Fluids behavior is hard to model in microgravity ( See the following ISS video)
The way bubbles form and interact inside the tank is surprising and difficult to model. However, modelling the sloshing is required to build better observation satellites.
Scientists have a good idea on how liquids slosh in Earth gravity. However, propellant sloshing in microgravity has a non-trivial effect on most Earth-orbiting satellites and can adversely affect satellite performance. Indeed, spacecraft carry large mass fractions of liquid propellant, as large as 38% (Astra 2A) of total launch mass. Sloshing may result in inaccurate spacecraft pointing, also known as “jitter”.
My Ph.D. student, Anthony Bourdelle (funded by the French Aerospace Lab and Space Agency), is currently finishing writing his Thesis on this topic. He recently proposed novel modeling and control tools in order to better estimate and reject the sloshing destabilizing torque acting on a satellite. Roughly speaking, the dynamical model we used is more nonlinear than the classical ones based on the Equivalent Mechanical Model. Anthony received a best student paper award in “Flight Dynamics, GNC and Avionics” at the EUCASS conference last summer.
I am happy to share the following references with interested researchers:
Bourdelle, A., L. Burlion, J.-M. Biannic, H. Evain, S. Moreno, C. Pittet, A. Dalmon, S. Tanguy, and T. Ahmed-Ali, “Towards New Control Design Oriented Models for Fuel Sloshing in Observation Spacecraft”, in Proceedings of the AIAA Scitech 2019 Forum, 2019.
Bourdelle, A. J.M. Biannic, H. Evain, S. Moreno, C. Pittet, and L. Burlion, “Propellant Sloshing Torque H∞ based Observer Design for Enhanced Attitude Control”, in Proceedings of the IFAC symposium on Automatic Control in Aerospace, 2019.
Bourdelle, A., J-M. Biannic, H. Evain, C. Pittet, S. Moreno, and L. Burlion, “Modeling andcontrol of propellant slosh dynamics in observation spacecraft,” in Proceedings of the 8th European Conference for Aeronautics and Space Sciences (Madrid, Spain, 1-4 July2019).
My other graduate student, Mike Fogel, is currently looking at some machine learning algorithms in order to treat the sloshing problem like a "black box", with no previous knowledge of the physics involved. This alternative approach is also very promising!