5 Werkstofftechnik
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Organisationseinheit der BAM
- 5 Werkstofftechnik (18)
- 5.1 Mikrostruktur Design und Degradation (18)
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- 7.6 Korrosion und Korrosionsschutz (6)
- 9 Komponentensicherheit (6)
- 9.4 Integrität von Schweißverbindungen (4)
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- 8.0 Abteilungsleitung und andere (2)
- 9.6 Additive Fertigung metallischer Komponenten (2)
Fractography plays a critical role in failure analysis of engineering components and has a considerable importance for safety investigations. Usually, the interpretation of fracture surfaces is done by experts with the help of literature and experimental data, that requires a lot of experience. The use of deep learning (DL) with neural networks in failure analysis becomes more and more relevant with the rapidly developing possibilities. Especially, the modern network architectures can assist fractographers in determining various fracture features on SEM images of the fracture surfaces. The basis for the best possible evaluation is the understanding of the influence of the input data used for training deep neural networks (DNN). Therefore, this study discusses the influence of the selection of the input data used for the prediction quality of these networks in order to take this into account for future data acquisition. Specimens of various metallic materials were subjected to fatigue cracking experiment under laboratory conditions. The fractured surfaces were then imaged using various modes or detectors (such as SE, BSE and topography) in SEM, and those captured images were used to create a training data set. The relevance of the individual data for the quality of the prediction is determined by a specific combination of the different detector data. For the training, the well-established architecture of a UNet-ResNet34 with a fixed set of hyperparameters is used. It has been found in this present study that the combination of all input data significantly increases the prediction accuracy, whereby even the combination of SE and BSE data provides considerable advantages over the exclusive use of SE images.
Die klassische Metallographie basiert auf Abbildungen einzelner Schliffebenen und kann auf räumliche Formen und Anordnungen des Gefüges nur bedingt schließen. Die Idee, aus metallographischen Serienschliffen dreidimensionale Gefügestrukturen zu rekonstruieren, ist daher naheliegend und nicht neu. Allerdings ist der Aufwand, in Handarbeit viele Einzel-Schliffe zu präparieren und zu Bildstapeln zusammenzusetzen, sehr hoch und steht einer häufigen Anwendung entgegen.
Deshalb wird an der BAM ein Roboter-gestütztes 3D-Metallographie-System entwickelt, das an einer Schliffprobe die Schritte Präparation und Bildeinzug vollautomatisch mit vielen Wiederholungen ausführt. Die Präparation umfasst Schleifen, Polieren und optional Ätzen der Schlifffläche, der Bildeinzug autofokussierte lichtmikroskopische Aufnahmen bei mehreren Vergrößerungsstufen. Der erhaltene Bildstapel wird anschließend vorverarbeitet, segmentiert und in ein 3D-Modell umgesetzt, das einer mikrotomographischen Aufnahme ähnelt, allerdings mit besserer lateraler Auflösung bei großem Volumen. Im Gegensatz zu tomographischen Verfahren besteht die Möglichkeit der Kontrastierung durch klassische chemische Ätzung. Die Integration eines REMs ist geplant. Bislang durchgeführte Arbeiten verdeutlichen die Möglichkeiten der Darstellung von Heißgas-Korrosionsschichten, Grauguss-Werkstoffen und Keramik-basierten mikroelektronischen Strukturen (Vias).
Die AG Fraktographie im DVM/DGM-Gemeinschaftsgremium „Elektronenmikroskopie in der Materialforschung“ betreibt seit 2013 eine fraktographische online-Datenbank („FractoDB“), die für das interessierte Fachpublikum kostenfrei zur Verfügung steht. Die Analyse und Bewertung von Bruchflächen und der darauf befindlichen Bruchmerkmale ist ein wichtiger Teilaspekt der Schadensanalyse bei der Suche nach Schadensmechanismen und Schadensursachen. Risse und Brüche an realen Bauteilen können nur dann bewertet werden, wenn gut dokumentierte Vergleichsbrüche aus Laborversuchen zur Verfügung stehen, sei es an Proben oder an Vergleichs-Bauteilen. Daher trägt die AG Fraktographie Bildmaterial zusammen, führt systematisch Laborversuche und Ringversuche durch und analysiert Brüche aus Schadensfällen. Die gewonnenen Daten werden zu Datensätzen zusammengestellt und über die Datenbank zugänglich gemacht. Derzeit ist ein Bestand von über 400 Datensätzen mit insgesamt über 4.500 Bildern verfügbar, welcher durchsucht werden kann und in Anlehnung an die VDI 3822 organisiert ist. Weitere Aktivitäten der AG Fraktographie, die in der FractoDB abgebildet werden, sind u.a. die Entwicklung einer fraktographischen Symbolik und die Analyse von Bruchmerkmalen mittels Machine Learning. Über die aktuellen Ergebnisse und Planungen wird berichtet.
In failure analysis, micro-fractographic analysis of fracture surfaces is usually performed based on practical knowledge which is gained from available studies, own comparative tests, from the literature, as well as online databases. Based on comparisons with already existing images, fracture mechanisms are determined qualitatively. These images are mostly two-dimensional and obtained by light optical and scanning electron imaging techniques. So far, quantitative assessments have been limited to macrocopically determined percentages of fracture types or to the manual measurement of fatigue striations, for example. Recently, more and more approaches relying on computer algorithms have been taken, with algorithms capable of finding and classifying differently structured fracture characteristics. For the Industrial Collective Research (Industrielle Gemeinschaftsforschung, IGF) project “iFrakto” presented in this paper, electron-optical images are obtained, from which topographic information is calculated. This topographic information is analyzed together with the conventional 2D images. Analytical algorithms and deep learning are used to analyze and evaluate fracture characteristics and are linked to information from a fractography database. The most important aim is to provide software aiding in the application of fractography for failure analysis. This paper will present some first results of the project.
The round robin test investigated the reliability users can expect for AlSi10Mg additive manufactured specimens by laser powder bed fusion through examining powder quality, process parameter, microstructure defects, strength and fatigue. Besides for one outlier, expected static material properties could be found. Optical microstructure inspection was beneficial to determine true porosity and porosity types to explain the occurring scatter in properties. Fractographic analyses reveal that the fatigue crack propagation starts at the rough as-built surface for all specimens. Statistical analysis of the scatter in fatigue using statistical derived safety factors concludes that at a stress of 36.87 MPa the fatigue limit of 107 cycles could be reached for all specimen with a survival probability of 99.999 %.
A global transition towards more sustainable, affordable and reliable energy systems is being stimulated by the Paris Agreement and the United Nation's 2030 Agenda for Sustainable Development. This poses a challenge for the corrosion industry, as building climate‐resilient energy systems and infrastructures brings with it a long‐term direction, so as a result the long‐term behaviour of structural materials (mainly metals and alloys) becomes a major prospect. With this in mind “Corrosion Challenges Towards a Sustainable Society” presents a series of cases showing the importance of corrosion protection of metals and alloys in the development of energy production to further understand the science of corrosion, and bring the need for research and the consequences of corrosion into public and political focus. This includes emphasis on the limitation of greenhouse gas emissions, on the lifetime of infrastructures, implants, cultural heritage artefacts, and a variety of other topics.
In the current study, the 3D nature of the melt pool boundaries (MPBs) in a 316 L austenitic steel additively manufactured by laser-based powder bed fusion (L-PBF) is investigated. The change of the cell growth direction and its relationship to the MPBs is investigated by transmission electron microscopy. A hitherto unreported modulated substructure with a periodicity of 21 nm is further discovered within the cell cores of the cellular substructure, which results from a partial transformation of the austenite, which is induced by a Ga+ focused ion beam. While the cell cores show the modulated substructure, cell boundaries do not. The diffraction pattern of the modulated substructure is exploited to show a thickness ≥200 nm for the MPB. At MPBs, the cell walls are suppressed, leading to continuously connecting cell cores across the MPB. This continuous MPB is described either as overlapping regions of cells of different growing directions when a new melt pool solidifies or as a narrow planar growth preceding the new melt pool.
To set up recommendations on how to define “reasonable minimum composition thresholds” for CO2 streams to access CO2 pipeline networks, we investigated potential impacts of CO2 streams with different and temporally variable compositions and mass flow rates along the CCS chain. All investigations were based on a generic “CCS cluster scenario” in which CO2 streams captured from a spatial cluster of eleven emitters (seven fossil-fired power plants, two cement plants, one refinery and one steel mill) are collected in a regional pipeline network. The resulting CO2 stream (19.78 Mio t impure CO2 per year) is transported in a trunk line (onshore and offshore) and injected into five generic replicate storage structures (Buntsandstein saline aquifers) offshore. Experimental investigations and modeling of selected impacts revealed beneficial as well as adverse impacts of different impurities and their combinations. Overall, no fundamental technical obstacles for transporting, injecting and storing CO2 streams of the considered variable compositions and mass flow rates were observed. We recommend to define minimum composition thresholds for each specific CCS project through limiting
i) the overall CO2 content,
ii) maximum contents of relevant impurities or elements,
iii) acceptable variability of concentrations of critical impurities, and defining impurity combinations to be avoided.
Undetected and undesired microstructural variations in components produced by laser powder bed fusion are a major challenge, especially for safety-critical components. In this study, an in-depth analysis of the microstructural features of 316L specimens produced by laser powder bed fusion at different levels of volumetric energy density and different levels of inter layer time is reported. The study has been conducted on specimens with an application relevant build height
(>100 mm). Furthermore, the evolution of the intrinsic preheating temperature during the build-up of specimens was monitored using a thermographic in-situ monitoring set-up. By applying recently determined emissivity values of 316L powder layers, real temperatures could be quantified. Heat accumulation led to preheating temperatures of up to about 600 °C. Significant differences in the preheating temperatures were discussed with respect to the individual process parameter combinations, including the build height. A strong effect of the inter layer time on the heat accumulation was observed. A shorter inter layer time resulted in an increase of the preheating temperature by more than a factor of 2 in the upper part of the specimens compared to longer inter layer times. This, in turn, resulted in heterogeneity of the microstructure and differences in material properties within individual specimens. The resulting differences in the microstructure were analyzed using electron back scatter diffraction and scanning electron microscopy. Results from chemical analysis as well as electron back scatter diffraction measurements indicated stable conditions in terms of chemical alloy composition and austenite phase content for the used set of parameter combinations. However, an increase of the average grain size by more than a factor of 2.5 could be revealed within individual specimens. Additionally, differences in feature size of the solidification cellular substructure were examined and a trend of increasing cell sizes was observed. This trend was attributed to differences in solidification rate and thermal gradients induced by differences in scanning velocity and preheating temperature. A change of the thermal history due to intrinsic preheating could be identified as the main cause of this heterogeneity. It was induced by critical combinations of the energy input and differences in heat transfer conditions by variations of the inter layer time. The microstructural variations were directly correlated to differences in hardness.
For reliability and safety issues of injection wells, corrosion resistance of materials used needs to be determined. Herein, representative low-cost materials, including carbon steel X70/1.8977 and low alloyed steel 1.7225, were embedded in mortar to mimic the realistic casing-mortar interface. Two types of cement were investigated: (1) Dyckerhoff Variodur commercial Portland cement, representing a highly acidic resistant cement and (2) Wollastonite, which can react with CO2 and become stable under a CO2 stream due to the carbonation process. Exposure tests were performed under 10 MPa and at 333 K in artificial aquifer fluid for up to 20 weeks, revealing crevice corrosion and uniform corrosion instead of expected pitting corrosion. To clarify the role of cement, simulated pore water was made by dispersing cement powder in aquifer fluid and used as a solution to expose steels. Surface analysis, accompanied by element mapping on exposed specimens and their crosssections, was carried out to trace the chloride intrusion and corrosion process that followed.