Dr Juan Padrino

• Computational fluid dynamics (CFD) of multiphase flows with or without phase change – Finite volume and boundary element methods (for creeping and potential flows) – Analytical methods of mathematical physics applied to fluid mechanics problems, e.g., lubrication approximation and perturbation methods.
• Microfluidics of liquids and gases and fluid flows in nanotechnology applications.
• Numerical and theoretical modelling of non-Newtonian flows, including viscoelasticity.
• Multiphase flow in porous media, including Net Zero applications, such as hydrogen storage and CO2 sequestration.
• One-dimensional multiphase flow in pipelines with or without fluid structure interaction – Applications to flow assurance.

Throughout the various phases of lithium-ion battery manufacturing, including coating, drying, and calendering, a significant amount of resources is wasted in trial-and-error cycles attempting to correct several defects arising in these processes, which can severely compromise the performance of the batteries.  To reduce this waste, numerical and theoretical modelling has been identified as a key tool for analysis. Juan’s work focuses on applying computational fluid dynamics (CFD) and analytical tools to model the flows arising in these processes, with the goal of revealing and understanding their attributes and finding remedies to those defects affecting battery performance.  In this project, Juan uses open-source software, such as OpenFOAM (RheoTool for viscoelastic fluids) and commercial programs including Ansys Polyflow, Polymat, and Fluent.