Giacomo Acciarini
About
My research project
Stochastic continuation for space trajectory design in uncertain environmentsAn essential part of any spacecraft mission is the design, planning, and operation of robust and fuel-efficient trajectories that can fulfill mission requirements while coping with the harsh reality of the space environment. These trajectories are traditionally engineered in a two-step approach. First, orbits are designed in a deterministic fashion, assuming that the dynamics and state of the spacecraft are known with infinite accuracy. Secondly, the robustness of these initial conditions is tested against model uncertainties and knowledge errors using brute-force Monte Carlo simulations that explore different realizations of the uncertainty set. This two-step approach is not only time-consuming but also contributes to slowing down the mission development process as the robustness of candidate orbits can only be assessed a-posteriori.
The goal of this project is to leverage advanced mathematical tools to directly calculate, up to a certain confidence level, regions of the phase space where the spacecraft is expected to orbit depending on the time scales and uncertainties of a user-defined problem. The numerical procedures will be general by nature and therefore applicable to a variety of spacecraft missions, including ESA’s Hera, aiming towards the binary asteroid 65803 Didymos, and the JAXA-lead MMX, destined for Phobos.
Supervisors
An essential part of any spacecraft mission is the design, planning, and operation of robust and fuel-efficient trajectories that can fulfill mission requirements while coping with the harsh reality of the space environment. These trajectories are traditionally engineered in a two-step approach. First, orbits are designed in a deterministic fashion, assuming that the dynamics and state of the spacecraft are known with infinite accuracy. Secondly, the robustness of these initial conditions is tested against model uncertainties and knowledge errors using brute-force Monte Carlo simulations that explore different realizations of the uncertainty set. This two-step approach is not only time-consuming but also contributes to slowing down the mission development process as the robustness of candidate orbits can only be assessed a-posteriori.
The goal of this project is to leverage advanced mathematical tools to directly calculate, up to a certain confidence level, regions of the phase space where the spacecraft is expected to orbit depending on the time scales and uncertainties of a user-defined problem. The numerical procedures will be general by nature and therefore applicable to a variety of spacecraft missions, including ESA’s Hera, aiming towards the binary asteroid 65803 Didymos, and the JAXA-lead MMX, destined for Phobos.
Publications
The risk of collisions in Earth’s orbit is growing markedly. In January 2021, SpaceX and OneWeb released an operator-to-operator fact sheet that highlights the critical reliance on conjunction data messages (CDMs) and observations, demonstrating the need for a diverse sensing environment for orbital objects. Recently, the University of Oxford and the University of Surrey developed, in collaboration with Trillium Technologies and the European Space Operations Center, an opensource Python package for modeling the spacecraft collision avoidance process, called Kessler. Such tools can be used for importing/exporting CDMs in their standard format, modeling the current low-Earth orbit (LEO) population and its short-term propagation from a given catalog file, as well as modeling the evolution of conjunction events based on the current population and observation scenarios, hence emulating the CDMs generation process of the Combined Space Operations Center (CSpOC). The model also provides probabilistic programming and ML tools to predict future collision events and to perform Bayesian inference (i.e., optimal use of all available observations). In the framework of a United Kingdom Space Agency-funded project, we analyze and study the impact of megaconstellations and observation models in the collision avoidance process. First, we monitor and report how the estimated collision risk and other quantities at the time of closest approach (e.g. miss distance, uncertainties, etc.) vary, according to different observation models, which emulate different radar observation accuracy. Then, we analyze the impact of future megaconstellations on the number of warnings generated from the increase in the number of conjunctions leading to an increased burden on space operators. FCC licenses were used to identify credible megaconstellation sources to understand how a potential consistent increase in active satellites will impact LEO situational safety. We finally present how our simulations help understand the impact of these future megaconstellations on the current population, and how we can devise better ground observation strategies to quantify future observation needs and reduce the burden on operators.