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- 2020 (32) (entfernen)
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- Additive manufacturing (8)
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- X-ray refraction (5)
- Porosity (4)
- Residual stress (4)
- Additive Manufacturing (2)
- Aluminum alloys (2)
- Ammonium nitrate (2)
- Ceramics (2)
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Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (31)
- 8.5 Röntgenbildgebung (30)
- 9 Komponentensicherheit (4)
- 9.4 Integrität von Schweißverbindungen (4)
- 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 mixture of ammonium nitrate (AN) prills and fuel oil (FO), usually called ANFO, is extensively used in the mining industry as a bulk industrial explosive. One of the major performance predictors of ANFO mixtures is the fuel oil retention, which is itself governed by the porosity of the AN prills. Standardised tests routinely used to assess oil retention face several important limitations; the first being the difficulty to cover the wide range of porosity contents and morphologies from different types of ammonium nitrate prills; the second being the inability to evaluate the closed porosity, which is an important factor regarding the sensitivity of the explosive to detonation. In this study, we present how X-ray computed tomography (XCT), and the associated advanced data processing workflow, can be used to fully characterise the structure and morphology of AN prills. We show that structural parameters such as volume fraction of the different phases and morphological parameters such as specific surface area and shape factor can be reliably extracted from the XCT data, and that there is a good agreement with the measured oil retention values. XCT can therefore be employed to non-destructively and accurately evaluate and characterise porosity in ammonium nitrate prills.
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.
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.
The creep strengthening mechanisms in (age-hardenable) aluminum alloys are analyzed on the basis of a new microstructural study of powder samples, an analysis of a comprehensive revision of creep data from the literature, and a new modeling approach. A strategy based on the strength difference (SD) method to separate the contributions of solid solution atoms and precipitates to creep strengthening is proposed. The new methodology considers the combination of the two contributions avoiding the need of a threshold stress term in the creep equation. The contribution of both precipitates and solid solution is taken into account by means of the analysis of the lattice parameter variation with aging time. For this study, powders of two commercial AA2xxx alloys have been analyzed using diffraction methods. The experimental results are modeled using Lubarda’s approach combined with the SD method.
The creep strengthening mechanisms in (age-hardenable) aluminum alloys are analyzed on the basis of a new microstructural study of powder samples, an analysis of a comprehensive revision of creep data from the literature, and a new modeling approach. A strategy based on the strength difference (SD) method to separate the contributions of solid solution atoms and precipitates to creep strengthening is proposed. The new methodology considers the combination of the two contributions avoiding the need of a threshold stress term in the creep equation. The contribution of both precipitates and solid solution is taken into account by means of the analysis of the lattice parameter variation with aging time. For this study, powders of two commercial AA2xxx alloys have been analyzed using diffraction methods. The experimental results are modeled using Lubarda's approach combined with the SD method.
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.
Porosity in additively manufactured materials, such as laser powder bed fusion Ti-Al6-V4, can play an important role in their mechanical performance. Not only the total porosity but also the shape/morphology of the individual pores need to be considered. Therefore, it is necessary to determine the distributions of different defect types (especially fusing defects and keyhole pores) and their dependence on process parameters. We show that synchrotron X-ray refraction radiography allows analysis of large samples (up to several millimeters) without compromising the detectability of submicrometer defects. Correspondingly, a classification tool is introduced that is able to quantitatively distinguish defects such as keyhole pores and binding defects with a confidence level of 94 %, even when the shape cannot be discerned because of limited spatial resolution.
The paper presents the results of a series of combined mechanical and in-situ morphological investigations on highstrength strain-hardening cement-based Composites (SHCC). Tension and compression experiments were performed in a CT scanner employing a dedicated mechanical testing rig. The in-situ microtomographic scans enabled correlating the measured specimen response with relevant microstructural features and fracture processes. The microstructural segmentation of SHCC was performed in the framework of Deep Learning and it targeted an accurate segmentation of pores, fibers and aggregates. Besides their accurate volumetric representation, these phases were quantified in terms of content, size and orientation. The fracture processes were monitored at different loading stages and Digital Volume Correlation (DVC) was employed to spatially map the strains and cracks in the specimens loaded in compression. The DVC analysis highlighted the effect of loading conditions, specimen geometry and material heterogeneity at the mesolevel on the strain distribution and fracture localization.
Connecting Diffraction-Based Strain with Macroscopic Stresses in Laser Powder Bed Fused Ti-6Al-4V
(2020)
The laser powder bed fusion (LPBF) production process often results in large residual stress (RS) in the parts. Nondestructive techniques to determine RS are badly needed. However, a reliable quantification of macro-RS (i.e., stress at the component level) by means of diffraction-based techniques is still a great challenge, because the link between diffraction-based strain and macro-RS is not trivial. In this study, we experimentally determine (by means of in-situ synchrotron radiation diffraction) this link for LPBF Ti-6Al-4V. We compare our results with commonly used models to determine the so-called diffraction elastic constants (DECs). We show that LPBF materials possess different DECs than wrought alloys, simply because their microstructural and mechanical properties are different. We also show that the existing models can be used to calculate DECs only if high accuracy of the RS values is not required. If the peculiarities of the microstructure have to be taken into account (as is the case of additively manufactured materials), a radically new approach is desirable.
In this work, which is part of a larger research program, a framework called “virtual data fusion“ was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray Computed Tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in Alkali-Silica Reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then “fused” in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.