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- 2020 (32) (entfernen)
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- Additive manufacturing (8)
- Computed tomography (6)
- X-ray refraction (5)
- Porosity (4)
- Residual stress (4)
- Additive Manufacturing (2)
- Aluminum alloys (2)
- Ammonium nitrate (2)
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Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (31)
- 8.5 Röntgenbildgebung (30)
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- 2 Prozess- und Anlagensicherheit (3)
- 5 Werkstofftechnik (3)
- 2.5 Konformitätsbewertung Explosivstoffe/Pyrotechnik (2)
- 5.1 Mikrostruktur Design und Degradation (2)
- 8.0 Abteilungsleitung und andere (2)
- 2.2 Prozesssimulation (1)
The contour scan strategies in laser powder bed fusion (LPBF) of Ti-6Al-4V were studied at the coupon level. These scan strategies determined the surface qualities and subsurface residual stresses. The correlations to these properties were identified for an optimization of the LPBF processing. The surface roughness and the residual stresses in build direction were linked: combining high laser power and high scan velocities with at least two contour lines substantially reduced the surface roughness, expressed by the arithmetic mean height, from values as high as 30 μm to 13 μm, while the residual stresses rose from ~340 to about 800 MPa. At this stress level, manufactured rocket fuel injector components evidenced macroscopic cracking. A scan strategy completing the contour region at 100 W and 1050 mm/s is recommended as a compromise between residual stresses (625 MPa) and surface quality (14.2 μm). The LPBF builds were monitored with an in-line twin-photodiode-based melt pool monitoring (MPM) system, which revealed a correlation between the intensity quotient I2/I1, the surface roughness, and the residual stresses. Thus, this MPM system can provide a predictive estimate of the surface quality of the samples and resulting residual stresses in the material generated during LPBF.
We show how the combination of the spatial autocorrelation function and permeability calculations, applied to 3D X-ray computed tomography data, can yield quantitative information on the anisotropy of both meso-structure and fluid flow in Diesel Particulate Filter (DPF) materials, such as Cordierite and SiC. It was found that both the degree of anisotropy, and the orientation of the permeability and meso-structure are similar, but not identical. We confirm that the morphological anisotropy of cordierite materials is weak, and clearly influenced by the extrusion process that determines the main direction of anisotropy. Properties of the autocorrelation function are discussed and it is shown why estimating the characteristic length of real meso-structures (grain or ?pore? size) is not possible. Finally, we show that the autocorrelation function applied on grey-level images can give a good estimate of the degree of anisotropy even with limited resolution.
Porous ceramic diesel particulate filters (DPFs) are extruded products that possess macroscopic anisotropic mechanical and thermal properties. This anisotropy is caused by both morphologic features (mostly the orientation of porosity) and crystallographic texture. We systematically studied those two aspects in a cordierite and two aluminum titanate (AT) ceramic materials of different porosity using mercury porosimetry, gas adsorption, electron microscopy, X-ray diffraction, and X-ray refraction radiography. We found that a lower porosity in AT content implies a larger isotropy of both the crystal texture and the porous space orientation. We also found that, analogous to cordierite, AT crystallites do align with their axis of negative thermal expansion along the extrusion direction. However, unlike what found for cordierite, the aluminium titanate crystallite form is such that a more pronounced (0 0 2) texture along the extrusion direction implies porosity aligned perpendicular to it.
The goal of the Special Issue “Brittle Materials in Mechanical Extremes” was to spark a discussion of the analogies and the differences between different brittle materials, such as, for instance, ceramics and concrete. Indeed, the contributions to the Issue spanned from construction materials (asphalt and concrete) to structural ceramics, reaching as far as ice. The data shown in the issue were obtained by advanced microstructural techniques (microscopy, 3D imaging, etc.) and linked to mechanical properties (and their changes as a function of aging, composition, etc.). The description of the mechanical behavior of brittle materials under operational loads, for instance, concrete and ceramics under very high temperatures, offered an unconventional viewpoint on the behavior of brittle materials. This is not at all exhaustive, but a way to pave the road for intriguing and enriching comparisons.
The present work offers an explanation on how the long-range interaction of dislocations influences their movement, and therefore the strain, during creep of metals. It is proposed that collective motion of dislocations can be described as a fractional Brownian motion. This explains the noisy appearance of the creep strain signal as a function of time. Such signal is split into a deterministic and a stochastic part. These terms can be related to two kinds of dislocation motions: individual and collective, respectively. The description is consistent with the fractal nature of strain-induced dislocation structures predicated in previous works. Moreover, it encompasses the evolution of the strain rate during all stages of creep, including the tertiary one. Creep data from Al99.8% and Al- 3.85%Mg tested at different temperatures and stresses are used to validate the proposed ideas: it is found that different creep stages present different diffusion characters, and therefore different dislocation motion character.
We show that the equation proposed by Takeuchi and Argon to explain the creep behavior of Al–Mg solid solution can be used to describe also the creep behavior of pure aluminum. In this frame, it is possible to avoid the use of the classic pre-exponential fitting parameter in the power law equation to predict the minimum creep strain rate. The effect of the fractal arrangement of dislocations, developed at the mesoscale, must be considered to fully explain the experimental data. These ideas allow improving the recently introduced SSTC model, fully describing the primary and secondary creep regimes of aluminum alloys without the need for fitting. Creep data from commercially pure Al99.8% and Al–Mg alloys tested at different temperatures and stresses are used to validate the proposed ideas.
As opposed to reviewing results on experimental determination of residual stress by diffraction, this paper discusses the open issues when dealing with residual stress determination in additive manufactured parts, in particular those manufactured with laser powder bed fusion techniques. Three points are addressed in detail: (a) the proper determination of the strain-free reference d0, (b) the problem of the determination of the principal axes, and (c) the use of the correct diffraction elastic constants. It is shown that all methods to determine the strain-free reference d0 suffer from caveats, and care must be taken in evaluating the most suitable for the problem being tackled. In addition, it is shown that, in some systems, the principal axes do correspond to the geometrical axes of the specimen, but this needs to be systematically checked, especially in the case of uni- or bidirectional hatching strategies. Finally, the need to experimentally determine the proper diffraction elastic constants is underlined, especially in the case of strongly textured specimens, which again depends on the deposition strategy.
Porous ceramic diesel particulate filters (DPFs) are extruded products that possess macroscopic anisotropic mechanical and thermal properties. This anisotropy is caused by both morphological features (mostly the orientation of porosity) and crystallographic texture. We systematically studied those two aspects in two aluminum titanate ceramic materials of different porosity using mercury porosimetry, gas adsorption, electron microscopy, X-ray diffraction, and X-ray refraction radiography. We found that a lower porosity content implies a larger isotropy of both the crystal texture and the porosity orientation. We also found that, analogous to cordierite, crystallites do align with their axis of negative thermal expansion along the extrusion direction. However, unlike what found for cordierite, the aluminium titanate crystallite form is such that a more pronounced (0 0 2) texture along the extrusion direction implies porosity aligned perpendicular to it.
While there is a large body of literature on the micro-mechanical behavior of metal matrix composites (MMCs) under uniaxial applied stress, very little is available on multi-phase MMCs. In order to cast light on the reinforcement mechanisms and damage processes in such multi-phase composites, materials made by an Al-based piston alloy and containing one and two ceramic reinforcements (planar-random oriented alumina fibers and SiC particles) were studied. In-situ compression tests during neutron diffraction experiments were used to track the load transfer among phases, while X-ray computed tomography on pre-strained samples was used to monitor and quantify damage. We found that damage progresses differently in composites with different orientations of the fiber mat. Because of the presence of intermetallic network, it was observed that the second ceramic reinforcement changed the load transfer scenario only at very high applied load, when also intermetallic particles break. We rationalized the present results combining them with previous investigations and using a micromechanical model.
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.