Analytical modeling of materials properties in metal additive manufacturing

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Abstract

Emerging additive manufacturing (AM) provides a green and sustainable manufacturing approach in an inverse philosophy compared to traditional procedures, benefiting the current global decarbonization strategy. However, AM still needs to address many challenges due to its multi-physical processes in various materials systems or multiple applying situations before implementation in more fields and replacing more places of traditional manufacturing. Specifically, the primary aim of this investigation is to study the microstructural changes that affect material properties, such as elastic modulus and Poisson’s ratio. These changes affect the materials performance, including residual stress, fractures, etc. To achieve this, the characterization of the microstructure of materials, mainly the surface/textures, grain size, and defects, if necessary, is of great importance. In this paper, the texture and grain size simulation for multi-phase materials systems are conducted based on accurate physical stimuli modeling of processing. The influence of microstructural evolution in metal additive manufacturing on material properties is characterized. Several paradigms have been constructed to model and predict manufacturing processes, utilizing physics-based semi-analytical frameworks. Experimental results have been presented to validate the fidelity of the models. It has been observed that the computer-simulated effective elastic modulus, using the same experimental processing parameters, is relatively stable and falls within the range of 109-117 GPa, showing no evidence of being influenced by layer or row settings. Besides, the simulated derivatives under the same settings are stable at around 850-900 MPa, falling within the range of experimental data of approximately 850-1050 MPa, albeit slightly lower. By bridging the gap between AM’s micro- and macrostructures and material properties, this work has the potential to transform the sector and spark a fresh outlook on science.

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