History Reduction Techniques for Simulation of Additive Manufacturing and Physically based Material Modeling
Sammanfattning: In this thesis, finite element (FE) simulations of additive manufacturing (AM) and physically based material modeling are presented. AM is a process where the component is built layer-wise. The material undergoes repeated heating and cooling cycles when layers are added, which may result in undesired deformation and residual stress in the built component. The choice of process parameters and scan strategy affect the resulting residual stress. Simulations can be used to support the experimental determination of process parameters and scan strategy. AM processes often comprise many added layers, and the passes are lengthy relative to their thicknesses and widths. This makes the FE simulations computationally expensive, with many elements and time steps. In this work, AM processes have been simulated with the FE-method using a lumping technique. This technique allows fewer time steps and a coarser mesh. Thermal behavior, deformation, and residual stresses have been simulated and compared with experiments. The simulations show that, by using the lumping technique, the computational effort can be reduced significantly with retained accuracy for the resulting temperature and deformations. The residual stresses become somewhat smaller. Alloy 625 is a nickel-based superalloy used in high-temperature applications owing to the hightemperature strength. The material is difficult to manufacture by conventional machining owing to excessive tool wear and low material removal rates. Thus alloy 625 is a material appropriate for the AM technology with its near-net shape potential. An existing, physically based flow stress model has been further developed to fit the mechanisms typical for alloy 625. This model gives an accurate mechanical behavior and capture viscoplasticity, creep, and relaxation. The physically based model has been calibrated versus compression tests and validated with a stress relaxation test performed in a Gleeble 3800 machine. The predicted relaxation was in good agreement with the measured relaxation. The usage of this kind of material model is expected to improve the prediction of the material behavior during the AM process and, thereby, the overall prediction of the AM process.
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