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- W4308783445 abstract "For the broader industrial usage of metal additive manufactured parts, especially made by laser powder bed fusion, a better prediction and understanding of the warpage and of eigenstresses within the final part are necessary. Due to the diverse and sophisticated metallurgical and thermal processes during production, physically motivated simulations are rather complex and time consuming. Therefore, various simplifications concerning the process and material models are frequently made, which leads to practicable simulation times at the expense of physical accuracy. This motivates the procedure in this contribution: A multiscale approach combining various modelling levels, in particular regarding the heat source and material model. The model is based on three finite element simulations on different levels and with different specific aims, i.e. the laser scan model, the layer hatch model and the part model. For the smallest scale considered, a sophisticated thermomechanically fully coupled model based on a phase transformation model explicitly considering the powder, molten, and re-solidified material is incorporated. The goal of this detailed simulation is to extract an effective heat source for the next level of simulation, i.e. the layer hatch model. The layer hatch model is used to extract the inherent strains for the part model. With these strains, the remaining deformation and eigenstresses of arbitrary large parts with the same material and laser parameters can be efficiently and directly computed. The capabilities of the present framework are investigated by simulations on the behaviour of a twin cantilever beam, where the effect of different process parameters on the overall material and structural response is carried out." @default.
- W4308783445 created "2022-11-15" @default.
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- W4308783445 date "2022-12-01" @default.
- W4308783445 modified "2023-10-14" @default.
- W4308783445 title "A micromechanically motivated multiscale approach for residual distortion in laser powder bed fusion processes" @default.
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- W4308783445 doi "https://doi.org/10.1016/j.addma.2022.103277" @default.
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