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The macroscopic behavior of polycrystalline materials is largely influenced by the shape, the arrangement and the orientation of crystallites. Different methods have thus been developed to determine the effective behavior of such materials as a function of their microstructural features. In this work, which focuses on polycrystalline materials with an elastic–viscoplastic behavior, the self-consistent, finite element and spectral methods are compared. These common methods are used to determine the effective behavior of different 316L polycrystalline aggregates subjected to various loading conditions. Though no major difference is observed at the macroscopic scale, the hardening rate is found to be slightly overestimated with the finite element method. Indeed, spatial convergence cannot be guaranteed for finite element calculations, even when fine mesh resolutions, for which the computational cost is important, are used. Also, as the self-consistent method does not explicitly account for neighborhood effects, important discrepancies between the self-consistent method and the other methods exist regarding the mechanical response of a specific grain. The self-consistent method nevertheless provides a reasonable description of the average response obtained for a group of grains with identical features (e.g. shape, orientation). [ABSTRACT FROM AUTHOR]

• Microstructure-sensitive framework has been extended and applied to SLM 316L. • As-built surface roughness has been considered explicitly in the finite element model. • Textured microstructure of SLM 316L has been evaluated concerning fatigue strength. • Competitive effects of surface defect and microstructure have been distinguished. This paper aims to study the individual and competitive effects of surface defects and microstructural components in an AM 316L by numerical methods. Based on the microstructure sensitive modeling framework, numerical simulations of models in different surface states with virtual quasi-realistic explicit microstructures are performed. Problems encountered during the establishment of the numerical polycrystalline aggregate model are discussed, including the grain morphology, the strongly textured microstructure with preferential crystallographic directions, roughness and surface defect. A statistical method based on generalized extreme value distribution along with a non-local method is used to describe the stochasticity of microstructural attributes. Simulations of differently configured explicit microstructure models are analyzed and discussed. [ABSTRACT FROM AUTHOR]