5 Werkstofftechnik
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- Additive Manufacturing (36)
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Organisationseinheit der BAM
- 5 Werkstofftechnik (321)
- 5.1 Mikrostruktur Design und Degradation (90)
- 5.2 Metallische Hochtemperaturwerkstoffe (85)
- 5.4 Multimateriale Fertigungsprozesse (74)
- 5.5 Materialmodellierung (37)
- 5.6 Glas (36)
- 5.3 Polymere Verbundwerkstoffe (34)
- 8 Zerstörungsfreie Prüfung (29)
- 9 Komponentensicherheit (29)
- 7 Bauwerkssicherheit (27)
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.
3D structural investigations are described by X-ray laminography studies of sandwich shell segments, made of a PVC foam core, covered by non-crimp fabric glass fibre composite lay-ups processed by vacuum assisted resin infusion of epoxy. The specific scope of this study is to image transversal flaws within the foam core (joints) and of single ply overlaps. Test flaws were purposely implemented in order to simulate typical failure under cyclic load. In a dedicated test rig for shell structures, the flaw evolution/propagation is monitored by thermography and optical 3D inspection of deformation. Due to the unfavourable preconditions for classical computed tomography as of large aspect ratio, the samples were investigated by coplanar translational laminography. Its limited range of observation angles of ± 45°, results in anisotropic artefacts about the normal to the sample surface, but the typical flaws are well visualized in the as-prepared state, in a state of early damage, and in the repaired state.
Modern wind turbine rotor blades consist of sandwich shell segments made from glass fiber reinforced polymers. During manufacturing, defects can arise which could lead to failure of the whole component under dynamic mechanical and thermal loads. Hence during operation defects can arise which, if detected, can be repaired locally and in-situ by applying repair patches instead of taking the whole rotor blade down and repair it remotely. This method is much more time and cost effective, since the shut-down time of the energy converter is limited to a minimum. These repair patches can, however, also lead to new defects if not applied optimally. Therefore, it is necessary to control the quality of the repair patches to ensure the best possible restoration of structural integrity of the component. As a rotor blade is an object with a large aspect ratio, X-ray laminography is predestined to provide 3D information of the objective volume. To enhance the amount of information gained from laminographic reconstruction, we use in this study a photon counting and energy discriminating X-ray detector and apply a material decomposition algorithm to the data. By inherently separating the incident spectra within the detection process into two distinct energy bins, the basis material decomposition can provide material resolved images. Choosing glass and epoxy resin as basis materials and numerically solving the inverse dual-energy equation system, the reconstructed laminographic datasets contain highly valuable information about the distribution of the basis materials within the structure. Furthermore, cross- artifacts arising from the limited angle of the projection data can be reduced by this method which allows to investigate structures that were hidden underneath the artefacts.
HEAs represent a relatively new class of materials. The the alloy concept is fundamentally different from the most conventional materials and alloys that are used today. Recently, the focus of HEA designs is more application-based. For that purpose, the elements of interest are carefully selected and multiple phases as well as micro-structures are deliberately adjusted. Currently, only limited attention has been paid to weldability of HEA. This encompasses possible effects on metallurgy and its influence on the desired properties. It remains open if welding causes e.g. considerable number of intermetallic phases or segregations and their effect on weld joint properties. For that reason, the scope of this study is to summarize already available studies on welding of HEAs with respect to the HEA-type, the applied welding process and its influence on the weld joint properties.
Virtual-lab-based determination of a macroscopic yield function for additively manufactured parts
(2019)
This work aims for an yield function description of additively manufactured (AM) parts of S316L steel at the continuum-mechanical macro-scale by means of so-called virtual experiments using a crystal plasticity (CP) model at meso-scale. Additively manufactured parts require the consideration of the specific process-related microstructure, which prevents this material to be macroscopically treated as isotropic, because of crystallographic as well as topological textures.
EBSD/CT-Scans from in-house additively manufactured specimen extract the unique microstructural topology which is converted to a representative volume element (RVE) with grain structure and crystal orientations.
Crystal plasticity model parameters on this RVE are calibrated and validated by means of mechanical testing under different texture angles. From virtual experiments on this RVE, yield loci under various loading conditions are simulated. The scale bridging from meso- to macro-scale is realised by the identification of the simulated yield loci as a modified anisotropic Barlat-type yield model representation.
Virtual-lab-based determination of a macroscopic yield function for additively manufactured parts
(2018)
This work presents a method for the yield function determination of additively manufactured parts of S316L steel. A crystal plasticity model is calibrated with test results and used afterwards to perform so-called virtual experiments, that account for the specific process-related microstructure including crystallographic and morphological textures. These simulations are undertaken on a representative volume element (RVE), that is generated from EBSD/CT-Scans on in-house additively manufactured specimen, considering grain structure and crystal orientations. The results of the virtual experiments are used to determine an anisotropic Barlat yield function, that can be used in a macroscopical continuum-sense afterwards. This scale-bridging approach enables the calculation of large-scale parts, that would be numerically too expensive to be simulated by a crystal plasticity model.
Der Vortrag gibt eine Einführung in die Methode der Vakuumheißextraktion und beschreibt die Anwendungsmöglichkeiten der an der BAMN betriebenen Anlage.
Although the slow crack growth in glass is dominated by stress-corrosion phenomena, it also should reflect the underlaying intrinsic fracture behavior controlled by glass chemistry and structure. To investigate such underlaying phenomena, crack growth velocity in alkali silicate glasses was measured in vacuum across 10 orders of magnitude with double cantilever beam technique. Measured and literature crack growth data were compared with calculated intrinsic fracture toughness data obtained from Young’s moduli and theoretical fracture surface energy. Data analysis reveals slight correlation with the packing density and significant deviations from the intrinsic brittle fracture behavior. These deviations do not follow simple compositional trends. Two opposing processes may explain this finding: a decrease in the apparent fracture surface energy due to stress-induced chemical changes at the crack tip and its increase due to energy dissipation during fracture.
The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience. In the IGF project "iFrakto", software is being developed that quantitatively determines fracture characteristics and fracture mechanisms utilizing digitized expert knowledge, machine learning, and standard 2D and topographical data from SEM imaging. Topographical data are obtained from 4QBSE detector using shape-from-shading technology. In the medium term, a software tool should provide knowledge-based suggestions for the evaluation of fracture surfaces in real time during SEM work or at subsequent evaluation. As a basis for this, round robins were carried out among fractographers in order to create a knowledge base, to query the practice-relevant requirements for such tools and to carry out first practical tests. Actual results are presented and the relevance of the evaluation strategy is evaluated.
Manipulating ceramic powder compacts and ceramic suspensions (slurries) within their volume with light requires a minimum transparency of the materials. Compared to polymers and metals, ceramic materials are unique as they offer a wide electronic band gap and thus a wide optical window of transparency. The optical window typically ranges from below 0.3 µm up to 5µm wavelength. Hence, to penetrate with laser light into the volume of a ceramic powder compound its light scattering properties need to be investigated and tailored. In the present study we introduce the physical background and material development strategies to apply two-photon-polymerization (2PP) for the additive manufacture of filigree structures within the volume of ceramic slurries.
Manipulating ceramic powder compacts and ceramic suspensions (slurries) within their volume with light requires a minimum transparency of the materials. Compared to polymers and metals, ceramic materials are unique as they offer a wide electronic band gap and thus a wide optical window of transparency. The optical window typically ranges from below 0.3 µm up to 5µm wavelength. Hence, to penetrate with laser light into the volume of a ceramic powder compound its light scattering properties need to be investigated and tailored. In the present study we introduce the physical background and material development strategies to apply two-photon-polymerization (2PP) for the additive manufacture of filigree structures within the volume of ceramic slurries.
The discovery of the high entropy concept at the beginning of the 3rd millennium lead to a worldwide increase in metallurgical research, as the possible element combinations seemed nearly endless and the range of applications wide. In the early years of research, one of the main goals was the discovery of a single-phase high entropy alloy. As research evolved, it was found that properties could be enhanced by opening the HE-concept towards multiphase alloys, and from the wide area of possibilities our group chose a tuning of the properties towards high temperature application.
Compositionally complex Al10Co25Cr8Fe15Ni36Ti6 alloy, which is single-phase at high temperature, around 1200°C, shows a three phase morphology at intermediate temperatures, around 800°C. A high temperature homogenization procedure has to be applied in order to decrease the segregation induced by the dendritic growth. Subsequent annealing promotes the formation of the strengthening γ' precipitates. The alloy shows a positive lattice misfit between the γ and the γ' phase, which can be an indicator for good creep properties.
The microstructure can be optimized by adding trace elements such as Mo and Hf, known as γ and γ' strengtheners in Ni-based superalloys, respectively. Atom probe measurements show that Mo segregates into the γ matrix, and Hf prefers the γ' precipitates, where it increases the lattice parameter and thus also the lattice misfit, by about 50%. The alloy family shows interesting mechanical properties, especially the Al9.5Co25Cr8Fe15Ni36Ti6Hf0,5 alloy – its tensile properties are better than those of commercial Alloy 800H and IN617 at temperatures up to 700°C.
Highly unrelaxed structural states of metallic glasses have often advantageous mechanical properties. Since metallic glasses continuously relax with time (age) or inherently are well relaxed after processing, methods to uniformly rejuvenate the material are needed. One approach that has received attention is the so-called cryogenic-cycling method, during which a metallic glass is repeatedly immersed into liquid nitrogen. In some cases, cryogenic cycling is truly efficient in increasing the stored excess enthalpy of metallic glasses, but it does not seem to be universally applicable to all alloys and structural states. The origins for these differences remain unclear due to our limited understanding of the underlying structural evolution. In order to shed more light onto the fundamental structural processes of cryogenic cycling, we pursue in-situ x-ray photon correlation spectroscopy (XPCS) to trace the atomic-scale structural dynamics of a Zr-based metallic glass in two different structural states (ribbon and bulk metallic glass). This method allows calculating the relaxation times as a function of time throughout the thermal cycling. It is found that the investigated glasses exhibit heterogeneous structural dynamics at 300 K, which changes to monotonic aging at 78 K. Cryogenic cycling homogenizes the relaxation time distribution for both structural states. This effect is much more pronounced in the ribbon, which is the only structural state that rejuvenates upon cycling. We furthermore reveal how fast atomic-scale dynamics is correlated with long-time average structural relaxation times irrespective of the state, and that the ribbon exhibits unexpected additional fast atomic-scale relaxation in comparison to the plate material. Overall, a picture emerges that points towards heterogeneities in fictive temperature as a requirement for cryogenic energy storage.
Towards Interoperability: Digital Representation of a Material Specific Characterization Method
(2022)
Certain metallic materials gain better mechanical properties through controlled heat treatments. For example, in age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which represent obstacles to dislocation movement. Precise tuning of the material structure is critical for optimal mechanical behavior in the application. Therefore, analysis of the microstructure and especially the precipitates is essential to determine the ideal parameters for the interplay of material and heat treatment. Transmission electron microscopy (TEM) is utilized to identify precipitate types and orientations in a first step. Dark-field imaging (DF-TEM) is often used to image the precipitates and to quantify their relevant dimensions.
The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, an automatable, digital approach is demonstrated. Based on DF-TEM images of different precipitation states of a wrought aluminum alloy, a modularizable digital workflow for quantitative precipitation analysis is presented. The integration of this workflow into a data pipeline concept will also be discussed. Thus, by using ontologies, the raw image data, their respective contextual information, and the resulting output data from the quantitative precipitation analysis can be linked in a triplestore. Publishing the digital workflow and the ontologies will ensure the reproducibility of the data. In addition, the semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability.
The presented work is part of two digitization initiatives, the Platform MaterialDigital (PMD, materialdigital.de) and Materials-open-Laboratory (Mat-o-Lab).
Towards interoperability: Digital representation of a material specific characterization method
(2023)
Certain metallic materials gain better mechanical properties through controlled heat treatments. In age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which hinder dislocation movement. Analysis of the microstructure and especially the precipitates by transmission electron microscopy allows identification of precipitate types and orientations. Dark-field imaging is often used to image the precipitates and quantify their relevant dimensions.
The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, a digital approach is demonstrated. The integration of an exemplary digital workflow for quantitative precipitation analysis into a data pipeline concept is presented. Here ontologies enable linking of contextual information to the resulting output data in a triplestore. Publishing digital workflow and ontologies ensures the reproducibility of the data. The semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability.
Due to the diversity of materials and the processes associated with their production and use, the complexity of the lifecycles of materials and the multitude of academic and industrial researchers participating in generation of data for material design impose a huge challenge. The topical goal of digitalizing materials and processes can only be adequately addressed by consolidating the efforts of all stakeholders in this field. There are many scattered activities, but there is a demand for an elimination of redundancies as well as an advance in acceptance and a common basis in the digitalization of materials. Furthermore, data analysis methods play an important role in both, the experimental and simulation-based digital description of materials, but they have been poorly structured so far.
Therefore, the two joint projects Platform Material Digital (PMD, materialdigital.de) and Materials open Laboratory (Mat-o-Lab, matolab.de) aim to contribute to a standardized description of data processing methods in materials research. Besides stimulating the formation of a collaborative community in this respect, their main technical goals are the quality assurance of the processes and the output data, the acquisition and definition of their accuracy as well as the interoperability between applications. In this regard, data management in accordance with the FAIR (findability, accessibility, interoperability, reuseability) principles is addressed. There is a common agreement in the scientific community following current discussions that data is supposed to be conform to these principles. This includes storage, processing and querying of data in a preferably standardized form.
To meet the challenge to contextualize material data in a way that is consistent with all stakeholders, all necessary information on the condition of the material including production and application-related changes have to be made available via a uniform, machine-readable description. For this purpose, ontologies are to be used since they allow for machine-understandable knowledge representations and conceptualizations that are needed for data management and the digitalization in the field of materials science.
As first efforts in PMD and Mat-o-Lab, application ontologies are created to explicitly describe processes and test methods. Thereby, the well-known tensile test of metals at room temperature was described ontologically in accordance with the respective ISO standard 6892-1:2019-11.
The efforts in creating this tensile test application ontology are shown in this presentation. Especially, the path of ontology development based on standards to be pursued is focused, which is in accordance with the generic recommendations for ontology development and which is supposed to be exemplary for the creation of other application ontologies.
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 evelopment 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 eachindividual 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.