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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.
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.
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.
The KupferDigital project aims to develop digital methods, tools, and data space infrastructures for digitalizing the entire life cycle of copper materials. The mechanical testing process is one of the main chains of such life cycles which generates lots of important testing data about the mechanical properties of the materials and their related materials and testing metadata. To train the digitalization of the mechanical testing process, different kinds of copper alloys were provided for this project, and their mechanical properties were measured by typical methods like Brinell and Vickers hardness and tensile testing. The primary raw testing data as well as the secondary datasets of these tests are provided. The detailed materials specifications, the utilized mechanical testing methods, and provided datasets are described in the content file. The test data files of heterogeneous structures are processed by the KupferDigital digital tools to be converted to standardized machine-readable data files.
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.
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.
Performing mechanical tests at high temperatures is a nontrivial issue: Compared to room temperature testing, additional phenomena like time-dependent Deformation processes and oxidation effects raise the complexity of the material’s response, while more sophisticated test setups and additional control parameters increase the number of potential sources of error. To a large extent, these complications can be overcome by carefully following all recommendations given in the respective high temperature testing standards, but more comprehensive background information helps to identify points of specific importance in particular test campaigns. In this chapter, an overview is given on general high temperature testing issues like the appropriate choice of experimental equipment and key aspects of temperature measurement. In subsequent sections, the major static and dynamic high temperature test methods are reviewed and their Special features, as compared to testing at room temperature, are highlighted based on example data sets. Influences of specimen size and environmental effects are shortly outlined in a concluding section. In the whole chapter, a focus is set on testing of “classical” metallic high temperature materials, but many considerations are equally valid for testing of intermetallics, composites, and high temperature ceramics.
A study was made on the effect of creep loading on the precipitate radii evolution of the aluminum alloy 2618A.
The overageing process of the alloy was investigated under load at a temperature of 190 °C with stresses between 79 and 181 MPa and compared to stress free isothermal ageing. The precipitates responsible for strength were characterized using dark-field transmission electron microscopy (DFTEM). This allows the experimental Determination of radii distributions of the rod-shaped Al2CuMg precipitates and the evaluation regarding their mean precipitate radius. It was found that the mean precipitate radius enables the comparison of the different microstructural conditions of crept and uncrept samples. The mean precipitate radii of the samples experiencing creep are significantly higher than those of undeformed samples. It was shown that the acquired radii distributions are viable to determine averaged particle radii for comparison of the aged samples. A ripening process including pipe diffusion along dislocations describes the data on coarsening very well for the creep samples.
In Germany spent nuclear fuel and high level radioactive waste is stored in interim storage containers with double lid systems. Those lids are equipped with metal seals (e.g. Helicoflex®) that ensure the safe enclosure of the inventory. The used metal seals consist of three components as can be seen in the cross-sectional view in Figure 1. The innermost part is a helical spring that is surrounded by an inner jacket made of stainless steel. The outer jacket that is made of a softer material which in case of assembly in the aforementioned storage containers is silver or aluminum (i.e. Al 99.5). During application the seal is compressed and due to the restoring force of the helical spring, the outer jacket is plastically deformed and adapts to the sealing surface. Hence, leakage paths are closed and the sealing function is generated. In Germany the above-mentioned containers are licensed for up to 40 years of interim storage, which in case extended storage becomes necessary before a final repository is available will have to be extended to even longer periods. Therefore, the evaluation of the long-term behavior of the seals is necessary, taking into account storage conditions, decay heat and possible mechanical loads as well.
At Bundesanstalt für Materialforschung und –prüfung (BAM) long-term investigations are being conducted in which seals are assembled in test flanges and aged at temperatures ranging from room temperature to 150°C for accelerated aging. The aged seals are tested semi-annually (after the first 6 months in which the seals are tested more frequently) regarding the sealing performance, the remaining seal force, and the useable resilience upon decompression. Results of these investigations have been published over the past years (e.g. Grelle, Wolff, Probst, Jaunich, & Völzke, 2017; Völzke, Wolff, Probst, Nagelschmidt, & Schulz, 2014). It was found that the seal force and the useable resilience decrease with time and temperature, which is in agreement with the result of other studies (Sassoulas et al., 2006; Wataru et al., 2016) as well. Geometry change of the outer jacket has been identified as the main reason for this seal behavior. At the prevailing operating temperatures and stresses the aluminum is subjected to creep deformation leading to a thinning of the outer jacket. Since the seal groove depth remains unchanged the helical spring expands, which in turn leads to a decrease of the generated spring and seal force.
Although the main reason for the change of seal parameters over time and temperature is known, a detailed characterization of the seal behavior and a reliable prediction of the parameter development for aging times that exceed the experimental time frame have not been possible, yet.
For deeper understanding of the aging processes, an Investigation program, which is covered in this contribution, is conducted at Bundesanstalt für Materialforschung und –prüfung (BAM) that focusses on the behavior of the aluminum jacket and its influence on the long-term sealing performance. The program investigates properties of material samples as well as the behavior of the seal as a component.
Original sheet material of the same aluminum that is used for manufacturing of the seals is investigated in compression creep tests. For this, a DMA (dynamic mechanical analysis) machine is employed (here used for static tests) that allows for a measurement of the specimens deformation under forces of up to 500 N. The advantage of this method is that the original material can be tested in the same shape as used for the seals which is 0.5 mm thick sheet material. For investigation of tensile creep standard specimens are used, that were machined from surrogate material of the same composition and annealing condition.
Furthermore, aluminum seals that are cut into smaller segments are assembled in flanges and placed in heating chambers at temperatures ranging from 23°C to 150°C. After different periods of time from 3 days to 300 days the segments are taken out of the flanges and are investigated, thus giving information on different states of aging. Measurements of the development of the seal contact width and the aluminum jacket thickness are done with an optical microscope. Further investigations on the segments will include metallography and hardness measurements.
From the detailed material and component behavior including the results of the long-term seal force and useable resilience investigations a better understanding of the overall seal behavior can be gained. The aim is to contribute to the development of material models and analytical approaches for the prediction of the sealing behavior in dependence of time and temperature.
Materials subjected to high-temperature service conditions will change their microstructure with time. Associated with this aging process is a change of mechanical properties as well as a change of damage mechanisms. Within the scope of the FVV project Aging and Lifetime, Fraunhofer IWM in Freiburg and BAM in Berlin (both Germany) experimentally characterized the widespread high-temperature aluminum alloy EN AW-2618A in different overaging states. Based on the experimental findings, models for numerical lifetime assessment with the finite-element method were implemented.
This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled “Toward a digital materials mechanical testing lab” [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.
This study investigates the room‐ and high‐temperature (650 °C) tensile and low‐cycle‐fatigue behavior of Inconel 718 produced by laser powder bed fusion (PBF‐LB/M) with a four‐step heat treatment and compares the results to the conventional wrought material. The microstructure after heat treatment is characterized on different length scales. Compared to the wrought variant, the elastic and yield properties are comparable at both test temperatures while tensile strength, ductility, and strain hardening capacity are lower. The fatigue life of the PBF‐LB/M variant at room temperature is slightly lower than that of the wrought material, while at 650 °C, it is vice versa. The cyclic stress response for both material variants is characterized by cyclic softening, which is more pronounced at the higher test temperature. High strain amplitudes (≥0.7%) at room temperature and especially a high testing temperature result in the formation of multiple secondary cracks at the transitions of regions comprising predominantly elongated grain morphology and columns of stacked grains with ripple patterns in the PBF‐LB/M material. This observation and pronounced crack branching and deflection indicate that the cracks are controlled by sharp micromechanical gradients and local crystallite clusters.
It is widely accepted that the magnetic state of a ferromagnetic material may be irreversibly altered by mechanical loading due to magnetoelastic effects. A novel standardized nondestructive testing (NDT) technique uses weak magnetic stray fields, which are assumed to arise from inhomogeneous deformation, for structural health monitoring (i.e., for detection and assessment of damage). However, the mechanical and microstructural complexity of damage has hitherto only been insufficiently considered. The aim of this study is to discuss the phenomenon of inhomogeneous “self-magnetization” of a polycrystalline ferromagnetic material under inhomogeneous deformation experimentally and with stronger material-mechanical focus. To this end, notched specimens were elastically and plastically deformed. Surface magnetic states were measured by a three-axis giant magnetoresistant (GMR) sensor and were compared with strain field (digital image correlation) and optical topography measurements. It is demonstrated that the stray fields do not solely form due to magnetoelastic effects. Instead, inhomogeneous plastic deformation causes topography, which is one of the main origins for the magnetic stray field formation. Additionally, if not considered, topography may falsify the magnetic signals due to variable lift-off values. The correlation of magnetic vector components with mechanical tensors, particularly for multiaxial stress/strain states and inhomogeneous elastic-plastic deformations remains an issue.
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.
Versions info:
V2 developed using BFO+CCO top-level ontologies.
V3 developed using PROVO+PMDco top-level ontologies.
V4 developed using BFO+IOF top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/ontologies/mechanical-testing-ontology
GitHub: https://github.com/HosseinBeygiNasrabadi/Mechanical-Testing-Ontology
MatPortal: https://matportal.org/ontologies/MTO
IndustryPortal: https://industryportal.enit.fr/ontologies/MTO
Addressing a strategy for publishing open and digital research data, this article presents the approach for streamlining and automating the process of storage and conversion of research data to those of semantically queryable data on the web. As the use case for demonstrating and evaluating the digitalization process, the primary datasets from low‐cycle‐fatigue testing of several copper alloys are prepared. The fatigue test ontology (FTO) and ckan.kupferdigital data management system are developed as two main prerequisites of the data digitalization process. FTO has been modeled according to the content of the fatigue testing standard and by reusing the basic formal ontology, industrial ontology foundry core ontology, and material science and engineering ontology. The ckan.kupferdigital data management system is also constructed in such a way that enables the users to prepare the protocols for mapping the datasets into the knowledge graph and automatically convert all the primary datasets to those machine‐readable data which are represented by the web ontology language. The retrievability of the converted digital data is also evaluated by querying the example competency questions, confirming that ckan.kupferdigital enables publishing open data that can be highly reused in the semantic web.
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.