The B.USOC team operated the Foam Coarsening experiment (FOAM-C) devoted to the study of the hydrodynamic properties of aqueous foams in micro-gravity.
From March 9 until October 13, 2020, 17 calibration runs and 64 science runs were performed to observe the coarsening of bubbles within the foam for 23 sample cells containing an aqueous detergent solution. Depending on the sample cell composition, the observations lasted between a few hours and several days.
The experiment was executed inside the Fluid Science Laboratory (FSL) onboard the International Space Station (ISS) and required six times the intervention of an astronaut to load and unload the experiment container inside FSL or to exchange units of sample cells, including five times by NASA astronaut Chris Cassidy.
B.USOC downloads and archives the images and data of each experiment run for near real time retrieval and treatment by the scientists connected at their User Home Base (UHB).
Why in microgravity?
The study of wet foams coarsening on Earth is difficult because gravity pulls the liquid between the bubbles downwards, and the small bubbles shrink while the larger ones tend to grow at the expense of others.
In micro-gravity wet foams are more stable because the liquid does not drain as on Earth. This allows studying the phenomena of a bubble slowly becoming bigger and bursting.
Theoretical approaches of drainage rely on assumptions that are only valid for dry foams. The physics of wet foams is therefore poorly understood. Improving the characterization of wet foams is hence a major goal of the FOAM-C experiment.
Solid and liquid foams are used across a variety of industries:
- cleaning products
- cleaning oil from water
A better understanding of foams physics could help improve their control and process design in industry for future utilization.
Feedback from FOAM-C Principal Investigator D. Langevin, CNRS research director
The foam team was pleased with the collaboration with the B-USOC. Without you, we would have lost a lot of opportunities, as the experience was a series of surprises: our forecasts were based on models that proved to be unsuitable, we will now have to find better ones. But for us, these unexpected results are very stimulating. We had to adapt the measurement times, parallel some of them and carry out tests. Your team has always been very understanding and very efficient.