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Organisationseinheit der BAM
- 5.2 Metallische Hochtemperaturwerkstoffe (199) (entfernen)
Paper des Monats
- ja (1)
Abstract While classically used to visualise the magnetic microstructure of functional materials (e.g., for magnetic applications), in this study, the Bitter technique was applied for the first time to visualise macroscopic deformation gradients in a polycrystalline low-carbon steel. Spherical indentation was chosen to produce a multiaxial elastic–plastic deformation state. After removing the residual imprint, the Bitter technique was applied, and macroscopic contrast differences were captured in optical microscopy. To verify this novel characterisation technique, characteristic “hemispherical” deformation zones evolving during indentation were identified using an analytical model from the field of contact mechanics. In addition, near-surface residual stresses were determined experimentally using synchrotron radiation diffraction. It is established that the magnetic domain distribution contrast provides deformation-related information: regions of different domain wall densities correspond to different “hemispherical” deformation zones (i.e., to hydrostatic core, plastic zone and elastic zone, respectively). Moreover, the transitions between these three zones correlate with characteristic features of the residual stress profiles (sign changes in the radial and local extrema in the hoop stress). These results indicate the potential of magnetic domain distribution imaging: visualising macroscopic deformation gradients in fine-grained ferromagnetic material with a significantly improved spatial resolution as compared to integral, mean value-based measurement methods.
Virtual-lab-based determination of a macroscopic yield function for additively manufactured parts
(2019)
This work aims for a yield function description of additively manufactured 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. From virtual experiments, 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
(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.
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.
The manufacturability of metallic alloys using laser-based additive manufacturing methods such as laser powder bed fusion has substantially improved within the last decade. However, local melting and solidification cause hierarchically structured and crystallographically textured microstructures possessing large residual stress. Such microstructures are not only the origin of mechanical anisotropy but also pose metrological challenges for the diffraction-based residual stress determination. Here we demonstrate the influence of the build orientation and the texture on the microstructure and consequently the mechanical anisotropy of as-built Inconel 718. For this purpose, we manufactured specimens with [001]/[011]-, [001]- and [011]/[111]-type textures along their loading direction. In addition to changes in the Young’s moduli, the differences in the crystallographic textures result in variations of the yield and ultimate tensile strengths. With this in mind, we studied the anisotropy on the micromechanical scale by subjecting the specimens to tensile loads along the different texture directions during in situ neutron diffraction experiments. In this context, the response of multiple lattice planes up to a tensile strain of 10% displayed differences in the load partitioning and the residual strain accumulation for the specimen with [011]/[111]-type texture. However, the relative behavior of the specimens possessing an [001]/[011]- and [001]-type texture remained qualitatively similar. The consequences on the metrology of residual stress determination methods are discussed.
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.
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.