5 Werkstofftechnik
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Im statistischen Mittel steht eine Windkraftanlage (WKA) in Deutschland alle 6 Jahre wegen eines Schadens an den Rotorblättern und verursacht Kosten von 20k€-40k€ infolge Ertragsausfall und Reparaturkosten. Bei über 30.000 WKA in Deutschland verursacht dies jährlichen Kosten von 100-200 Mio. €. Zu 70% sind die Ursachen Fertigungsfehler. Diesem Themenkomplex widmet sich FB-5.3 in Kooperation mit FBs der Zerstörungsfreien Prüfung (Abt. 8) schon seit Jahren.
Im aktuellen Projekt geht es um einen vorzeitigen Verschleiß der Rotorblätter infolge der Verwendung gealterter Glasfaser-Rovings. (GF). Die Entwicklung moderner Windkraftanlagen hatte in Europa seinen Ursprung in den 90er Jahren. OEMs und GF-Hersteller waren dicht beisammen. Die Globalisierung des Marktes führt heute zu einer weltweiten Verschiffung der GF in feucht-warmen Containern. Je nach Beschaffenheit (Chemie) der Schlichten (Oberflächenbehandlung) von GF können diese stark altern (Hydrolyse-Effekte) und die Festigkeit kann im Bauteil um bis zu 50% abgemindert sein.
In einer Kooperation mit der Rotorblattallianz, einem Zusammenschluss der OEMs, Halbzeugherstellern und Forschungsinstituten, wurden schon vor 5 Jahren in einem Forschungsprojekt (FB-5.3; VH 5538) die chemischen Mechanismen der Alterung exemplarisch für eine Glasfaser-Roving-Type aufgeklärt. Im aktuellen Projekt (FB-5.3; VH 5304) wird ein beschleunigtes Alterungsverfahren (erhöhte Temperatur und Feuchte) am Roving im un-impregnierten Zustand entwickelt und die Festigkeit nachfolgend nach Einbettung in eine Epoxid-Harz-Matrix bestimmt. Je nach Alterungszustand zeigt sich eine Abnahme der Zwischenfaserbruchfestigkeit von bis zu 50%. Nicht alle Glasfaser-Roving-Typen zeigen diesen Effekt. Es ist gelungen für OEMs und Halbzeughersteller ein handhabbares Verfahren zur innerbetrieblichen Qualitätssicherung zu entwickeln, da die wenigsten Firmen über komplexe Analyseverfahren, wie an der BAM, verfügen.
Inconel 718 (IN718) is a traditional age-hardenable nickel-based alloy that has been increasingly processed by additive manufacturing (AM) in recent years. In the as-solidified condition, IN718 exhibits chemical segregation and the undesired Laves phase, requiring a solution annealing (SA) prior to aging. The material produced by AM does not respond to the established thermal routines in the same way as conventionally produced IN718, and there is still no consensus on which routine yields optimal results. This work aims to provide a fundamental understanding of the heat treatment (HT) response by continuously monitoring the microstructural evolution during SA via time-resolved synchrotron x-ray diffraction, complemented by ex-situ scanning electron microscopy (SEM). The samples were produced by laser powder bed fusion to a geometry of 10x20x90 mm³, from which Ø1x5 mm³ cylindric specimens were extracted. Two different scanning strategies – incremental 67° rotations, Rot, and alternating 0°/67° tracks, Alt – were used, leading to two different as-built conditions. 1-hour SAs were carried out in the beamline ID22 of the ESRF at 50 KeV. Two SA temperatures, SA1 = 1020 °C, and SA2 = 1080 °C were tested for each scanning strategy. Data were processed using the software PDIndexer. In the as-built state, all samples showed typical subgrain columnar cell structures with predominant Nb/Mo segregation and Laves phase at the cell walls, as seen by SEM. The Alt scan induced higher intensity on the Laves peaks than the Rot scan, suggesting a greater content of Laves. Chemical homogenization in the SA was largely achieved during the heating ramp (Fig. 1). SA2 eliminated the Laves peaks just before reaching 1080 °C, and mitigated differences between Rot and Alt samples. On the other hand, SA1 induced the precipitation of the generally detrimental δ phase, also observed by SEM. Furthermore, the Rot scan showed higher δ peak intensities than the Alt scan, indicating a higher content of δ in the latter. No signs of recrystallization were observed in any of the investigated SAs.
Zirconium vanadate (ZrV2O7) is a well-known negative thermal expansion (NTE) material that exhibits significant isotropic contraction over a broad temperature range (~150°C < T < 800°C). Therefore, it can be used to create composites with controllable expansion coefficients and prevent thermal stress, fatigue, cracking, and deformation at interfaces. We implement interdisciplinary research to analyze such material. We study the influence of the synthesis methods and their parameters on the sample's purity, crystallinity, and homogeneity. Moreover, we implement ab initio-based vibrational computations with partially treated anharmonicity in combination with experimental methods to follow temperature-induced structural changes and rationalize the negative thermal expansion in this material, including the influence of the local structure disorder.
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
The materials mechanical testing ontology (MTO) was developed by collecting the mechanical testing vocabulary from ISO 23718 standard, as well as the standardized testing processes described for various mechanical testing of materials like tensile testing, Brinell hardness test, Vickers hardness test, stress relaxation test, and fatigue testing. Confirming the ISO/IEC 21838-2 standard, MTO utilizes the Basic Formal Ontology (BFO), Common Core Ontology (CCO), Industrial Ontologies Foundry (IOF), Quantities, Units, Dimensions, and data Types ontologies (QUDT), and Material Science and Engineering Ontology (MSEO) as the upper-level ontologies. Reusing these upper-level ontologies and materials testing standards not only makes MTO highly interoperable with other ontologies but also ensures its acceptance and applicability in the industry. MTO represents the mechanical testing entities in the 230 classes and four main parts: i) Mechanical testing experiments entities like tensile, hardness, creep, and fatigue tests as the subclasses of mseo:Experiment, ii) Mechanical testing quantity concepts such as toughness, elongation, and fatigue strength in the appropriate hierarchies of bfo:Disposition and bfo:Quality classes, iii) Mechanical testing artifacts like indenter as the subclasses of cco:Artifact, and iv) mechanical testing data like the stress-strain, S-N, or creep curves as the subclasses of cco:InformationContentEntity. MTO is publicly available via the KupferDigital GitLab repository.
Nickel-based alloys have been widely used for gas turbine blades owing to their excellent mechanical properties and corrosion resistance at high temperatures. The operating temperatures of modern gas turbines have been increased in pursuit of increased thermal efficiency. Turbine blades are exposed to these high temperatures combined with mechanical stresses, resulting in material damage through creep, fatigue, and other mechanisms. These turbine blades must be regularly inspected and replaced as needed, to prevent the loss of efficiency, breakdown, and catastrophic failure. Repair of the damaged turbine blades is often a more practical and cost-effective option than replacement, as replacement is associated with high costs and loss of material resources. To this end, state-of-the-art repair technologies including different additive manufacturing and brazing processes are considered to ensure efficient repair and optimum properties of repaired components.
In any repaired part, materials property-mismatches and/or inner defects may facilitate the crack initiation and propagation and thus reduce the number of load cycles to failure. Therefore, a fundamental understanding of the fatigue crack growth and fracture mechanisms in joining zones is required to enable the prediction of the remaining life of repaired components and to further improve and adapt the repair technologies.
Fatigue crack growth experiments have been conducted on SEN (Single Edge Notch) specimens joined via brazing, and pre-sintered Preform (PSP) and multi-materials (casted/printed) specimens layered via additive manufacturing (AM). The experiments were performed at 950 °C and various stress ratios. The crack growth was measured using DCPD (Direct Current Potential Drop) method. The stress intensity factors for joined SEN specimens were calculated using the finite element method and then used to derive the fatigue crack growth curves. Metallographic and fractographic analyses were conducted to get insight into the fracture mechanism.
Results show that the experimental technique for fatigue crack growth was successfully adapted and applied for testing joined specimens. Furthermore, the initial tests indicate that the investigated braze filler material provides a lower resistance to crack growth, and bonding defects cause a crack to deviate to the interface of the base material and joining zone. In AM-sandwich specimens, the crack growth rates are significantly reduced when the crack reaches the interface of printed material and casted material. The obtained crack growth data can be used to calibrate a crack growth model, which will further be utilized to predict the remaining life of repaired components.
Experimentally informed multiscale creep modelling of additive manufactured Ni-based superalloys
(2023)
Excellent creep resistance at elevated temperatures, i.e. T / T_m> 0.5, due to γ-γ’ microstructure is one of the main properties of nickel-based superalloys. Due to its great importance for industrial applications, a remarkable amount of research has been devoted to understanding the underlying deformation mechanism in a wide spectrum of temperature and loading conditions. Additive manufactured (AM) nickel-based superalloys while being governed by similar γ-γ’ microstructure, exhibit AM-process specific microstructural characteristics, such as columnar grains, strong crystallographic texture (typically <001> fiber texture parallel to build direction) and compositional inhomogeneity, which in turn leads to anisotropic creep response in both stationary and tertiary phases.
Despite the deep insights achieved recently on the correlation between process parameters and the resulting microstructure, the anisotropic creep behavior and corresponding deformation mechanism of these materials are insufficiently understood so far. One reason for this is the lack of capable material models that can link the microstructure to the mechanical behavior. To overcome this challenge, a multiscale microstructure-based approach has been applied by coupling crystal plasticity (CP) and polycrystal model which enables the inclusion of different deformation mechanisms and microstructural characteristics such as crystallographic texture and grain morphology. The method has been applied to experimental data for AM-manufactured INCONEL-738LC (IN738). The effect of different slip systems, texture, and morphology on creep anisotropy at 850°C has been investigated. Results suggest a strong correlation between superlattice extrinsic stacking fault (SESF) and microtwinning and observed creep anisotropy.
Recent advances in Deep Learning (DL) have significantly impacted the field of materials modelling. DL tools have been recently considered as promising tools to address the complex relationships among processing, microstructure and property of materials. The thermal stability of polycrystalline materials is a highly interesting and complex problem that could be addressed using DL techniques. The Multi-Phase-Field (MPF) method has emerged as a powerful tool for addressing grain growth phenomena from multiple perspectives. Unlike sharp-interface based methods, the MPF approach bypasses the need for detailed information on individual grains. In this work, we use DL to address issues related to MPF simulations of grain growth including numerical efficiency, computing speed, and resource consumption. This presents specific challenges for high-performance computing (HPC) due to the large datasets and complex computations required by both MPF and DL methods. We study various 3D microstructure settings with the goal of accelerating the simulation process while exploring different physical effects. In particular, the impact of grain boundary and triple junction energies on grain growth are to be investigated. The results will be presented in terms of the evolving size and shape distribution of the grains.
Many metallic materials gain better mechanical properties through controlled heat treatments. For example, in age-hardenable aluminium alloys, the strengthening mechanism is based on the controlled formation of nanometre-sized precipitates, which represent obstacles to dislocation movement and consequently increase the strength. Precise tuning of the material microstructure is thus crucial for optimal mechanical behaviour under service condition of a component. Therefore, analysis of the microstructure, especially the precipitates, is essential to determine the optimum parameters for the interplay of material and heat treatment. Transmission electron microscopy (TEM) is utilized to identify precipitate types and orientations in the first step. Dark-field imaging (DF-TEM) is often used to image the precipitates and thereafter quantify their relevant dimensions. Often, these evaluations are still performed by manual image analysis, which is very time-consuming and to some extent also poses reproducibility problems.
Our work aims at a semantic representation of an automatable digital approach for this material specific characterization method under adaption of FAIR data practices. Based on DF-TEM images of different precipitation states of a wrought aluminium alloy, the modularizable, digital workflow of quantitative analysis of precipitate dimensions is described. The integration of this workflow into a data pipeline concept will also be discussed. Using ontologies, the raw image data, their respective contextual information, and the resulting output data of the quantitative image analysis can be linked in a triplestore. Publishing the digital workflow and the ontologies will ensure data reproducibility. In addition, the semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability.
We report about a joint project aiming at the digitalization of a lab course in materials testing. The undergraduate students were asked to prepare samples of a precipitation hardened aluminum alloy and characterize them using hardness and tensile tests. In a first step, we developed the frames for the digital labor notebook using eLabFTW. The primary data and the relevant metadata of each run were saved in a central database and made available for analysis and report issues. The whole set of results produced in a course was made available in the database. This database can be improved and serve as an open repository for data on this specific alloy.
The logical frame for the joint project was provided by the PMD Core Ontology (PMDco), a mid-level ontology that enables the representation and description of processes and process chains in an MSE-specific manner, ensuring full traceability of generated data. For the digitalization of this lab course, the tensile test ontology (TTO) was applied which is designed as a module of the PMDco using strongly related semantic concepts.