Coating is a very challenging application for numerical engineers due to the very small scales (usually microns) envolved during the process.

FLOW-3D is a very useful simulation tool for this kind of application, due to its unique capabilities in tracking the fluid surface.
The software is born in Los Alamos laboratories under the hands of the inventor of the VOF method, today agreed as the best numerical method for tracking free surface flows. Thanks to this, FLOW-3D has superior capabilities in simulating free surface transient flows, exactly like the thin layer of any metal or fluid, in a complex moving environment.
Users can quickly import any 3D cad geometry into the software, setting the fluid to simulate, electrical properties or working condition, and run the calculation.

Simulation provides in output several information of interest for coating application:
    • pressure and velocity value in every point at every time-frame
    • temperature field at every time-frame
    • particle dynamics
    • surface tension forces
    • contact angles/capillarity effects
    • fluid film thickness and residence time
    • flow efficiency
    • electric charge distribution
    • deformation of walls or membranes
    • forces produced by fluid on the container

Additionally, users can add in the simulation a very rich multi-physics, like: multiple solid moving objects, deformable components, evaporation/condensation phenomena, electrically charged particles, or surface tension and capillarity effects.

Nowadays, to get into the market with the highest quality level product as possible, it is often used to perform an optimization study of the own coating system, for example to control at the best the film thickness.
To search for very extremum performance in a very quick way, try the software IOSO Technology (by SigmaTechnology).
IOSO will work in loop with your modeling tools, using a new optimization "push-button" technology, that adopt a Self-Organization Strategy making use of up to 7 different well-known optimization methods (gradients, genetic, neural network, search region,...).