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The use of novel multi-scale correlative methods, which involve the coordinated characterisation of matter across a range of length scales, are becoming of increasing value to materials scientists. Here, we describe for the first time how a multi-scale correlative approach can be used to investigate the nature of ductile fracture in metals. Specimens of a nuclear pressure vessel steel, SA508 Grade 3, are examined following ductile fracture using medium and high-resolution 3D X-ray computed tomography (CT) analyses, and a site-specific analysis using a dual beam plasma focused ion beam scanning electron microscope (PFIB-SEM). The methods are employed sequentially to characterise damage by void nucleation and growth in one volume of interest, allowing for the imaging of voids that ranged in size from less than 100 nm to over 100 mm. This enables the examination of voids initiated at carbide particles to be detected, as well as the large voids initiated at inclusions. We demonstrate that this multi-scale correlative approach is a powerful tool, which not only enhances our understanding of ductile failure through detailed characterisation of microstructure, but also provides quantitative information about the size, volume fractions and spatial distributions of voids that can be used to inform models of failure. It isfound that the vast majority of large voids nucleated at MnS inclusions, and that the volume of a void varied according to the volume of its initiating inclusion raised to the power 3/2. The most severe voiding was concentrated within 500 mm of the fracture surface, but measurable damage was found to extend to a depth of at least 3 mm. Microvoids associated with carbides (carbide-initiated voids) were found to be concentrated around larger inclusion-initiated voids at depths of at least 400 mm. Methods for quantifying X-ray CT void data are discussed, and a procedure for using this data to calibrate parameters in the Gurson-Tvergaard Needleman (GTN) model for ductile failure is also introduced.
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.
As humanity contemplates manned missions to Mars, strategies need to be developed for the design and operation of hospitable environments to safely work in space for years. The supply of spare parts for repair and replacement of lost equipment will be one key need, but in-space manufacturing remains the only option for a timely supply. With high flexibility in design and the ability to manufacture ready-to-use components directly from a computeraided model, additive manufacturing (AM) technologies appear extremely attractive. For the manufacturing of metal parts, laser-beam melting is the most widely used AM process. However, the handling of metal powders in the absence of gravity is one prerequisite for its successful application in space. A gas flow throughout the powder bed is successfully applied to compensate for missing gravitational forces in microgravity experiments. This so-called gas-flow-assisted powder deposition is based on a porous Building platform acting as a filter for the fixation of metal particles in a gas flow driven by a pressure difference maintained by a vacuum pump.
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.
Several cylindrical specimens and dental implants, presenting diagonal lattice structures with different cell sizes (600, 900 and 1200 µm) were additively manufactured by selective laser melting process. Then they were implanted for two months in a sheep. After removal, they were studied by Archimedes’ method as well as X-ray computed tomography in order to assess the penetration of bone into the lattice. We observed that the additive manufactured parts were geometrically conform to the theoretical specifications. However, several particles were left adhering to the surface of the lattice, thereby partly or entirely obstructing the cells. Nevertheless, bone penetration was clearly visible. We conclude that the 900 µm lattice cell size is more favourable to bone penetration than the 1200 µm lattice cell size, as the bone penetration is 84 % for 900 µm against 54 % for 1200 µm cell structures. The lower bone penetration value for the 1200 µm lattice cell could possibly be attributed to the short residence time in the sheep. Our results lead to the conclusion that lattice implants additively manufactured by selective laser melting enable better bone integration.
Up to now, there exists a lack of methods for the additive manufacturing of voluminous ceramic parts with properties comparable to those of conventionally manufactured ones. A high density after sintering is needed to reach the superior properties of ceramic materials. We have developed a new additive manufacturing method, Laser-Induced Slip casting (LIS), to generate ceramic green bodies with high particle packing density and with virtually no restriction in the particle size of the feedstock, especially in terms of small particles. This is achieved by laser-induced local drying of slurries, with the process resembling many features of the well-established stereolithography, but without the excessive use of polymeric material. Thus, unlike the stereolithography process, the resulting green bodies can be processed like traditionally produced ceramic parts. This method allows large and dense additive-manufactured parts to be obtained from conventional water-based ceramic slurries. As an example, we will demonstrate the application of this novel technique with Si3N4.
Durch den großflächigen Einsatz der Computertomographie (CT) in unterschiedlichen Industriebereichen steigen auch die Anforderungen an die quantitative Bildanalyse. Subjektive Bildwahrnehmung muss durch objektive Algorithmen ersetzt werden. In diesem Artikel stellt die Bundesanstalt für Materialforschung und -prüfung (BAM), die seit den 1980er Jahren an der Entwicklung der industriellen CT beteiligt ist, anhand ausgewählter Beispiele den aktuellen Stand ihrer Analysemethoden an verschiedenen Anwendungsbeispielen der CT vor.
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.
The mixture of ammonium nitrate (AN) prills and fuel oil (FO), usually referred to as ANFO, is extensively used in the mining industry as a bulk explosive. One of the major performance predictors of ANFO mixtures is the fuel oil retention, which is itself governed by the complex pore structure of the AN prills. 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. Importantly, oil retention measurements (qualifying the efficiency of ANFO as explosives) correlate well with the specific surface area determined by XCT. XCT can therefore be employed non-destructively; it can accurately evaluate and characterise porosity in ammonium nitrate prills, and even predict their efficiency.