Multi-scale modeling for prediction of residual stress and distortion in Ti–6Al–4V semi-circular thin-walled parts additively manufactured by laser powder bed fusion (LPBF)

Abstract

Despite many advantages of metallic additive manufacturing technology (AM), the difficulties in fully observing and modeling the complex nature of the process prevent its wide implementation in different industry sectors. There have been significant efforts during the last decade to develop reliable models to predict temperature field, melting stage, residual stresses and distortion during a material deposition in AM processes, in order to understand the complex process–structure–property relations in different scales, from powder particle to the whole part. In this study, a mechanical and thermo-mechanical computational methods are implemented to trade off the assessment between accuracy and computational cost of the process simulation. By taking advantage of a multiscale approach to reduce the computational cost and time while achieving promising accuracy, two scaled-models and non-scaled models with various levels of fidelity’s discretization were developed. The fidelity level is defined in space by allocating different numbers of physical layers of powder deposition to the finite element and in time by the time increment definition in numerical simulations. The commercial finite element software ABAQUS-implicit associating AM-plugin is utilized for modeling the printing process. The high-fidelity level for scaled part modeling duplicates the process and guides the medium-fidelity level reducing the computational resources needed. Then, by achieving the adequate configuration from the aforementioned level, the non-scaled model with the real dimensions of the experiments is simulated. Subsequently, the low-fidelity level is implemented for the real scale part utilizing the inherent strain method, taking into account the residual strains. The different approaches are compared, showing that the inherent strain method is more efficient in terms of accuracy and computational cost than the multiscale thermo-mechanical method.