Magnus Ekh

Additive manufacturing (AM) methods like powder bed fusion–laser beam (PBF-LB) enable complex geometry production. However, understanding and predicting the microstructural properties of AM parts remain challenging due to the inherent non-homogeneity introduced during the manufacturing process. This study demonstrates a novel approach for 3D microstructure representation and virtual testing of non-homogeneous AM materials using 2d electron backscatter diffraction (EBSD) data. By employing the representative volume element (RVE) method, we reconstruct the 3D microstructure from 2D EBSD datasets, effectively capturing the grain morphological characteristics of PBF-LB-produced Hastelloy X. Using validated RVE data, we artificially generate combinations of two grain textures to gain deeper insight into locally affected areas, particularly the stress distribution within the interfaces, as well as global material behavior, exploring non-homogeneity. Computational homogenization (CH) utilizing a crystal elasticity finite element (CEFE) method is used to virtually test and predict directional elastic properties, offering insights into relationships between microstructure evolution and property correlation. The experimentally validated results show a strong correlation, with only 0.5–3.5% correlation error for the selected grain tessellation method. This consistency and reliability of the methodology provide high confidence for additional virtual tests predicting the properties of non-homogeneous, artificially generated combined-grain structures.

Rolling contact fatigue of railway rails not only severely deforms the surface material near the rail head, but also induces an anisotropy in the mechanical behavior due to work hardening and alignment of the microstructure along the shear direction. Cracks typically initiate in this region and propagate along the aligned microstructure. The fatigue behavior of rails is evaluated under uniaxial loading in the undeformed material state. However, this is not representative of the contact loading condition and material performance after years of service. Herein, the nonproportional multiaxial fatigue of as‐received and biaxially predeformed pearlitic rail steel R260 is investigated. Four material states are investigated, corresponding to the microstructure found at different depths from the severely deformed surface material at the rail head. A starting notch is machined by electrical discharge machining to control crack initiation and allow for comparable surface crack propagation measurements. The crack path is found to be strongly influenced by the degree of predeformation while the early surface crack propagation rate is found to be similar for all material states.

This study provides a methodology for exploring the microstructural and mechanical properties of the Haynes^®282^® alloy produced via the Powder Bed Fusion-Electron Beam (PBF-EB) process. Employing 2D Electron Backscatter Diffraction (EBSD) data, we have successfully generated 3D representations of columnar microstructures using the Representative Volume Element (RVE) method. This methodology allowed for the validation of elastic properties through Crystal Elasticity Finite Element (CEFE) computational homogenization, revealing critical insights into the material behavior. This study highlights the importance of accurately representing the grain morphology and crystallographic texture of the material. Our findings demonstrate that created virtual models can predict directional elastic properties with a high level of accuracy, showing a maximum error of only ~5% compared to the experimental results. This precision underscores the potential of our approach for predictive modeling in Additive Manufacturing (AM), specifically for materials with complex, non-homogeneous microstructures. It can be concluded that the results uncover the intricate link between microstructural features and mechanical properties, underscoring both the challenges encountered and the critical need for the accurate representation of grain data, as well as the significance of achieving a balance in EBSD area selection, including the presence of anomalies in strongly textured microstructures.

In this contribution macroscopic modeling of phase transformations and mechanical behavior of low alloy steels are developed and investigated. Such modeling is of importance in simulations of transient thermo-mechanical processes which can cause phase transformations, examples from the railway industry include train braking induced frictional heating as well as rail grinding and welding operations. We adopt a modeling approach which includes phase transformation kinetics and individual constitutive models for the phases in combination with different homogenization methods. Algorithmic implementations of the isostrain, isostress and self-consistent homogenization methods are presented and demonstrated in finite element simulations of a laser heating experiment. Stress field results from the different homogenization methods are compared against each other and also against experimental data. The importance of including transformation induced plasticity in the modeling is highlighted, as well as the multi-phase stages of the heating and cooling.

Block braked railway wheels are subjected to thermal and rolling contact loading. The thermal loading results in high temperatures and thermal stresses which cause slow time dependent processes such as creep, relaxation and static recovery of the wheel material. At the same time, the rolling contact loading implies a very fast mechanical load application. This paper is focused on material modeling of pearlitic steel for a wide range of loading rates at elevated temperatures. The starting point is a viscoplasticity model including nonlinear isotropic and kinematic hardening. The Delobelle overstress function is employed to capture strain rate dependent response of the material. The model also includes static recovery of the hardening to capture slower viscous (diffusion dominated) behaviour of the material. Experiments for the pearlitic wheel steel ER7 in terms of cyclic strain-controlled uniaxial tests with hold-time, uniaxial ratchetting tests including rapid cycles and biaxial cyclic tests with tension/compression and torsion are used to calibrate the material model. These experiments were performed under isothermal conditions at different temperatures. In the ratchetting tests, higher loading rates are obtained and these have been used to calibrate the high strain rate response of the viscoplasticity model. The paper is concluded with a numerical example of a block braked wheel where the importance of accounting for the viscoplasticity in modelling is highlighted.