debris mass survives to ground. Instead it is considered preferable that a majority of spacecraft mass is vaporised or aerosolised in the upper atmosphere. As such it is vital that the nature of the generation of these upper-atmospheric pollutants by demising debris is well understood. Such research sits at the intersection of aerospace engineering and atmospheric science, this work seeks to explore a vehicle-specific engineering analysis.

Recent work on the open-source TransAtmospherIc FlighT SimulAtioN tool (TITAN) developed at the University of Strathclyde has enabled the use of the software as an uncertainty quantification tool. This functionality is applied here in order to explore how the distribution of upper-atmosphere mass emission during demise of a typical LEO satellite can be characterised.

In this work the re-entry of a representative model of a tumbling Starlink satellite is simulated, accounting for 6 Degree-of-Freedom trajectory dynamics and transatmospheric aerothermodynamical effects. Perturbations in terms of initial spacecraft state and temperature, as well as flight-relevant atmospheric conditions, are applied. Then a Monte Carlo campaign is used to recover distributions of emitted species across altitude. Due to the high similarity of Starlink satellites such an approach can be considered generalisable across the constellation, enabling mass emissions predictions to be extended to a global scale.

This work hopes to provide both a tutorial on how such analyses can be performed as well as giving information from a spacecraft-specific perspective that can be applied in atmospheric modelling approaches and also potentially used to inform future compliance behaviours and life cycle analyses.