Filtern
Erscheinungsjahr
- 2020 (216) (entfernen)
Dokumenttyp
- Zeitschriftenartikel (93)
- Vortrag (69)
- Beitrag zu einem Tagungsband (21)
- Posterpräsentation (18)
- Sonstiges (8)
- Forschungsdatensatz (4)
- Buchkapitel (1)
- Beitrag zu einem Sammelband (1)
- Dissertation (1)
Sprache
- Englisch (159)
- Deutsch (55)
- Mehrsprachig (2)
Schlagworte
- Additive manufacturing (15)
- Thermography (12)
- Computed tomography (11)
- Additive Manufacturing (9)
- Ultrasound (9)
- LIBS (7)
- Porosity (7)
- X-ray refraction (7)
- Radar (6)
- Residual stress (6)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (216) (entfernen)
Paper des Monats
- ja (3)
Eingeladener Vortrag
- nein (69)
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.
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.
Intensified Alkali-Silica Reaction (ASR) damage has occurred on German roadways in recent years, leading to requirements for compulsory pre-construction investigation of aggregate alkali sensitivity using concrete tests with external alkali supply. However, since these tests are time-consuming and cost-intensive, there is interest in replacing them with a solubility test on pure aggregate in 0.1 M KOH solution at 80°C with a defined NaCl content (1wt.-%). In this context, the influence of aggregate pore structure on SiO2 and Al2O3 solubility was investigated in this project. This paper compares the results of porosity studies with X-ray Computed Tomography (3D-CT) and the Brunauer-Emmett-Teller (BET) method on individual quarried and river gravel granules of both rhyolite and greywacke. For visualization and quantification of both externally accessible and fully enclosed surfaces of granules using X-ray 3D-CT, special software tools were developed. The results demonstrated that the river gravel granules had significantly larger externally accessible surfaces than the quarried granules. BET measurements on individual stones showed, as expected, that measured surfaces were about three orders of magnitude larger than those from the X-ray 3D-CT analyses due to the higher spatial resolution of BET. There was no apparent correlation between the X-ray 3D-CT and BET surface areas. Mercury porosimetry measurements indicate that this may be due to the presence of significant porosity below the spatial resolution of the X-ray 3D-CT. A comparison of SiO2 and Al2O3 solubility measurements with the X-ray 3D-CT and BET surface area data resulted only in weak, inconclusive correlations, indicating the need for further experimental investigation.
The improvement potential of ultrafast all-optical switching by soliton self-trapping, using all-solid dual-core fibres with high index contrast, was analyzed numerically. The study of the femtosecond nonlinear propagation was performed based on coupled generalised nonlinear Schrödinger equations considering three fibre architectures: homogeneous cladding all-solid, photonic crystal air-glass, and photonic crystal all-solid. The structural geometries of all three architectures were optimised in order to support high-contrast switching performance in the C-band, considering pulse widths at the 100 fs level. Comparing the three structural alternatives, the lowest switching energies at common excitation parameters (1700 nm and 70 fs pulses) were predicted for the homogeneous cladding dual-core structure. Further optimization of the excitation wavelength and pulse width resulted in lower switching energies and simultaneous improvement of the switching contrasts at the combination of 1500 nm, 75 fs pulses and a fibre length of 43 mm. The spectral aspect in this optimised case expresses a broadband and uniform switching character with a span of over 200 nm and a contrast exceeding 30 dB at more frequency channels.
Data-driven research is considered the new paradigm in science. In this field, data is the new resource from which knowledge is extracted that is too complex for traditional methods. Several factors such as national funding and advances in information technology, are driving the development. In particular, the creation of databases and the analysis of data with artifical intelligence are playing an important role in establishing the new paradigm. However, there are numerous challenges that must be overcome to realize the full potential of data-driven methods. This talk sets the stage for the upcoming workshop by reviewing some of the historical developments and the current state of data-driven science in NDT and materials science.
Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data.
The one-dimensional thermal quadrupole method is used to evaluate a pulsed thermography measurement at delaminations in a glass-fiber reinforced plastic plate quantitatively. The large-scale delaminations have been induced by tension overload and are air-filled and are usually located at the same depth as the notch bottom of a notch on the rear side. While classical evaluation methods like pulsed phase thermography and thermal Signal reconstruction are focused on the delamination depth only, the thermal quadrupole method determines spatially resolved two parameters for delaminations, delamination depth and local thermal resistance. Interestingly, lateral heat flows do not disturb this kind of depth evaluation.
The understanding of process-microstructure-property-performance (PMPP) relationships in additive manufacturing (AM) of metals is highly necessary to achieve wide-spread industrial application and replace conventionally manufactured parts, especially regarding safety-relevant applications. To achieve this understanding, reliable data and knowledge regarding material’s microstructure-property relationships (e.g. the role of defects) is needed, since it represents the base for future more targeted process optimizations and more reliable calculations of performance. However, producing reliable material data and assessing the AM material behaviour is not an easy task: big challenges are e.g. the actual lack of standard testing methods for AM materials and the occasional difficulties in finding one-to-one comparable material data for the conventional counterpart.
This work aims to contribute to end this lack of reliable material data and knowledge for the low cycle fatigue behaviour of the most used titanium alloy in aerospace applications (Ti-6Al-4V). For this purpose, two sets of test specimens were investigated. The first set was manufactured from cylindrical rods produced by an optimized DED-L process and the second was manufactured from a hot formed round bar. The test specimens were cyclically loaded until failure in the low-cycle-fatigue (LCF) regime. The tests were carried out according to ISO 12106 between 0.3 to 1.0 % axial strain amplitude from room temperature up to 400°C. The LCF behaviour is described and compared between materials and with literature values based on cyclic deformation curves and strain-based fatigue life curves. Besides, the parameters of Manson-Coffin-Basquin relationship were calculated. The microstructures (initial and after failure) and fracture surfaces were comparative characterized. Thereby, the focus lied on understanding the role of grain morphology and defects on the failure mechanisms and fatigue lifetimes. For this latter characterization, optical microscopy (OM), scanning electron microscopy (SEM) and micro computed tomography (µCT) were used.
Damit eine Simulationsrechnung, beispielsweise mit einer FEM-Software, eine ausreichend hohe Genauigkeit erreicht, muss vorausgesetzt werden, dass die Modellparameter eine sehr hohe Güte aufweisen. Die genaue Kenntnis der Materialparameter ist dabei von besonderer Bedeutung. Um diese Parameter bestimmen zu können, müssen die verwendeten Werkstoffe messtechnisch charakterisiert werden. Neben anderen Ansätzen sind dafür akustische Verfahren im Ultraschallbereich geeignet. Für dünnwandige und plattenförmige Materialien können aus den sich ausbreitenden geführten Wellen messtechnisch Dispersionskurven bestimmt und aus diesen die Materialparameter abgeleitet werden.
Da für die Signalverarbeitung und für Optimierungsaufgaben aktuell zunehmend Machine Learning Tools zum Einsatz kommen, stellt sich die Frage, ob diese Werkzeuge auch für die Ermittlung der Materialparameter aus den gemessenen Dispersionskurven eingesetzt werden können.
In der vorgestellten Untersuchung soll ein Convolutional Neural Network aufgestellt werden, welches aus Dispersionsbildern Muster extrahiert und aus diesen eine Schätzung für die Materialparameter ermittelt. Um die Machbarkeit dieses Ansatzes zu prüfen, werden zunächst nur isotrope Materialien betrachtet. Für das Netz werden mit der Scaled-Boundary-Finite-Element-Methode synthetische Daten für das Trainieren und Validieren generiert. Zusätzlich werden die Hyperparameter des neuronalen Netzes variiert, um ein optimales Model für die Schätzung zu finden. Anschließend kann das Netz mit experimentellen Daten getestet und das Ergebnis hinsichtlich der Genauigkeit bewertet werden.
Fortwährend besteht ein wesentlicher Bedarf an Nachrechnungen von bestehenden Brückenbauwerken. Die Zuverlässigkeit der Berechnungsergebnisse hängt insbesondere von der Anzahl und von der Qualität der einbezogenen Informationen ab. Durch die Anwendung von zerstörungsfreien Prüfmethoden können quantitative Informationen gesammelt werden, die für die Beurteilung der Tragwerke sowohl relevant als auch ausreichend genau sind. Die gemessenen Daten können explizit in probabilistische Berechnungsmodelle für die Nachrechnung einer Brücke einfließen. Dadurch wird das Modell sukzessive an die Realität angenähert — in anderen Worten: "zugeschärft". Die Zuverlässigkeit der Ergebnisse der Nachrechnung steigt.
In diesem Posterbeitrag wird ein entwickeltes Konzept für die Verwendung von Messergebnissen (anstelle von deterministischen Informationen und Annahmen) im statischen Nachweis zusammengefasst. Am Fallbeispiel einer Spannbetonbrücke werden die Vorteile des dargestellten Ansatzes aufgezeigt. Die Messgrößen (hier die Positionen der Längsspannglieder) und die Messstrategien können anhand von Sensitivitätsanalysen definiert und die Anforderungen an die Messergebnisse aus der statischen Berechnung spezifiziert werden. Die Auswirkungen
a) der Messunsicherheit auf die Tragwerkszuverlässigkeit sowie
b) von gegenüber den vor den Messungen verfügbaren Informationen abweichenden Messwerten sind am Beispiel der Lokalisierung der Längsspannglieder durch Ultraschall- und Radarmessungen dargestellt.
Air pollution in industrial environments is a major risk. Precise knowledge about the distribution of air pollutants is necessary to develop plausible occupational health measures. Combinatory systems, consisting of mobile robots and stationary sensors, can be effective solutions for the coverage of large measurement areas.
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.
Over decades, the German Federal Institute for Materials Research and Testing (BAM) has established a sophisticated calibration laboratory for force, temperature and electrical quantities. Since more than 15 years it is accredited, currently by the national accreditation body (DAkkS), and offers its service also to external entities on a global scale. As a public provider, we are furthermore committed to research and development activities that demand measurements with highest quality and low level of uncertainties. Two R&D examples are highlighted within this contribution.
A powerful tool to understand, demonstrate and explain the limits of the pulsed technique in terms of detectability and localizability of AM keyhole pores has been assessed by comparing the active thermographic approach (both experimental and FEM simulations) to Computed Tomography results;
✓ µCT results demonstrate that the intended defect geometry is not achieved; indeed a network of voids (microdefects consisting of small sharp-edged hollows with a complicated, almost fractal, inner surface) was found;
✓ both Exp-PT and FEM results explains clearly why no indication of defect related to the thermal contrasts could be found during the investigation of an uncoated surface. However, the application of further data evaluations focusing on the thermal behavior and emissivity evaluation (PPT post data processing) enable the detection of some defects;
✓ coating facilitates a closer inspection of inner defects, but inhomogeneities of the coating could impair the spatial resolution and lead to the emergence of hotspots (the FEM simulation reached its limit with this extreme geometry where a 25 µm thin disc is considered at a 1 cm thick specimen in millisecond time resolution);
✓ both Exp-PT and FEM results allow the conclusion that very short pulses of 200 ms or shorter should be sufficient to detect these defects below, but near the surface; besides a short duration of the thermal phenomenon it should be emphasized, about 0.04 s (high frame rate camera);
A large amount of data and information is collected in the field of non-destructive testing (NDT) in civil engineering. The weakly structured data are usually evaluated with regard to specific testing tasks (e.g. geometry determination, damage localization, quality assurance). While the data offers great economic potential, i.e. to support construction planning, monitoring and maintenance processes, the evaluation is manual and case-by-case and therefore too inefficient for broader applications. We present recent visions and approaches how these large amounts of data need to be handled in the future and how we aim to make the acquired knowledge accessible to our stakeholders. Building on initiatives in materials research, we stress the importance of further research in the field of semantic data integration particularly motivate why an ontology is needed for the area of NDT in civil engineering.
Structural health monitoring (SHM) is a term that groups together techniques adopted to evaluate in a continued fashion the structural integrity and degradation of technical appliances. SHM is particularly attractive for components that are difficult to access or expensive to take off-line. Among many other techniques, SHM can be performed using ultrasonic guided waves (UGW) which have an advantage of traveling over Long distances. Various guided wave modes exist along with many methods for their generation and sensing, e.g by means of interdigital transducers (IDT). This contribution is dedicated to the design and characterization of a flexible piezopolymerbased IDT which allows for the selective excitation of UGW, resulting in more straightforward data analysis. The designed IDT was characterized using a 3D Laser Doppler Vibrometer (3D LDV) in the air to identify and analyze the IDT’s Vibration modes. Then the transducer was mounted on an aluminum plate, and the generated wavefield was measured with the 3D LDV.
According to this investigation, we demonstrate that it is possible to selectively excite desired guided wave mode, namely the A0 mode, suppressing the excitation of the S0 mode. Moreover, the measured wavefield allows for analysis of the directivity of the designed IDT. All in all the results show good correlation between theoretical predictions and measured values, thus allowing to use the current design in terms of selective excitation as it is.
Structural health monitoring (SHM) is a term that groups together techniques adopted to evaluate in a continued fashion the structural integrity and degradation of technical appliances. SHM is particularly attractive for components that are difficult to access or expensive to take off-line. Among many other techniques, SHM can be performed using ultrasonic guided waves (UGW) which have an advantage of traveling over Long distances. Various guided wave modes exist along with many methods for their generation and sensing, e.g by means of interdigital transducers (IDT). This contribution is dedicated to the design and characterization of a flexible piezopolymerbased IDT which allows for the selective excitation of UGW, resulting in more straightforward data analysis. The designed IDT was characterized using a 3D Laser Doppler Vibrometer (3D LDV) in the air to identify and analyze the IDT’s Vibration modes. Then the transducer was mounted on an aluminum plate, and the generated wavefield was measured with the 3D LDV.
According to this investigation, we demonstrate that it is possible to selectively excite desired guided wave mode, namely the A0 mode, suppressing the excitation of the S0 mode. Moreover, the measured wavefield allows for analysis of the directivity of the designed IDT. All in all the results show good correlation between theoretical predictions and measured values, thus allowing to use the current design in terms of selective excitation as it is.
Die chemische Analyse von Beton gehört bei der Ermittlung des Ist-Zustandes von Stahl- und Spannbetonbauwerken zu den grundlegenden Untersuchungen bei der Zustandserfassung. Der tiefenabhängige Chloridgehalt sowie der Karbonatisierungsfortschritt müssen bei der Bewertung des Ist-Zustandes, beim Instandsetzungsbedarf und ggf. bei der Planung eines erforderlichen Instandsetzungskonzeptes mit einbezogen werden. Seit Mitte der 1990er Jahre wird an der Bundesanstalt für Materialforschung und -prüfung die laserinduzierte Plasmaspektroskopie (engl. Laser-induced Breakdown Spectroscopy) – kurz LIBS – stetig für die chemische Analyse von Beton weiterentwickelt. In diesem Beitrag wird der aktuelle Stand der Forschung/ Technik und der Normungsarbeit präsentiert, sowie zukünftig mögliche Anwendungen vorgestellt. Mit den aktuellen LIBS-Systemen (mobiles LIBS-System sowie kommerziell erhältliche Laborsysteme) ist es möglich den Chloridgehalt ortsaufgelöst in wenigen Minuten zu quantifizieren, sogenannte Elementlandkarten zu erstellen und somit die Elementverteilung innerhalb des Betons zu visualisieren. Durch das Scannen eines Bohrkernquerschnittes und der simultanen Erfassung von mehreren Elementen mit einer Messung, ist es zudem möglich, die Gesteinskörnung in den Messdaten zu identifizieren und den Chloridgehalt auf die Zementsteinmatrix zu beziehen. Fehlerquellen aus der Umrechnung der betonbezogenen Chloridgehalte können dadurch minimiert werden. Neben den Grundlagen von LIBS werden vor allem aktuelle Praxisbeispiele vorgestellt, die die aktuellen Möglichkeiten des Verfahrens veranschaulichen.
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.
Due to the high sensitivity of coda waves to the smallest structural alterations such as strain, humidity or temperature changes, ultrasonic waves are a valid means to examine entire structures employing networks of ultrasonic transducers. In order to substantiate this ex ante assessment, the viability of measuring ultrasonic waves as a valid point of reference and inference for structural changes is to be further scrutinized in this work. In order to investigate the influence of mechanical strain on ultrasonic signals, a four-point bending test was carried out on a reinforced concrete beam at Ruhr University Bochum. Thus, measurements collected from a network of selected transducer pairings arranged across the central, shear-free segment of the test specimen, were correlated to their respective strain fields. Detected ultrasonic signals were evaluated employing Coda Wave Interferometry. Such analysis comprised the initial non-cracked state as well as later stages with incremental crack depth and quantity. It was to ascertain that the test specimen can in fact be qualitatively compartmentalized into areas of compression and tension identified via Relative Velocity Changes presented in Attribute Maps. However, since results did not entail a zero crossing, i.e., neither positive nor negative values were to be calculated, only relative changes in this work displayed staggered over the height of the object under test, are discussed. Under the given methodological premises, additional information is currently required to make quantitative assertions regarding this correlation of ultrasonic and strain results. This holds true for the comparability of the ultrasonic and strain results for both non-cracked and even the cracked state.
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.
Automatic segmentation of cracks using crack detection methods fails when applied on concrete with embedded reinforcements; it results in artifacts called false-detected cracks. We present a two-step approach to trace the cracks which reduces significantly detecting the false ones. In the first step, the reinforcements were found and removed from the 3D data set, and in the second step, the cracks were detected in the 3D data set free from reinforcements. To visualize and determine the structure and the degree of damages nondestructively, planar tomography as a special case of laminography was used.
Creep and fracture behavior of conventionally and additively manufactured stainless steel 316L
(2020)
A critical task within the frame of establishing process-structure-property-performance relationships in additive manufacturing (AM) of metals is producing reliable and well-documented material behavior’s data and knowledge regarding the structure-property correlation, including the role of defects. After all, it represents the basis for developing more targeted process optimizations and more reliable predictions of performance in the future. Within this context, this contribution aims to close the actual gap of limited historical data and knowledge concerning the creep behavior of the widely used austenitic stainless steel 316L, manufactured by Laser-Powder-Bed-Fusion (L-PBF). To address this objective, specimens from conventional hot-rolled and AM material were tested under application-relevant conditions according to existing standards for conventional material, and microstructurally characterized before and after failure. The test specimens were machined from single blocks from the AM material. The blocks were manufactured using a standard scan and build-up strategy and were subsequently heat-treated. The creep behavior is described and comparatively assessed based on the creep lifetime and selected creep curves and characteristic values. The effect of defects and microstructure on the material’s behavior is analyzed based on destructive and non-destructive evaluations on selected specimens. The AM material shows shorter creep lives, reaches the secondary creep stage much faster and at a lower strain, and features lower creep ductility compared to its conventional counterpart. The creep damage behavior of the AM material is more microstructure than defect controlled and is characterized by the formation and accumulation of single intergranular damage along the whole volume. Critical features identified are the grain morphology and the grain-boundary as well as the dislocation’s density. Micro-computed tomography (µCT) proves to be an alternative to metallography to analyze the creep damage.
Im Bereich der Zerstörungsfreien Prüfung (ZfP) im Bauwesen werden eine Vielzahl von Messdaten erfasst. Obwohl Sie als Grundlage für wissenschaftliche Analysen dienen, gibt es noch keine einheitliche Repräsentation der Daten. Eine Analyse verschiedener verteilter Datensätze über unterschiedliche Prüfobjekte hinweg ist daher kaum möglich.
Wir stellen einen Ansatz für ein integriertes Datenmanagement verteilter Datensätze auf Basis von Semantic-Web Technologien vor. Der Ansatz basiert im Kern auf einem mathematischen Modell – der sogenannten Ontologie – welches das Wissen unserer Domäne ZfPBau repräsentiert. Die von uns entwickelte ZfPBau Ontologie wird mit Datenquellen verknüpft und beschreibt so die semantische Bedeutung der Daten. Darüber hinaus fungiert die Ontologie als zentrales Konzept für den Datenbankzugriff. Domänen-fremde Datenquellen können durch die Verknüpfung mit der ZfPBau Ontologie einfach integriert werden und stehen zur generischen Nutzung im Sinne der Digitalisierung direkt zur Verfügung. Basierend auf einer umfangreichen Literaturrecherche, skizzieren wir die Möglichkeiten die sich daraus für die ZfP im Bauwesen ergeben, wie zum Beispiel Messdaten computergestützt zu sortieren, zu analysieren, Zusammenhänge zu erkennen und zu erklären.
Der erwartete Nutzen dieses Ansatzes der Wissensrepräsentation und des Datenzugriffs für die ZfP-Community ist eine Erweiterung des Wissens durch Datenaustausch in der Forschung (Interoperabilität), die wissenschaftliche Verwertung großer existierender Datenquellen mit datenbasierten Verfahren (wie Bilderkennung, Messunsicherheitsberechnungen, Faktoranaylsen, Materialcharackterisierung) und letztlich ein vereinfachter Transfer von ZFP-Daten in Ingenieurmodelle und somit in die Baupraxis.
Ontologien sind bereits Kern vielzähliger intelligenter Systeme wie Building-Information-Modeling oder Forschungsdatenbanken. Der Beitrag gibt einen Überblick über die Werkzeuge die wir derzeit für die Kommunikation mit ihnen schaffen.
Crack detection in steel bars at high surface temperatures is a critical problem in any manufacturing industry. Surface breaking cracks are the major problems during the billet casting. Many NDT techniques are proven its capability in crack detection at room temperature. Here, we are demonstrating the possibility of exposure of cracks using laser line thermography at higher surface temperatures (up to 600 °C). A continuous-wave (CW) laser is used to excite the sample kept at higher surface temperatures. The temperature distribution over the sample due to the laser line scanning is captured using a temperature calibrated infrared (IR) thermal camera. The response of the sample temperature in crack detection is investigated using a validated FE model. The impact of the oxide layer in crack detection is investigated by using two types of samples; one without any oxide layer and the second is with the oxide layer. The influence of laser power in the detection of defects at high temperatures is studied. 3D numerical models were developed for the cases; when the sample is with oxide layer and without any oxide layer for a better understanding of physics. The surface temperature rise due to laser heating is higher for the scaled sample compared to the no-scale sample. The presence of the oxide layer above the parent metal will reduce the reflectivity of the surface. Lower reflectivity will lead to increased absorption of incident energy so that the surface temperature rise will be higher than the surface with no scale. Thermal contrast linearly depends on laser power, which means higher laser power will increase the defect detectability even at a higher surface temperature.
Design and Implementation of Smart Multisensor Monitoring System for Safe Workplaces with LoRaWAN
(2020)
This project addresses the application of safe workplaces in offices and chemical laboratories where indoor air quality plays an important role. The LoRaWAN (Long Range Wide Area Network) is used as a communication interface to make important sensor data globally accessible. The goal of the development is to create a sensor node and an online and offline solution that collects the data from the sensor nodes and stores it on a local server or in a cloud. In cooperation with the companies WISTA GmbH and IONOS, a test sensor network is going to be established in the Berlin-Adlershof area.
Herein, we present a detailed investigation of the electrochemically triggered formation and dissolution processes of α- and β-sulfur crystals on a monolithic carbon cathode using operando high-resolution synchrotron radiography (438 nm/pixel).
The combination of visual monitoring with the electrical current response during cyclic voltammetry provides valuable insights into the sulfur formation and dissolution mechanism. Our observations show that the crystal growth process is mainly dictated by a rapid equilibrium between long-chain polysulfides on one side and solid sulfur/short-chain polysulfides on the other side, which is consistent with previous studies in this field. The high temporal and spatial resolution of synchrotron imaging enables the observation of different regimes during the sulfur formation and dissolution process. The appearance of short-chain polysulfides after the first anodic CV peak initiates a rapid dissolution process of α-sulfur crystals on the cathode. The increase in the long-chain lithium polysulfide concentration at the cathode surface during charge results in an increased crystal growth rate, which in turn produces imperfections in α- and β-sulfur crystals. There are strong indications that these defects are fluid inclusions, which may trap dissolved polysulfides and therefore reduce the electrochemical cell capacity.
Thanks to its good strength/mass ratio, a glass fibre reinforced plastic (GFRP) composite is a common material widely used in aviation, power production, automotive and other industries. In its turn, active infrared (IR) nondestructive testing (NDT) is a common inspection technique for detecting and characterizing structural defects in GFRP. Materials to be tested are typically subjected to optical heating which is supposed to occur on the material surface. However, GFRP composite is semitransparent for optical radiation of both visual and IR spectral bands. Correspondingly, the inspection process represents a certain combination of both optical and thermal phenomena. Therefore, the known characterization algorithms based on pure heat diffusion cannot be applied to semi-transparent materials. In this study, the phenomenon of GFRP semi-transparency has been investigated numerically and experimentally in application to thermal NDT. Both Xenon flash tubes and a laser have been used for thermal stimulation of opaque and semi-transparent test objects. It has been shown that the Penetration of optical heating radiation into composite reduces detectability of shallower defects, and the signal-to-noise ratio can be enhanced by applying the technique of thermographic signal reconstruction (TSR). In the inspection of the semi-transparent GFRP composite, the most efficient has been the laser heating followed by the TSR data processing. The perspectives of defect characterization of semi-transparent materials by using laser heating are discussed. A neural network has been used as a candidate tool for evaluating defect depth in composite materials, but its training should be performed in identical with testing conditions.
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.
Detection of Multiple Cracks in Four-Point Bending Tests Using the Coda Wave Interferometry Method
(2020)
The enlargement of the cracks outside the permitted dimension is one of the main causes for the reduction of service life of Reinforced Concrete (RC) structures. Cracks can develop due to many causes such as dynamic or static load. When tensile stress exceeds the tensile strength of RC, cracks appear. Traditional techniques have limitations in early stage damage detection and localisation, especially on large-scale structures. The ultrasonic Coda Wave Interferometry (CWI) method using diffuse waves is one of the most promising methods to detect subtle changes in heterogeneous materials, such as concrete. In this paper, the assessment of the CWI method applied for multiple cracks opening detection on two specimens based on four-point bending test is presented. Both beams were monitored using a limited number of embedded Ultrasonic (US) transducers as well as other transducers and techniques (e.g., Digital Image Correlation (DIC), LVDT sensors, strain gauges, and Fiber Optics Sensor (FOS)). Results show that strain change and crack formation are successfully and efficiently detected by CWI method even earlier than by the other techniques. The CWI technique using embedded US transducers is undoubtedly a feasible, efficient, and promising method for long-term monitoring on real infrastructure.
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-6Al4V alloy. We show that (a) the transverse isotropy of the material yields good agreement between the best-fit isotropy approximation (equivalent to the classic Kröner’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.
The moisture content of the subfloor has to be determined before installation to avoid damages of the floor covering. Only if the readiness for layering is reached, an installation without damages can be expected in all cases. In general, three different approaches exist to measure the residual water content: determination of the moisture content, determination of the water release, or determination of the corresponding relative humidity. All three approaches are tested in laboratory at eight different screed types including two different samples thicknesses in each case. The moisture content and the water release are measured by sample weighing, the corresponding relative humidity is measured by embedded sensors. All three approaches are compared and correlated to each other. The evaluations show only weak correlation and, in several cases, contradicting results. Samples are considered as being ready for layering and not-being ready for layering at the same time, depending on the chosen approach. Due to these contradicting results, a general threshold for the risk of damage cannot be derived based on these measurements. Furthermore, the experiment demonstrates that the measurement of corresponding relative humidity is independent of the considered screed type or screed composition. This makes the humidity measurement to very promising approach for the installation of material moisture monitoring systems in the future.
Reinforced concrete and several other building materials deteriorate during their service life. Almost all deterioration processes are related to moisture. For understanding those processes, knowing the exact amount of the moisture content and the moisture transport characteristics is crucial. In fact, the moisture transport in porous materials is a two-phase flow; consisting of the vapour and the liquid phase. The two corresponding parameters are the diffusion coefficient and the hydraulic conductivity. By means of an inverse approach, these two coefficients are experimentally determined. The moisture transport of eight different screed types during hydration and evaporation is monitored based on embedded humidity sensors. The measured humidity profiles are converted into a pore saturation by adapting the approach of Hillerborg to the measured pore volume distribution. The summation of all pore saturations yields the total moisture content including the ink-bottle effect during desorption. The pore volume distribution was determined by mercury intrusion porosimetry as well as by gas adsorption. The measurement of the humidity and the pore saturation in the entire sample enables to invert the mass balance in order to extract the diffusion coefficient and the hydraulic conductivity. The determined diffusion coefficients of the eight investigated screeds are between m2s-1 and m2s-1.
Rund ein Jahr haben DIN und DKE in einem gemeinsamen Projekt mit dem Bundesministerium für Wirtschaft und Energie und zusammen mit ca. 300 Fachleuten aus Wirtschaft, Wissenschaft, öffentlicher Hand und Zivilgesellschaft an der Normungsroadmap Künstliche Intelligenz gearbeitet. Eine hochrangige Steuerungsgruppe unter dem Vorsitz von Prof. Wolfgang Wahlster hat die Erarbeitung koordiniert und begleitet.
Ziel der Roadmap ist die frühzeitige Entwicklung eines Handlungsrahmens für die Normung und Standardisierung, der die internationale Wettbewerbsfähigkeit der deutschen Wirtschaft unterstützt und europäische Wertmaßstäbe auf die internationale Ebene hebt.(...)
Das Thema Wasserstoff ist an der BAM seit mehr als hundert Jahren aktuell und steht auch gegenwärtig im Zentrum zahlreicher Forschungs- und Kooperationsaktivitäten. Mit der aktuellen Wasserstoff-Strategie der BAM werden wichtige Voraussetzungen dafür geschaffen, dass der Markthochlauf gelingt und die technische Sicherheit und Überwachung der Infrastrukturen und Anlagen gewährleistet ist – von der Erzeugung, über den Transport bis zur Speicherung und Bereitstellung von Wasserstoff als Energieträger der Zukunft.
A Kramers-Kronig (KK) receiver is applied to a phase-sensitive optical time domain reflectometry based on direct detection. An imbalanced Mach-Zehnder interferometer with a 2× 2 coupler is used in sensing system to encode the phase information into optical intensity. The directly obtained signal is treated as the in-phase component, and the KK receiver provides the quadrature component by Hilbert transform of the obtained signal, so that the optical phase can be retrieved by IQ demodulation. The working principle is well explained, and the obtained phase variance is theoretically analyzed. The experiment demonstrates the functionality of the sensor and validates the theoretical analysis.
X-ray computed tomography has many applications in materials science and non-destructive testing. While the standard filtered back-projection reconstruction of the radiographic data sets 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.