Micromechanical Modeling of AlSi10Mg Processed by Laser-Based Additive Manufacturing: From as-Built to Heat-Treated Microstructures

Abstract

The unique microstructure of the alloy AlSi10Mg produced by the laser-based powder bed fusion of metals (PBF-LB/M) provides high-strength and high-strain-hardening capabilities of the material. The microstructure and mechanical properties of 3D-printed, i.e., additively manufactured, AlSi10Mg are significantly altered by post-building heat-treatment processes applied in order to tailor the final properties of the parts. Using an accurate computational model to predict and improve the mechanical performance of 3D-printed samples considering their microstructural features can accelerate their employment in envisaged applications. The present study aims to investigate the correlation between microstructural features and the mechanical behavior of as-built, direct-aged, and T6 heat-treated samples of PBF-LB/M AlSi10Mg under tensile loading using experiment and microstructure-sensitive modeling approaches. Nanoindentation tests are used to calibrate the parameters of the constitutive models for the Al and Si-rich phases. The experimental investigations revealed that heat treatment significantly changes the sub-grain morphology of the Si-rich phase, and this can have a considerable effect on the mechanical behavior of the components. The effect of the modeling of the Si-rich phase in the representative volume elements on the prediction of mechanical behavior is investigated using the J2 plasticity model. The combination of the crystal plasticity model for Al and the J2 plasticity model for the Si-rich phase is used to predict the tensile properties of the as-built and heat-treated states. The predicted results are in good agreement with the experimental results. This approach can be used to understand the microstructure–property relationship of PBF-LB/M AlSi10Mg and eventually tailor heat treatment for PBF-LB/M AlSi10Mg based on the requirement of the application.

Multiphysics multi-scale computational framework for linking process–structure–property relationships in metal additive manufacturing: a critical review

“…For instance, Figure 43 illustrates a typical CPFEM framework to obtain microstructure sensitive tensile loading simulation for LPBF of AlSiMg component. As shown, to generate synthetic microstructural representation (RVE), the authors utilised the open-source software package Kanapy [462]. The Kanapy software discretises the RVE into a sufficient number of voxels to emulate experimental microstructural representation, i.e.…”

“…In most cases, time-consuming micromechanical tests (i.e. Nano-indentation tests [462]) are required, which probe individual grains. In addition, an inverse problem is needed to be solved (i.e.…”

“…calibration of constitutive material parameters until the simulation results match with experiments). For instance, in the CPFEM framework discussed above [462], the Nelder-Mead algorithm was employed along with Nano-indentation experiments to obtain material parameters. Recently, the major thrust has been given towards using the data-driven algorithm to get constitutive material parameters [463].…”

“…Note that in Figure 43, the blue curve denotes the j2 plasticity model, which deviates from the experimental stress–strain behaviour. Thus, it can be concluded that the CPFEM framework provides a robust virtual/digital platform to understand the s–p and p–s–p response in MAM.

Figure 43. Illustration of steps involved in development of CPFEM framework to simulate microstructure sensitive tensile loading of AlSiMg component fabricated using LPBF [462].

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“…Illustration of steps involved in development of CPFEM framework to simulate microstructure sensitive tensile loading of AlSiMg component fabricated using LPBF [462]. …”