The main goal of the project is to provide experimentally validated predictive computational tools that can be used to tailor spray drier operations. Spray drying is a process used in many industrial areas to produce powders from a liquid slurry. The solution or suspension is atomized in fine droplets that are dried in a hot air stream. Collisions between droplets, partially and completely dry particles lead to different outcomes among bouncing, coalescence, agglomeration and break-up. These phenomena influence the size and morphology of the final product so their prediction is essential for modelling spray drier processes.The first part of the project is based on the investigation of viscous effect on droplet interactions. Binary droplet collisions are analyzed numerically through DNS and experimentally through droplet generator device.
The investigation based on the micro scale will be used to update and close the macro scale model. A stochastic-DSMC (Direct Simulation Monte Carlo) model can be used to simulate isothermal water sprays arising from high pressure nozzles. The main goal of the second part of the project is the expansion of the model validity to non-isothermal sprays of dairy products, covering the full range from droplet to particles. The predictive capabilities of the DSMC model will be improved in order to replace the measurements currently needed to describe the agglomeration rate. Also the macro scale part comprehends an experimental validation with pilot scale spray drying tests.
This research project is carried out with funding by Tetra Pak CPS, Heerenveen.