5 Werkstofftechnik
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Eingeladener Vortrag
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The collaborative project “Impacts of impurities in CO2 streams captured from different emitters in a regional cluster on transport, injection and storage (CLUSTER)” aimed to set up recommendations on how to define “reasonable minimum composition thresholds” that CO2 streams should meet when accessing CO2 transport pipeline networks. Within CLUSTER, we investigated potential impacts of CO2 streams with different and temporally variable compositions and mass flow rates along the whole CCS chain. Investigations included, amongst others, impacts on: Corrosion of pipeline steel, pipeline network design and related transport costs, alteration of well bore cements, pressure development and rock integrity, geochemical reactions, and petrophysical and geomechanical rock properties.
All investigations are based on a generic CCS chain scenario. In this scenario, CO2 streams are captured from a spatial cluster of eleven emitters and collected in a regional pipeline network. Emitters comprise seven fossil fuel-fired power plants equipped with different capture technologies, two cement plants, one refinery and one integrated iron and steel plant. In total, 19.78 Mio t CO2 (including impurities) are captured in the emitter cluster annually. The combined CO2 stream is transported in a trunk line with a length of 400 km (100 km of these offshore) and is injected into five generic storage structures. The storage reservoirs are saline aquifers of the Buntsandstein.
The investigations revealed beneficial and deteriorating impacts of different impurities and combinations thereof. Overall, no fundamental technical obstacles for transporting, injecting and storing CO2 streams of the modelled variable compositions and mass flow rates were observed. Based on the results, the CLUSTER project team recommends not to define “minimum composition thresholds” for CO2 streams as strict threshold values for each individual impurity in the stream. Instead, CO2 stream compositions and variabilities for specific CCS projects should be constrained with regard to a set of parameters including i) the overall CO2 content, ii) maximum contents of relevant impurities or elements, iii) acceptable variability of CO2 stream composition, and iv) impurity combinations to be avoided.
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.
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.
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.
According to the definition of the ASM handbook [1,3], a defect is "an imperfection. that can be shown to cause failure by a quantitative analysis and that would not have occurred in the absence of the imperfection". The topic of the present three-part review is a discussion of defects which can cause failure in cyclically loaded structures. The features discussed comprise material defects such as non-metallic inclusions, pores or micro-shrinkages, etc. and geometric defects such as surface roughness and secondary notches which have their origin in manufacturing, and defects such as surface damage due to scratches, impact events or contact fatigue as well as corrosion pits which arise in service. In this first part, the discussion is prefaced by an introduction to basic aspects which are essential for a deeper understanding of the characteristics and mechanisms how the defects influence fatigue crack initiation and propagation. These include the life cycle of a fatigue crack from initiation up to fracture, crack arrest, multiple crack initiation and coalescence, and the material and geometrical properties affecting these.
This third part of the review on defects as root cause of fatigue failure addresses cavities (pores, micro-shrinkages, unmelted regions), defective microstructures and microcracks as material defects and defects due to local damage during manufacturing, service and maintenance such as dents, scratches and localized corrosion. In addition, damage due to contact fatigue and the effect of surface roughness are discussed in the context of fatigue failure. Also addressed is the competition between different kinds of defects in controlling the initiation and early growth of fatigue cracks.
Defects as a root cause of fatigue failure of metallic components. II: Non-metallic inclusions
(2019)
This second part of the review on defects as root cause of fatigue failure comprises the origin, the nature and the effects of non-metallic inclusions. Topics addressed are the different kinds of inclusions formed during the manufacturing process, various types of mis-match causing local stresses and, as a consequence, fatigue crack initiation, and effects of characteristics such as size, morphology, localization, spatial distribution and orientation of the defects on the fatigue behavior. Methods for inclusion counting and sizing are discussed along with statistical aspects necessary to be considered when evaluating structural components.