Computational Fluid Dynamics and Machine Learning as tools for Optimization of Micromixers geometry. (arXiv:2203.02498v1 [physics.flu-dyn])

This work explores a new approach for optimization in the field of
microfluidics, using the combination of CFD (Computational Fluid Dynamics), and
Machine Learning techniques. The objective of this combination is to enable
global optimization with lower computational cost. The initial geometry is
inspired in a Y-type micromixer with cylindrical grooves on the surface of the
main channel and obstructions inside it. Simulations for circular obstructions
were carried out using the OpenFOAM software to observe the influences of
obstacles. The …

arxiv computational fluid dynamics geometry learning machine machine learning optimization physics tools