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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.
By means of a small-scale truss bridge, the ability of the Measurement- and Model-based Structural Analysis to detect and localise damage was examined in. Although there was no noteworthy difficulty in detecting damage, it turned out that damage localisation responds sensitively to systematic influences, i.e. non-modelled properties of the mechanical model. Therefore, another experiment is being conducted to re-examine the Measurement- and Model-based Structural Analysis. For this purpose, the bending test is carried out as it has been already theoretically respectively numerically discussed in. In this attempt, the systematic influences such as residual stress are kept as low as possible.
To better understanding the failure of adhesive joints tensile tests were carried out on miniature test specimens from Norway spruce in the synchrotron. Urea-formaldehyde resin was used as adhesive. e. For comparison purposes, tensile tests were carried out on solid wood and on bonded miniature tensile shear samples with acoustic emission. The acoustic emission signals of all the experiments occurred with classified pattern recognition. This resulted in two classes of signals for each two frequency peaks. One class consisted of the low-frequency and the other of the higher-frequency peak of higher intensity, but this was essentially independent from the structure (solid wood or plywood) and size scale of the test specimens. The influence of the adhesive layers was determined on wood test specimens on laboratory scale and on miniature test specimens with an adhesive layer and selected fiber orientations. This gave evidence that the sound emission signals from the failure of the adhesive layer presumably of the class with low frequency signals peak in the range of services can be assigned.
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.
Recent years have seen extended use of ultrasonic techniques for concrete infrastructure assessement. They are applied for quality assurance and condition assessement at bridges, power plants, dams and other important objects. However, there are still a couple of significant limitations. They include, but are not limited to depth of penetration, imaging complex structures or early stage detections of distributed damage. The talk will give information on recent research in this area. Specifically, the application of the unique deep penetration system LAUS is shown. Ultrasonic monitoring using embedded transducers to check for subtle and sudden changes in the material is introduced as well. Comments on initiatives for validation, standardization and certification will be given.
Air-coupled ultrasound was used for assessing natural defects in wood boards by through-transmission scanning measurements. Gas matrix piezoelectric (GMP) and ferroelectret (FE) transducers were studied. The study also included tests with additional bias voltage with the ferroelectret receivers. Signal analyses, analyses of the measurement dynamics and statistical analyses of the signal parameters were conducted. After the measurement series, the samples were cut from the measurement regions and the defects were analyzed visually from the cross sections. The ultrasound responses were compared with the results of the visual examination of the cross sections. With the additional bias voltage, the ferroelectret measurement showed increased signal-to-noise ratio, which is especially important for air-coupled measurement of high-attenuation materials like wood. When comparing the defect response of GMP and FE sensors, it was found that FE sensors had more sensitive dynamic range, resulting from better s/n ratio and short response pulse. Classification test was made to test the possibility of detecting defects in sound wood. Machine learning methods including decision trees, k-nearest neighbor and support vector machine were used. The classification accuracy varied between 72 and 77% in the tests. All the tested machine learning methods could be used efficiently for the classification.
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.