Microstructure evolution of Al-Si-10Mg in direct metal laser sintering using phase-field modeling

Jyotirmoy Nandy , Hrushikesh Sarangi , Seshadev Sahoo

Advances in Manufacturing ›› 2018, Vol. 6 ›› Issue (1) : 107 -117.

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Advances in Manufacturing ›› 2018, Vol. 6 ›› Issue (1) : 107 -117. DOI: 10.1007/s40436-018-0213-1
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Microstructure evolution of Al-Si-10Mg in direct metal laser sintering using phase-field modeling

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Abstract

Direct metal laser sintering (DMLS) has evolved as a popular technique in additive manufacturing, which produces metallic parts layer-by-layer by the application of laser power. DMLS is a rapid manufacturing process, and the properties of the build material depend on the sintering mechanism as well as the microstructure of the build material. Thus, the prediction of part microstructures during the process may be a key factor for process optimization. In addition, the process parameters play a crucial role in the microstructure evolution, and need to be controlled effectively. In this study, the microstructure evolution of Al-Si-10Mg alloy in DMLS process is studied with the help of the phase field modeling. A MATLAB code is used to solve the phase field equations, where the simulation parameters include temperature gradient, laser power and scan speed. From the simulation result, it is found that the temperature gradient plays a significant role in the evolution of microstructure with different process parameters. In a single-seed simulation, the growth of the dendritic structure increases with the increase in the temperature gradient. When considering multiple seeds, the increasing in temperature gradients leads to the formation of finer dendrites; however, with increasing time, the dendrites join and grain growth are seen to be controlled at the interface.

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Additive manufacturing / Direct metal laser sintering (DMLS) / Phase field modeling / Microstructure

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Jyotirmoy Nandy,Hrushikesh Sarangi,Seshadev Sahoo. Microstructure evolution of Al-Si-10Mg in direct metal laser sintering using phase-field modeling. Advances in Manufacturing, 2018, 6(1): 107-117 DOI:10.1007/s40436-018-0213-1

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