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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.
Ti-6Al-4V bridges were additively fabricated by selective laser melting (SLM) under different scanning speed conditions, to compare the effect of process energy density on the residual stress state. Subsurface lattice strain characterization was conducted by means of synchrotron diffraction in energy dispersive mode. High tensile strain gradients were found at the frontal surface for samples in an as-built condition. The geometry of the samples promotes increasing strains towards the pillar of the bridges. We observed that the higher the laser energy density during fabrication, the lower the lattice strains. A relief of lattice strains takes place after heat treatment.
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 mu m) 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.
Laser based powder bed fusion additive manufacturing offers the flexibility to incorporate standard and user-defined scan strategies in a layer or in between the layers for the customized fabrication of metallic components. In the present study, four different scan strategies and their impact on the development of microstructure, texture, and residual stresses in laser powder bed fusion additive manufacturing of a nickel-based superalloy Inconel 718 was investigated. Light microscopy, scanning electron microscopy combined with electron back-scatter diffraction, and neutron diffraction were used as the characterization tools. Strong textures with epitaxially grown columnar grains were observed along the build direction for the two individual scan strategies. Patterns depicting the respective scan strategies were visible in the build plane, which dictated the microstructure development in the other planes. An alternating strategy combining the individual strategies in the successive layers and a 67 degrees rotational strategy weakened the texture by forming finer micro-structural features. Von Mises equivalent stress plots revealed lower stress values and gradients, which translates as lower distortions for the alternating and rotational strategies. Overall results confirmed the scope for manipulating the microstructure, texture, and residual stresses during laser powder bed fusion additive manufacturing by effectively controlling the scan strategies.
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.
The paper is motivated by some inconsistencies and contradictions present in the literature on the calculation of the so-called diffraction elastic constants. In an attempt at unifying the views that the two communities of Materials Science and Mechanics of Materials have on the subject, we revisit and define the terminology used in the field. We also clarify the limitations of the commonly used approaches and show that a unified methodology is also applicable to textured materials with a nearly arbitrary grain shape. We finally compare the predictions based on this methodology with experimental data obtained by in situ synchrotron radiation diffraction on additively manufactured Ti-6Al-4V alloy. We show that (a) the transverse isotropy of the material yields good agreement between the best-fit isotropy approximation (equivalent to the classic Kroner's model) and the experimental data and (b) the use of a general framework allows the calculation of all components of the tensor of diffraction elastic constants, which are not easily measurable by diffraction methods. This allows us to extend the current state-of-the-art with a predictive tool.
High-density polyethylene becomes optically transparent during tensile drawing when previously saturated with diesel fuel. This unusual phenomenon is investigated as it might allow conclusions with respect to the material behavior. Microscopy, differential scanning calorimetry, density measurements are applied together with two scanning X-ray scattering techniques: wide angle X-ray scattering (WAXS) and X-ray refraction, able to extract the spatially resolved crystal orientation and internal surface, respectively. The sorbed diesel softens the material and significantly alters the yielding characteristics. Although the crystallinity among stretched regions is similar, a virgin reference sample exhibits strain whitening during stretching, while the diesel-saturated sample becomes transparent. The WAXS results reveal a pronounced fiber texture in the tensile direction in the stretched region and an isotropic orientation in the unstretched region. This texture implies the formation of fibrils in the stretched region, while spherulites remain intact in the unstretched parts of the specimens. X-ray refraction reveals a preferred orientation of internal surfaces along the tensile direction in the stretched region of virgin samples, while the sample stretched in the diesel-saturated state shows no internal surfaces at all. Besides from stretching saturated samples, optical transparency is also obtained from sorbing samples in diesel after stretching.
Diffraction enhanced imaging (DEI) is an advanced digital radiographic imaging technique employing the refraction of X-rays to contrast internal interfaces. This study aims to qualitatively and quantitatively evaluate images acquired using this technique and to assess how different fitting functions to the typical rocking curves (RCs) influence the quality of the images. RCs are obtained for every image pixel. This allows the separate determination of the absorption and the refraction properties of the material in a position-sensitive manner. Comparison of various types of fitting functions reveals that the Pseudo-Voigt (PsdV) function is best suited to fit typical RCs. A robust algorithm was developed in the Python programming language, which reliably extracts the physically meaningful information from each pixel of the image. We demonstrate the potential of the algorithm with two specimens: a silicone gel specimen that has well-defined interfaces, and an additively manufactured polycarbonate specimen.
Laser-based additive manufacturing methods allow the production of complex metal structures within a single manufacturing step. However, the localized heat input and the layer-wise manufacturing manner give rise to large thermal gradients. Therefore, large internal stress (IS) during the process (and consequently residual stress (RS) at the end of production) is generated within the parts. This IS or RS can either lead to distortion or cracking during fabrication or in-service part failure, respectively. With this in view, the knowledge on the magnitude and spatial distribution of RS is important to develop strategies for its mitigation. Specifically, diffraction-based methods allow the spatial resolved determination of RS in a non-destructive fashion. In this review, common diffraction-based methods to determine RS in laser-based additive manufactured parts are presented. In fact, the unique microstructures and textures associated to laser-based additive manufacturing processes pose metrological challenges. Based on the literature review, it is recommended to (a) use mechanically relaxed samples measured in several orientations as appropriate strain-free lattice spacing, instead of powder, (b) consider that an appropriate grain-interaction model to calculate diffraction-elastic constants is both material- and texture-dependent and may differ from the conventionally manufactured variant. Further metrological challenges are critically reviewed and future demands in this research field are discussed.
X-ray computed tomography has many applications in materials science and non-destructive testing. While the standard filtered back-projection reconstruction of the radiographic datasets 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.