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2024 | OriginalPaper | Buchkapitel

Modelling Temperature Distribution in Multi-track Multi-layer Selective Laser Melted Parts: A Finite Element Approach

verfasst von : Anuj Kumar, Mukul Shukla

Erschienen in: Advances in Mechanical Engineering and Material Science

Verlag: Springer Nature Singapore

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Abstract

Selective laser melting (SLM) is an additive manufacturing (AM) process suited for printing three-dimensional metallic components. Throughout the SLM process, the thermal characteristics are crucial in ensuring the build quality of the print. Therefore, it becomes essential to determine the temperature distribution of the SLMed parts. Experimental approaches to address this issue are capital and time intensive. Numerical modelling studies for temperature distribution generally simulate single tracks, which cannot be extrapolated for the whole SLMed part. In this study, the multi-track, multi-layer SLM builds of IN718 were simulated using a three-dimensional finite element model. The temperature-dependent material properties were considered in modelling, and the laser scanning beam was described as a moving volumetric heat source. The temperature distribution on printed layers was evaluated, after which thermal profiles from simulated layers were extracted, and the permissible limit exercise was performed to identify potential hotspots. The predicted thermal history can also be used to optimise SLM process parameters. Further, the effects of scan strategy (layer start and rotation angle) on the temperature distribution were studied. It is evident from the results that the layer rotation angle affects the thermal history as the length of the scan vector changes depending upon the scan strategy used in a layer. This modelling approach can be utilised to further develop the microstructure evolution based on the simulated thermal history for SLMed parts.

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Metadaten
Titel
Modelling Temperature Distribution in Multi-track Multi-layer Selective Laser Melted Parts: A Finite Element Approach
verfasst von
Anuj Kumar
Mukul Shukla
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-5613-5_25

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