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Layer-by-layer additive manufacturing (AM) by means of laser-powder bed Fusion (L-PBF) offers many prospects regarding the design of lattice structures used, for example, in gas turbines. However, defects such as bulk porosity, Surface roughness, and re-entrant features are exacerbated in nonvertical structures, such as tilted struts. The characterization and quantification of these kinds of
defects are essential for the correct estimation of fracture and fatigue properties.
Herein, cylindrical struts fabricated by L-PBF are investigated by means of X-ray computed tomography (XCT), with the aim of casting light on the dependence of the three kinds of defects (bulk porosity, surface roughness, and re-entrant features) on the build angle. Innovative analysis methods are proposed to correlate shape and position of pores, to determine the angular-resolved Surface roughness, and to quantify the amount of re-entrant surface features, q. A meshing of the XCT surface enables the correlation of q with the classical Surface roughness Pa. This analysis leads to the conclusion that there is a linear correlation between q and Pa. However, it is conjectured that there must be a threshold of surface roughness, below which no re-entrant features can be build.
The quantitative analysis of microstructural features is a key to understanding the micromechanical behavior of metal matrix composites (MMCs), which is a premise for their use in practice. Herein, a 3D microstructural characterization of a five-phase MMC is performed by synchrotron X-ray computed tomography (SXCT). A workflow for advanced deep learning-based segmentation of all individual phases in SXCT data is shown using a fully convolutional neural network with U-net architecture. High segmentation accuracy is achieved with a small amount of training data. This enables extracting unprecedently precise microstructural parameters (e.g., volume fractions and particle shapes) to be input, e.g., in micromechanical models.
Additive manufacturing (AM) of metals and in particular laser powder bed fusion (LPBF) enables a degree of freedom in design unparalleled by conventional subtractive methods. To ensure that the designed precision is matched by the produced LPBF parts, a full understanding of the interaction between the laser and the feedstock powder is needed. It has been shown that the laser also melts subjacent layers of material underneath. This effect plays a key role when designing small cavities or overhanging structures, because, in these cases, the material underneath is feed-stock powder. In this study, we quantify the extension of the melt pool during laser illumination of powder layers and the defect spatial distribution in a cylindrical specimen. During the LPBF process, several layers were intentionally not exposed to the laser beam at various locations, while the build process was monitored by thermography and optical tomography. The cylinder was finally scanned by X-ray computed tomography (XCT). To correlate the positions of the unmolten layers in the part, a staircase was manufactured around the cylinder for easier registration. The results show that healing among layers occurs if a scan strategy is applied, where the orientation of the hatches is changed for each subsequent layer. They also show that small pores and surface roughness of solidified material below a thick layer of unmolten material (>200 µm) serve as seeding points for larger voids. The orientation of the first two layers fully exposed after a thick layer of unmolten powder shapes the orientation of these voids, created by a lack of fusion.
Targeting biomedical applications, Triply Periodic Minimal Surface (TPMS) gyroid sheet-based structures were successfully manufactured for the first time by Electron Beam Melting in two different production Themes, i.e., inputting a zero (Wafer Theme) and a 200 µm (Melt Theme) wall thickness. Initial assumption was that in both cases, EBM manufacturing should yield the structures with similar mechanical properties as in a Wafer-mode, as wall thickness is determined by the minimal beam spot size of ca 200 µm. Their surface morphology, geometry, and mechanical properties were investigated by means of electron microscopy (SEM), X-ray Computed Tomography (XCT), and uniaxial tests (both compression and tension). Application of different manufacturing Themes resulted in specimens with different wall thicknesses while quasi-elastic gradients for different Themes was found to be of 1.5 GPa, similar to the elastic modulus of human cortical bone tissue. The specific energy absorption at 50% strain was also similar for the two types of structures. Finite element simulations were also conducted to qualitatively analyze the deformation process and the stress distribution under mechanical load. Simulations demonstrated that in the elastic regime wall, regions oriented parallel to the load are primarily affected by deformation. We could conclude that gyroids manufactured in Wafer and Melt Themes are equally effective in mimicking mechanical properties of the bones.
X-ray computed tomography has many applications in materials science and non-destructive testing. While the standard filtered back-projection reconstruction of the radiographic data sets is fast and simple, it typically fails in returning accurate results from missing or inconsistent projections. Among the alternative techniques that have been proposed to handle such data is the Direct Iterative REconstruction of Computed Tomography Trajectories (DIRECTT) algorithm. We describe a new approach to the algorithm, which significantly decreases the computational time, while achieving a better reconstruction quality than that of other established algorithms.
Complementary to Part 1 of this work, the bi-continuous microstructure of porous synthetic cordierite ceramics for filtration applications was investigated using 3D x-ray computed tomography at different resolutions. Applying both Fast Fourier Transform and a newly developed image analysis algorithm, we quantitatively evaluated porosity and pore orientation. The statistical approach allows extraction of spatially resolved or average values. Porosity values based on x-ray absorption agree with mercury intrusion measurements, while pore orientation factors agree with x-ray refraction data (Part 1 of this work), and with published crystallographic texture data.
This paper focuses on the experimental evaluation of one of the key microstructural Parameters of a short-fiber reinforced composite – the orientation distribution of fibers. It is shown that computed tomography (CT) produces results suitable for reconstruction of the orientation distribution function. This function is used for calculation of the effective elastic properties of polymer-fiber reinforced concrete. Explicit formulas are derived for overall elastic moduli accounting for orientation distribution in the frameworks of the noninteraction approximation, the Mori–Tanaka–Benveniste scheme, and the Maxwell scheme.
The approach illustrated can be applied to any kind of composite material.
The material and damage behaviour of additively manufactured polyamide 12 under cyclic loading was characterized by cyclic tests and microstructure analysis by using microscopy, X-ray refraction, and computed tomography. The results were used to determine parameters for the viscoplastic material model by Chaboche and a damage model by Gurson-Tvergaard-Needleman. The temperature was monitored during the experiments and the self-heating effect was observed. By including this effect, a higher accuracy could be achieved with the results of mechanical experiments.
In order to characterise the material and damage behaviour of additively manufactured polyamide 12 (PA12) under quasi-static load and to implement it in a numerical model, experiments under quasi-static load as well as microstructural investigations were carried out. Selective laser sintering (SLS) was used as the manufacturing process. For the classification of the material behaviour, quasi-static cyclic tests with holding times as well as tensile tests were performed. X-ray refraction and computed tomography (CT) were used to investigate the damage behaviour. The Chaboche model, which has already been applied for metallic materials under thermomechanical loading, served as the basis for the selection of the numerical material model. The same procedure was used for the selection of the damage model, where the Gurson–Tvergaard–Needleman (GTN) model was chosen, which was already used for porous metallic materials. The Chaboche model shows very good agreement with experimental results. Furthermore, the coupling with the GTN model allows a very good modelling of the damage behaviour. Finally, it could be shown that the selected models are suitable to simulate the material and damage behaviour of 3D printed PA12.
Digital Volume Correlation (DVC) is a powerful set of techniques used to compute the local shifts of 3D images obtained, for instance, in tomographic experiments. It is utilized to analyze the geometric changes of the investigated object as well as to correct the corresponding image misalignments for further analysis. It can therefore be used to evaluate the local density changes of the same regions of the inspected specimens, which might be shifted between measurements. In recent years, various approaches and corresponding pieces of software were introduced. Accuracies for the computed shift vectors of up to about 1‰of a single voxel size have been reported. These results, however, were based either on synthetic datasets or on an unrealistic setup. In this work, we propose two simple methods to evaluate the accuracy of DVC-techniques using more realistic input data and apply them to several DVC programs. We test these methods on three materials (tuff, sandstone, and concrete) that show different contrast and structural features.