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The digitalization of materials science and engineering (MSE) is currently leading to remarkable advancements in materials research, design, and optimization, fueled by computer‐driven simulations, artificial intelligence, and machine learning. While these developments promise to accelerate materials innovation, challenges in quality assurance, data interoperability, and data management have to be addressed. In response, the adoption of semantic web technologies has emerged as a powerful solution in MSE. Ontologies provide structured and machine‐actionable knowledge representations that enable data integration, harmonization, and improved research collaboration. This study focuses on the tensile test ontology (TTO), which semantically represents the mechanical tensile test method and is developed within the project Plattform MaterialDigital (PMD) in connection with the PMD Core Ontology. Based on ISO 6892‐1, the test standard‐compliant TTO offers a structured vocabulary for tensile test data, ensuring data interoperability, transparency, and reproducibility. By categorizing measurement data and metadata, it facilitates comprehensive data analysis, interpretation, and systematic search in databases. The path from developing an ontology in accordance with an associated test standard, converting selected tensile test data into the interoperable resource description framework format, up to connecting the ontology and data is presented. Such a semantic connection using a data mapping procedure leads to an enhanced ability of querying. The TTO provides a valuable resource for materials researchers and engineers, promoting data and metadata standardization and sharing. Its usage ensures the generation of finable, accessible, interoperable, and reusable data while maintaining both human and machine actionability.
KupferDigital mechanical testing datasets: Stress relaxation and low-cycle fatigue (LCF) tests
(2024)
The KupferDigital project deals with the development of a data ecosystem for digital materials research on the basis of ontology-based digital representations of copper and copper alloys. This document provides exemplary mechanical testing datasets for training the developed KupferDigital infrastructures. Different types of cast copper alloys were provided for this research and their mechanical testing (stress relaxation and low-cycle fatigue) was performed in the accredited materials testing laboratory, while the test results were reported according to the DIN/ISO standards and attached with the maximum possible metadata about the sample history, equipment, and calibration. The attached content file consisted of the obtained primary raw testing data as well as the secondary datasets of these tests containing the detailed metadata of mechanical testing methods. Such test data files are processed by the KupferDigital digital tools to be converted to standardized machine-readable data files.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
The high operating temperatures of radial compressor wheels in exhaust gas turbochargers lead to a change 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 be-havior 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.
Iron aluminides, already reported in the late 19th century, did not cease to attract the interest of scientists and engineers ever since. Besides good oxidation resistance, low density and resource availability, potentials for hightemperature strengths that compete with high-alloy steels were unlocked by low alloy contents. Still, research on alloy design continues, as alloying usually comes at the price of brittleness in low-temperature regimes. A potential candidate is the quinary Fe–Al–Mo–Ti–B system which is strengthened by solid solution and eutectic borides. It was shown to have good strength and outstanding creep resistance under compressive loading up to elevated temperatures. Although the individual effect of alloy additions is well understood in iron aluminides, little is known about the combined effects of alloying concentrations on microstructure, phase stability and mechanical properties. Therefore a systematic study of two Ti-doped near-Fe3Al alloys with varying contents of Mo (2–4 at.%) and B (0.5–1 at.%) was conducted. In total eight different alloys were fabricated by investment casting into ceramic shell molds. Alloys were characterized and compared by grain size, phase transitions, microstructure evolution as well as elemental compositions and volume fractions of phases. For mechanical characterization, macrohardness and microhardness tests as well as tensile tests at ambient and high tempera tures were conducted. Independent of alloy additions, alloys with 24–25 at.% Al exhibit superior proof strength due to a higher matrix hardness. Decreasing B content generally decreases strength by lower secondary phase fractions which contribute via particle hardening. Reducing Mo content decreases both the solute concentration in the matrix and secondary phase fractions. Surprisingly, strength is similar or even superior to alloys with higher Mo content. Strength relations are discussed with a focus on solid-solution hardening theory and other competing strengthening mechanisms.
Fatigue tests were performed on the forged aluminum alloy EN AW-2618A in the T61 state. Different stress ratios (R = -1, R = 0.1) were selected to study the influence of mean stress on fatigue life. Two overaged states (10 h/230 ◦C, 1000 h/230 ◦C) were also tested to investigate the influence of overaging on fatigue life. Transmission electron microscopy (TEM) was used to characterize the precipitates (S-phase), which are mainly responsible for the strength of the alloy. A fractographic analysis was also performed to determine the failure mode. Overaging reduces the fatigue life compared to the T61 state. The longer the aging time, the lower the fatigue resistance. The reason is the decrease in (yield) strength, which correlates with the radius of the S-phase: the precipitate radius increases by a factor of approximately two for the overaged states compared to the initial state. The analysis of the fracture surfaces showed crack initiation occurs predominantly on the outer surface and is
associated with the primary phases.
Mechanical testing ontology
(2023)
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.
To accelerate the growth of Industry 4.0 technologies, the digitalization of mechanical testing laboratories as one of the main data-driven units of materials processing industries is introduced in this paper. The digital lab infrastructure consists of highly detailed and standard-compliant materials testing knowledge graphs for a wide range of mechanical testing processes, as well as some tools that enable the efficient ontology development and conversion of heterogeneous materials’ mechanical testing data to the machine-readable data of uniform and standardized structures. As a basis for designing such a digital lab, the mechanical testing ontology (MTO) was developed based on the ISO 23718 and ISO/IEC 21838-2 standards for the semantic representation of the mechanical testing experiments, quantities, artifacts, and report data. The trial digitalization of materials mechanical testing lab was successfully performed by utilizing the developed tools and knowledge graph of processes for converting the various experimental test data of heterogeneous structures, languages, and formats to standardized Resource Description Framework (RDF) data formats. The concepts of data storage and data sharing in data spaces were also introduced and SPARQL queries were utilized to evaluate how the introduced approach can result in the data retrieval and response to the competency questions. The proposed digital materials mechanical testing lab approach allows the industries to access lots of trustworthy and traceable mechanical testing data of other academic and industrial organizations, and subsequently organize various data-driven research for their faster and cheaper product development leading to a higher performance of products in engineering and ecological aspects.
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.