Abstract
Numerical simulation is a powerful tool for understanding the complex physics of metal additive manufacturing (MAM) processes and to provide guidelines for optimization of the process conditions. The fast kinetics and highly localized nature of the involved phenomena demand high levels of time and space discretization for MAM simulations which significantly increases the computational costs. The existing simplified simulation approaches apply gross approximations to overcome the numerical cost barrier. This study proposes a multiscale approach which breaks down the problem into two scales of local and global simulations. The method argues that a high level of discretization is only required for capturing the physics of fast-kinetics phenomena occurring in the vicinity of the melt-pool, while a much coarser discretization is applicable for the rest of the simulation domain. As a particular type of adaptive submodeling technique, the results of fine-mesh local simulations around the moving melt-pool are combined with the outcome of a coarse-mesh global solution to provide reliable predictions at a significantly reduced computational cost. The efficiency and reliability of the proposed idea has been evaluated for 2D thermal simulation of the selective laser melting process. The outcome of the exercise demonstrates that the methodology can reduce the computational cost of the simulations by an order of magnitude with minimal loss of accuracy.
Highlights
Commercial additive manufacturing (AM) was first introduced in 1987 with stereo-lithography (SL) from 3D Systems [1]
These results demonstrate the effectiveness of the multiscale approach for reducing the computational cost of AM simulations
An adap tive local-global multiscale simulation approach is introduced with the aim of reducing the computational costs
Summary
Commercial additive manufacturing (AM) was first introduced in 1987 with stereo-lithography (SL) from 3D Systems [1]. It has been shown in [21,37,46,47] that employment of an adaptive re-meshing strategy in high-fidelity continuum FE models, provides reliable SLM temperature profiles at reduced computational costs In this approach, the mesh density near the melt-pool is kept high adap tively in order to capture the large thermal gradients, while it is re duced in the rest of the body. A small adaptive-local model with fine level of time and space discretization moves with the laser and solves the temperature field around the melt-pool, while the global simulation uses large ele ments and time increments to provide reliable thermal profiles far from the melt-pool. Material properties - Temperature dependent thermal conductivity, density, and specific heat - Heat transfer in the melt-pool due to convection was considered by artificially increasing the thermal conductivity in the liquid state
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