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This study aims to represent an approach for transferring the materials testing datasets to the digital schema that meets the prerequisites of the semantic web. As a use case, the tensile stress relaxation testing method was evaluated and the testing datasets for several copper alloys were prepared. The tensile stress relaxation testing ontology (TSRTO) was modeled following the test standard requirements and by utilizing the appropriate upper-level ontologies. Eventually, mapping the testing datasets into the knowledge graph and converting the data-mapped graphs to the machine-readable Resource Description Framework (RDF) schema led to the preparation of the digital version of testing data which can be efficiently queried on the web.
The heat-resistant cast iron EN-GJSA-XNiSiCr35-5-2 (Ni-Resist D-5S) was investigated for its fatigue crack growth behavior at room and high temperatures. Force-controlled tests were carried out at constant temperatures (20 °C, 500 °C, 700 °C) without and with hold time and different load ratios. The crack growth behavior was also characterized under TMF loading (Tmin = 400 °C, Tmax = 700 °C) by applying IP and OP conditions and different load ratios. Three different techniques were combined to monitor crack growth: potential drop, thermography, and compliance method. The effect of the different loading conditions on the fatigue crack growth behavior will be presented and discussed.
In this presentation, the results of the determination of the diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 are presented. The analysis is based on high-energy synchrotron diffraction experiments performed at the Deutsches Elektronen-Synchrotron. It is shown that the characteristic microstructure of laser powder bed fused Inconel 718 impacts the elastic anisotropy and therefore the diffraction and single-crystal elastic constants. Finally, the consequences on the diffraction-based residual stress determination of laser powder bed fused Inconel 718 are discussed.
Gas turbine components, made of nickel-based alloys, undergo material damage due to high temperatures and mechanical stresses. These components need periodic replacement to avoid efficiency loss and failure. Repair of these parts is more cost-effective than replacement. State-of-the-art repair technologies, including different additive manufacturing (AM) and brazing processes, are considered for efficient restoration. Materials properties mismatches and/or internal defects in repaired parts may expedite crack initiation and propagation, reducing fatigue life. To understand the crack growth behavior in joining zones and predict the remaining life of repaired components, fatigue crack growth (FCG) tests were conducted on specimens of nickel-based alloys joined via brazing, pre-sintered preforms and AM. The FCG experimental technique was successfully adapted for joined specimens and results indicate that the investigated braze material provides a lower resistance to crack growth. In AM-sandwich specimens, the crack growth rates are significantly reduced at the interface of AM and cast material.
This contribution presents the results of an experimental study on the LCF behavior of an austenitic 316L stainless steel produced by laser powder bed fusion featuring a low defect population, which allows for an improved understanding of the role of other typical aspects of a PBF‑LB microstructure. The LCF tests were performed between room temperature and 600 °C. A hot‑rolled 316L variant was tested as a reference. The mechanical response is characterized by strain-life curves, a Coffin‑Manson‑Basquin fitting, and cyclic deformation curves. The damage and deformation mechanisms are studied with X-ray computed tomography, optical and electron microscopy. The PBF‑LB/M/316L exhibits lower fatigue lives at lower strain amplitudes. The crack propagation is mainly transgranular. The solidification cellular structure seems to be the most relevant underlying microstructural feature determining the cyclic deformation behavior.
Following the new paradigm of materials development, design, and optimization, digitalization is the main goal in materials sciences and engineering (MSE) which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web technologies (SWT) are used since they allow for machine-actionable and human-readable knowledge representations needed for data management, retrieval, and (re)use.
The project ‘platform MaterialDigital’ (PMD, https://materialdigital.de) aims to bring together and support interested parties from both industrial and academic sectors in a sustainable manner in solving digitalization tasks and implementing digital solutions. Therefore, the establishment of a virtual material data space and the systematization of the handling of hierarchical, process-dependent material data are focused. Core points to be dealt with are the development of agreements on data structures and interfaces implemented in distinct software tools and to offer users specific support in their projects. Furthermore, the platform contributes to a standardized description of data processing methods in materials research. In this respect, selected MSE methods are semantically represented which are supposed to serve as best practice examples with respect to knowledge representation and the creation of knowledge graphs used for material data.
Accordingly, this presentation shows the efforts taken within the PMD project towards the digitalization in MSE such as the development of the mid-level PMD core ontology (PMDco, https://github.com/materialdigital/core-ontology). Furthermore, selected results of a PMD partner project use case addressing data and knowledge management from synthesis, production, and characterization of materials are shown.
Das hochaktuelle Thema der Integration und Wiederverwendung von Wissen und Daten aus Herstellung, Bearbeitung und Charakterisierung von Materialien wird im Zuge der digitalen Transformation in der Materialwissenschaft und Werkstofftechnologie in verschiedenen Projekten adressiert. Dabei stehen die Interoperabilität von nach FAIR-Prinzipien erstellten und veröffentlichten Daten und Anwendungen im Vordergrund. Zur Umsetzung eines komplexen Datenmanagements sowie der Digitalisierung im Bereich der Materialwissenschaften etablieren sich Ontologien zunehmend als belastbares Werkzeug. Sie ermöglichen sowohl menschenlesbare als auch maschinenverständliche und -interpretierbare Wissensrepräsentationen durch semantische Konzeptualisierungen.
Im Rahmen des Projektes Plattform MaterialDigital (PMD, materialdigital.de) werden Ontologien verschiedener Ebenen entwickelt (verbindende mid-level sowie Domänen-Ontologien). Die PMD-Kernontologie (PMD Core Ontology - PMDco) ist eine Ontologie der mittleren Ebene), die Verbindungen zwischen spezifischeren MSE-Anwendungsontologien und domänenneutralen Konzepten herstellt, die in bereits etablierten Ontologien höherer Ebenen (top-level Ontology) verwendet werden. Sie stellt somit einen umfassenden Satz von durch Konsensbildung in der Gemeinschaft (geteiltes Vokabular) entstanden Bausteinen grundlegender Konzepte aus der Materialwissenschaft und Werkstofftechnik (MSE) dar. Das primäre Ziel des PMDco-Designs ist es, die Interoperabilität zwischen verschiedenen MSE-bezogenen und anderen Ontologien zu ermöglichen. Die PMDco dient als umfassend ausgelegte und erweiterbare semantische Zwischenschicht, die gemeinsame MSE-Konzepte durch semantisches Mapping auf andere Darstellungen vereinheitlicht, was sie zu einem effizienten Werkzeug zur Strukturierung von MSE-Wissen macht. In dieser Präsentation wird die Version 2.0 der PMDco vorgestellt.
Weiterhin wird eine auf die PMDco bezogene normenkonforme ontologische Repräsentation zur Speicherung und Weiterverarbeitung von Zugversuchsdaten präsentiert, die in enger Zusammenarbeit mit Standardisierungsgremien erstellt wurde. Dies umfasst den Weg von der Entwicklung einer Ontologie nach Norm, der Konvertierung von Daten aus Standardtests in das interoperable RDF-Format bis hin zur Verbindung von Ontologie und Daten. Letztendlich können die entsprechenden Daten in einem Triple Store abgelegt und abgefragt werden. Auf Basis dieser Zugversuchsontologie wurde im Folgenden unter Verwendung eines elektronischen Laborbuches (electonic lab notebook – ELN) zur Datenaufnahme eine Praktikumsreihe von Universitätsstudierenden digitalisiert. Dadurch wurde eine vollständig digital integrierte Versuchsführung ermöglicht, die auf andere Versuchsreihen und Experimente übertragbar ist und ebenfalls vorgestellt werden soll. Neben einer erleichterten Aufnahme, Analyse und (Wieder-)Verwendbarkeit von Daten wird damit eine Sensibilisierung von Studierenden für Datenstrukturierung sowie semantische Technologien im Sinne der Aus- und Weiterbildung erreicht.
The high operating temperatures of radial compressor wheels in exhaust gas turbochargers lead to abchange in the original microstructure of the heat-resistant aluminum alloy EN AW-2618A (overaging). This is caused by thermal loads that are close to the age hardening temperature and can even exceed it for a short time. The aging mechanisms have been investigated together with low cycle fatigue (LCF), thermomechanical fatigue (TMF) and creep up to max. 190 °C in previous research projects. The behavior of the alloy under high cycle fatigue (HCF) and the influence of load spectra have hardly been investigated. Since the operating temperatures of centrifugal compressors are expected to increase in the future, this research project investigated the HCF behavior at 230 °C, a test temperature significantly higher than the age hardening temperature. The objectives of the project were to establish a suitable experimental database, to understand the relevant microstructural processes, and to further develop and adapt suitable models and evaluation methods. In addition to a basic characterization of the HCF behavior in the initial condition T61, the experimental investigation program included targeted mechanical tests to isolate the influencing factors of mean stress (𝑅 = −1, 𝑅 = 0.1), material overaging (T61, 10 h/230 °C, 1000 h/230 °C), test temperature (20 °C, 230 °C), test frequency (0.2 Hz, 20 Hz) as well as variable amplitudes. On this basis, the models and evaluation methods developed in the previous projects were adapted and further developed to reflect thermal and mechanical loads in the lifetime assessment.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
This presentation provides a comprehensive overview of recent developments and the current status within the Semantic Interoperability work area, with a particular emphasis on the advancements related to the Platform MaterialDigital Core Ontology (PMDco). The presentation will delve into the collaborative and community-supported curation process that has been instrumental in shaping PMDco. Additionally, we will introduce the innovative Ontology Playground, showcasing its role in fostering experimentation and exploration within the realm of ontology development.
Results of an extended TMF test program on grade P92 steel in the temperature range of 620 ◦C–300 ◦C, comprising in-phase (IP) and out-of-phase (OP) tests, partly performed with symmetric dwells at Tmax/Tmin, are presented. In contrast to previous studies, the low-strain regime is also illuminated, which approaches flexible operation in a power plant with start/stop cycles. At all strain amplitudes, the material performance is characterized by continuous cyclic softening, which is retarded in tests at lower strains but reaches similar magnitudes in the course of testing. In the investigated temperature range, the phase angle does not affect fatigue life in continuous experiments, whereas the IP condition is more detrimental in tests with dwells. Fractographic analyses indicate creep-dominated and fatigue-dominated damage for IP and OP, respectively. Analyses of the (micro)hardness distribution in the tested specimens suggest an enhanced microstructural softening in tests with dwell times for the low- but not for the high-strain regime. To rationalize the obtained fatigue data, the fracturemechanics-based DTMF concept, which was developed for TMF life assessment of ductile alloys, was applied. It is found that the DTMF parameter correlates well with the measured fatigue lives, suggesting that subcritical growth of cracks (with sizes from a few microns to a few millimeters) governs failure in the investigated range of strain amplitudes.
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.
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.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
In this presentation, an approach how to maintain a comprehensive and intuitive MSE-centric terminology composing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures is shown.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
This research deals with the development of the Vickers hardness knowledge graph, mapping the example dataset in them, and exporting the data-mapped knowledge graph as a machine-readable Resource Description Framework (RDF). Modeling the knowledge graph according to the standardized test procedure and using the appropriate upper-level ontologies were taken into consideration to develop the highly standardized, incorporable, and industrial applicable models. Furthermore, the Ontopanel approach was utilized for mapping the real experimental data in the developed knowledge graphs and the resulting RDF files were successfully evaluated through the SPARQL queries.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
In dieser Präsentation werden die letzten Entwicklungen in der Plattform MaterialDigital (PMD) im DIN Normenausschuss 062-01-42 AA zur Zug- und Duktilitätsprüfung für Metalle vorgestellt. Dabei werden hauptsächlich die Entwicklungen und Neustrukturierung der PMD Core Ontology (PMDco) sowie die entsprechende Anpassung der Zugversuchsontologie (Tensile Test Ontology - TTO) inklusive des Datenmappings adressiert. Für das Datenmapping wurde ein speziell im Zusammenhang mit der PMD erstellter Zugversuchsdatensatz verwendet, welcher frei verfügbar in einem online Zenodo Repository veröffentlicht ist. Weiterhin wird die Weiterentwicklung der Norm in Verbindung mit ihrer folgenden Revision hinsichtlich der Integration von Aspekten zur Digitalisierung in der Materialwissenschaft und Werkstofftechnik sowie der Verwendung von semantischen Technologien, wie unter anderem ontologischen Repräsentationen von Materialien und Prozessen, diskutiert.