Simulation of the microfluidic mixing and the droplet generation for 3D printing of nuclear fuels

This paper presents the computational fluid dynamics modeling of an additive manufacturing process that is candidate for the production of Gen IV nuclear reactor fuels. The modeled process combines the internal gelation to produce metal hydrous oxides with the 3D ceramic printing to create a green body from these gelled oxides as described by Pouchon (2016). The objective of the simulations is to optimize the process parameters: microfluidic mixing of the internal gelation reagents and generation of droplets of the mixed solutions. The simulations were performed using the OpenFOAM software, and to perform these simulations with the correct solution parameters, the properties of the fluids of interest were measured. The results show that a thorough mixing of the metal solution and the methenamine and urea mixture in a microfluidic mixer can be achieved in tens of milliseconds by either winding the mixing channel to create secondary flows or splitting the solutions inlets to yield additional diffusion interfaces. The optimal droplet size is achieved by using a mechanically vibrating 3D printing head that leads to a frequency-following Rayleigh instability. The results of the simulations suggest the parameters (micromixer geometry, flow rate, vibration frequency and others) that will optimize the mixing efficiency in a microfluidic mixer and the droplet generation process from a 3D printing head.