Developing a DEM-Coupled OpenFOAM solver for multiphysics simulation of additive manufacturing process

in Scipedia.com (2022, December)

Powder-based additive manufacturing technologies, specifically selective laser melting, are challenging to model due to the complex, interrelated physical phenomena that are present on multiple spatial ... [more ▼]

Powder-based additive manufacturing technologies, specifically selective laser melting, are challenging to model due to the complex, interrelated physical phenomena that are present on multiple spatial scales, during the process. A key element of such models will be the detailed simulation of flow and heat transfer throughout the melt pool that is formed when the powder particles melt. Due to the high temperature gradients that are rised inside the melt pool, Marangoni force plays a key role in governing the flows inside the melt pool and deciding its shape and dimensions[1]. On the other hand the mass and heat transfer between the melt and the powder also has a signifacnt role in shaping the melt pool at the edges. In this study we modified an OpenFOAM solver(icoReactingMultiphaseInterFoam) cou- pled with an in-house developed DEM code known as eXtended Discrete Element Method or XDEM which models the dynamics and thermodynamics of the particles[2]. By adding the Marangoni force to the momentum equation and also defining a laser model as a boundary Condition for Liquid-Gas Interface, the solver is capable of modeling selective laser melting process from the moment of particle melting to the completion of the so- solidified track. The coupled solver was validated with an ice-packed bed melting case and was used to simulate a multi-track selective laser melting process. [less ▲]

On the Reduction of Computational Costs for Tungsten Powder Bed Processes

Scientific Conference (2022, May 31)

During the Discrete Element Method (DEM) representation of powder bed processes (e.g. tungsten oxide reduction, tungsten carbide synthesis, selective laser sintering) a numerical solution for each single ... [more ▼]

During the Discrete Element Method (DEM) representation of powder bed processes (e.g. tungsten oxide reduction, tungsten carbide synthesis, selective laser sintering) a numerical solution for each single particle is impractical due to the extremely high number of particles (e.g. 10^12). However, in such processes, particles in the vicinity of each other observe low gradients concerning their thermodynamic state. This characteristic can be exploited to avoid solving repeatedly numerically equivalent equation systems. This contribution presents two numerical methods aiming to reduce the computational costs of DEM approaches for the thermochemical conversion of powder beds. In the two methods after an appropriated numerical treatment, a group of particles under similar boundary conditions is substituted by a single-effective-entity. Consequently, the entire powder space is divided into sub-domains to be solved. The methods result in considerable lower number of equations that increase computational efficiency and enable feasible time simulations. The applications of the industrial synthesis of tungsten powders and the selective laser sintering (SLS) of powder metals are presented and discussed. [less ▲]