TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Klotz, Ulrich E. A1 - Tiberto, Dario A1 - Vafaeenezhad, Hossein A1 - Mishurova, Tatiana A1 - Skrotzki, Birgit T1 - Effect of keyhole and lack-of-fusion pores on the anisotropic microstructure and mechanical properties of PBF-LB/M-produced CuCrZr alloy N2 - Due to the high reflectance and heat conductivity of copper and its alloys, the processing window for laser-based powder bed fusion (PBF-LB/M) processing of high-density copper components fundamentally overlaps with conduction and keyhole melting zones, resulting in the emergence of certain pores in the structure of printed parts. The present research aims to study how the development of process-induced lack-of-fusion or keyhole porosities during the PBF-LB/M process can affect the anisotropic microstructure and mechanical properties of the produced copper alloys. For this purpose, several samples were produced utilizing a similar CuCrZr-feedstock composition but varied process parameters from different areas of the PBF-LB/M processing window, specifically at laser powers of 300 W and 380 W which define the boarders of the conduction and keyhole regimes. X-ray computed tomography (XCT) revealed that the 300-W and 380-W samples achieved relative densities of 98.88% and 99.99%, respectively, with elongated lack-of-fusion pores forming at 300 W and semi-spherical keyhole pores at 380 W. Microstructural analyses employing scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) demonstrated strong anisotropy in different build directions of the samples, owing to the growth of long columnar grains with intense < 101  orientation along the build directions. Here, the emergence of different types of pores can cause competition between the epitaxial growth of columnar grains and the heterogeneous nucleation of new grains on the layers’ interfaces, thereby significantly varying the grain size, preferred orientation, crystallographic texture, and microstructural anisotropy of the samples. Furthermore, compression tests and nanoindentation measurements of the printed alloys in the longitudinal and transverse directions revealed that the 300 W and 380 W samples exhibited compressive strength anisotropies of 0.061 and 0.072, and average nanoindentation hardness values of 1.3 GPa and 1.5 GPa, respectively. The orientation of elongated lack-of-fusion porosities perpendicular to the loading axis was identified as the most damaging factor, significantly reducing mechanical performance compared to the uniformly distributed keyhole pores. KW - Copper Alloy KW - Laser-based powder bed fusion KW - Microstructure KW - Mechanical properties KW - X-ray computed tomography (XCT) KW - Porosity KW - Anisotropy PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-625655 DO - https://doi.org/10.1007/s40964-025-00972-2 SN - 2363-9520 SP - 1 EP - 15 PB - Springer Science and Business Media LLC AN - OPUS4-62565 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein T1 - Domain-level ontology formulation based on the Platform Material Digital (PMD) ontology: case study Brinell hardness N2 - A large amount of publicly available data is reproduced every day in the field of materials science, while these kind of material data can have different formats and types like paper-type publications, standards, datasheets or isolated datasets in repositories. However, gathering a specific library from such extensive and diverse material data is always challenging for the materials scientists and engineers, since the time-related limitations are not allowed to fully access the large publicly available databases; search across these disparate databases, manage the large volumes of heterogeneous datasets, and integrate data from multiple sources. To address these challenges and make data findable, accessible, interoperable, and reusable (FAIR), an efficient data management system is necessary to build comprehensive, documented, and connected data spaces in the future. A formal standardized knowledge representation through an ontology can address such problems and make data more available and interoperable between related domains. Ontology can also rich machine processable semantic descriptions that increases the performance of scientific searches. In this regard, the Platform MaterialDigital (PMD) is currently working on developing a high-level ontology for the materials and material related processes. For example, in one of the PMD projects of “KupferDigital”, we will try to develop a data ecosystem for digital materials research based on ontology-based digital representations of copper and copper alloys. As a case study, this paper describes the methodology for ontology development of Brinell hardness, based on PMD core ontology. The methodology we describe includes the following steps; gathering the required domain terminology from different resources like standards (DIN EN ISO 6506-1) and test reports, representing the performance of a standard-conformant hardness test and the treatment of the recorded values up to a “reportable” hardness value for a material, designing the process chain according to the semantic technologies, and developing a domain-level ontology of Brinell hardness based on PMD ontology semantic formalization. Apart the mentioned methodology, some interesting tools and methods were introduced and ontology design challenges and possible solutions for modelling materials and processes were discussed. Furthermore, a dataset from the Brinell hardness measurement of cast copper samples is prepared for testing the query process. T2 - MSE 2022 CY - Darmstadt, Germany DA - 27.09.2022 KW - Copper KW - Materials Science KW - Ontology KW - Platform MaterialDigital (PMD) KW - Brinell hardness PY - 2022 AN - OPUS4-56092 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Ontology-Oriented Modeling of the Vickers Hardness Knowledge Graph N2 - 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. KW - Data Mapping KW - FAIR Data KW - Ontology KW - Knowledge Graph KW - Vickers Hardness PY - 2024 DO - https://doi.org/10.4028/p-k8Gj2L VL - 149 SP - 33 EP - 38 PB - Trans Tech Publications Ltd CY - Switzerland AN - OPUS4-59981 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Waitelonis, Jörg A1 - Birkholz, Henk A1 - Jung, Matthias A1 - Schilling, Markus A1 - v. Hartrott, Philipp A1 - Bruns, Marian A1 - Schaarschmidt, Jörg A1 - Beilke, Kristian A1 - Mutz, Marcel A1 - Nebel, Vincent A1 - Königer, Veit A1 - Beran, Lisa A1 - Kraus, Tobias A1 - Vyas, Akhilesh A1 - Vogt, Lars A1 - Blum, Moritz A1 - Ell, Basil A1 - Chen, Ya‐Fan A1 - Waurischk, Tina A1 - Thomas, Akhil A1 - Durmaz, Ali Riza A1 - Ben Hassine, Sahar A1 - Fresemann, Carina A1 - Dziwis, Gordian A1 - Beygi Nasrabadi, Hossein A1 - Hanke, Thomas A1 - Telong, Melissa A1 - Pirskawetz, Stephan A1 - Kamal, Mohamed A1 - Bjarsch, Thomas A1 - Pähler, Ursula A1 - Hofmann, Peter A1 - Leemhuis, Mena A1 - Özçep, Özgür L. A1 - Meyer, Lars‐Peter A1 - Skrotzki, Birgit A1 - Neugebauer, Jörg A1 - Wenzel, Wolfgang A1 - Sack, Harald A1 - Eberl, Chris A1 - Portella, Pedro Dolabella A1 - Hickel, Tilmann A1 - Mädler, Lutz A1 - Gumbsch, Peter T1 - Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science N2 - This article describes advancements in the ongoing digital transformation in materials science and engineering. It is driven by domain‐specific successes and the development of specialized digital data spaces. There is an evident and increasing need for standardization across various subdomains to support science data exchange across entities. The MaterialDigital Initiative, funded by the German Federal Ministry of Education and Research, takes on a key role in this context, fostering collaborative efforts to establish a unified materials data space. The implementation of digital workflows and Semantic Web technologies, such as ontologies and knowledge graphs, facilitates the semantic integration of heterogeneous data and tools at multiple scales. Central to this effort is the prototyping of a knowledge graph that employs application ontologies tailored to specific data domains, thereby enhancing semantic interoperability. The collaborative approach of the Initiative's community provides significant support infrastructure for understanding and implementing standardized data structures, enhancing the efficiency of data‐driven processes in materials development and discovery. Insights and methodologies developed via the MaterialDigital Initiative emphasize the transformative potential of ontology‐based approaches in materials science, paving the way toward simplified integration into a unified, consolidated data space of high value. KW - Semantic Interoperability KW - Data Spaces KW - Integration Workflows KW - MaterialDigital PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-622952 DO - https://doi.org/10.1002/adem.202401092 SN - 1527-2648 SP - 1 EP - 25 PB - Wiley-VCH CY - Weinheim AN - OPUS4-62295 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Bauer, Felix A1 - Uhlemann, Patrick A1 - Thärig, Steffen A1 - Rehmer, Birgit A1 - Skrotzki, Birgit T1 - Mechanical testing dataset of cast copper alloys for the purpose of digitalization N2 - 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. KW - FAIR principles KW - Hardness KW - Low-Cycle Fatigue (LCF) KW - Tensile testing KW - Stress relaxation PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-605005 DO - https://doi.org/10.1016/j.dib.2024.110687 SN - 2352-3409 SP - 1 EP - 15 PB - Elsevier BV AN - OPUS4-60500 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eisenbart, Miriam A1 - Hanke, Thomas A1 - Bauer, Felix A1 - Beygi Nasrabadi, Hossein A1 - Junghanns, Kurt A1 - Dziwis, Gordian A1 - Tikana, Ladji A1 - Parvez, Ashak Mahmud A1 - van den Boogaart, Karl Gerald A1 - Sajjad, Mohsin A1 - Friedmann, Valerie A1 - Preußner, Johannes A1 - Ramakrishnan, Anantha Narayanan A1 - Klengel, Sandy A1 - Meyer, Lars‐Peter A1 - Martin, Michael A1 - Klotz, Ulrich Ernst A1 - Skrotzki, Birgit A1 - Weber, Matthias T1 - KupferDigital: Ontology‐Based Digital Representation for the Copper Life Cycle N2 - The copper life cycle comprises numerous stages from the alloy production to the manufacturing and usage of engineered parts until recycling. At each step, valuable data are generated and stored; some are transferred to the subsequent stations. A thorough understanding of the materials’ behavior during manufacturing processes or throughout their product lifetime is highly dependent on a reliable data transfer. If, for example, a failure occurs during the service life, information about the manufacturing route can be of decisive importance for detecting the root cause of the failure. Additionally, the life cycle assessment hinges on the availability of data. Recording and storing interoperable structured data is, therefore, a thriving research field with huge implications for the economic strength of the manufacturing industry. In the KupferDigital project, it is demonstrated how an ontology‐based data space can be utilized not only as an innovative method for storing and providing interoperable life cycle data but also as a means to enable automated data analysis and evaluation, leading to new insights and the creation of new knowledge using semantic data and technologies. This work illustrates how data recorded at different research facilities can be integrated into one single data space, allowing queries across heterogeneous sources. KW - Copper Alloy KW - Ontology KW - Digitalization KW - Data Space KW - Semantic Representation PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-630213 SN - 1527-2648 DO - https://doi.org/10.1002/adem.202401735 VL - 27 IS - 8 SP - 1 EP - 29 PB - Wiley AN - OPUS4-63021 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Ontology-oriented modeling of the Vickers hardness knowledge graph N2 - 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. T2 - ICMMM 2023: 10th International Conference on Mechanics, Materials and Manufacturing CY - Washington, D.C., USA DA - 18.08.2023 KW - Ontology KW - Knowledge graph KW - Data mapping KW - Vickers hardness KW - FAIR data PY - 2023 AN - OPUS4-58100 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Tensile test ontology (TTO) N2 - Tensile Test Ontology (TTO) has developed for representing the Tensile testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6892-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. V3 developed using PROVO+PMDco top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/tensile-test GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO- MatPortal: https://matportal.org/ontologies/TTO IndustryPortal: https://industryportal.enit.fr/ontologies/TTO KW - Ontology KW - Tensile testing PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/tensile-test UR - https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO- UR - https://matportal.org/ontologies/TTO UR - https://industryportal.enit.fr/ontologies/TTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60545 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Norouzi, Ebrahim A1 - Sack, Harald A1 - Skrotzki, Birgit T1 - Performance Evaluation of Upper‐Level Ontologies in Developing Materials Science Ontologies and Knowledge Graphs N2 - This study tackles a significant challenge in ontology development for materials science: selecting the most appropriate upper‐level ontologies for creating application‐level ontologies and knowledge graphs. Focusing on the use case of Brinell hardness testing, the research assesses the performance of various top‐level ontologies (TLOs)—basic formal ontology (BFO), elementary multiperspective material ontology (EMMO), and provenance ontology (PROVO)—in developing Brinell testing ontologies (BTOs). Consequently, three versions of BTOs are created using combinations of these TLOs along with their integrated mid‐ and domain‐level ontologies. The performance of these ontologies is evaluated based on ten parameters: semantic richness, domain coverage, extensibility, complexity, mapping efficiency, query efficiency, integration with other ontologies, adaptability to different data contexts, community acceptance, and documentation and maintainability. The results show that all candidate TLOs can effectively develop BTOs, each with its distinct advantages. BFO provides a well‐structured, understandable hierarchy, and excellent query efficiency, making it suitable for integration across various ontologies and applications. PROVO demonstrates balanced performance with strong integration capabilities. Meanwhile, EMMO offers high semantic richness and domain coverage, though its complex structure impacts query efficiency and integration with other ontologies. KW - Materials Science KW - Ontology KW - Knowledge Graph PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-612227 DO - https://doi.org/10.1002/adem.202401534 SN - 1527-2648 SP - 1 EP - 18 PB - Wiley AN - OPUS4-61222 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Hanke, Thomas A1 - Skrotzki, Birgit T1 - Semantic Representation of Low‐Cycle‐Fatigue Testing Data Using a Fatigue Test Ontology and ckan.kupferdigital Data Management System N2 - 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. KW - Accessible KW - CKAN KW - Interoperable KW - Digitalizations KW - Ontologies KW - Reusable data KW - Fatigue testing PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-604991 UR - https://onlinelibrary.wiley.com/doi/10.1002/adem.202400675 DO - https://doi.org/10.1002/adem.202400675 SN - 1527-2648 SP - 1 EP - 11 PB - Wiley AN - OPUS4-60499 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Tensile stress relaxation test ontology (TSRTO) N2 - Tensile Stress Relaxation Test Ontology (TSRTO) has developed for representing the tensile stress relaxation testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 10319-1 standard. Versions info: V1 developed using BFO+CCO top-level ontologies. V3 developed using PROV+PMDco top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/relaxation-test GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Stress-Relaxation-Test-Ontology-TSRTO MatPortal: https://matportal.org/ontologies/TSRTO IndustryPortal: https://industryportal.enit.fr/ontologies/TSRTO KW - Ontology KW - Tensile stress relaxation testing KW - FAIR data PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/relaxation-test UR - https://github.com/HosseinBeygiNasrabadi/Tensile-Stress-Relaxation-Test-Ontology-TSRTO UR - https://matportal.org/ontologies/TSRTO UR - https://industryportal.enit.fr/ontologies/TSRTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60546 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Chen, Yue A1 - Schilling, Markus A1 - von Hartrott, P. A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit A1 - Olbricht, Jürgen T1 - Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing N2 - In recent years, the design and development of materials are strongly interconnected with the development of digital technologies. In this respect, efficient data management is the building block of material digitization and, in the field of materials science and engineering (MSE), effective solutions for data standardization and sharing of different digital resources are needed. Therefore, ontologies are applied that represent a map of MSE concepts and relationships between them. Among different ontology development approaches, graphical editing based on standard conceptual modeling languages is increasingly used due to its intuitiveness and simplicity. This approach is also adopted by the Materials-open-Laboratory project (Mat-o-Lab), which aims to develop domain ontologies and method graphs in accordance with testing standards in the field of MSE. To suit the actual demands of domain experts in the project, Ontopanel was created as a plugin for the popular open-source graphical editor diagrams.net to enable graphical ontology editing. It includes a set of pipeline tools to foster ontology development in diagrams.net, comprising imports and reusage of ontologies, converting diagrams to Web Ontology Language (OWL), verifying diagrams using OWL rules, and mapping data. It reduces learning costs by eliminating the need for domain experts to switch between various tools. Brinell hardness testing is chosen in this study as a use case to demonstrate the utilization of Ontopanel. KW - Materials Testing KW - Ontology KW - Visual ontology development KW - Data mapping KW - FAIR PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-560339 DO - https://doi.org/10.1007/s40192-022-00279-y SP - 1 EP - 12 PB - Springer AN - OPUS4-56033 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Hanke, T. A1 - Weber, M. A1 - Eisenbart, M. A1 - Bauer, F. A1 - Meissner, R. A1 - Dziwis, G. A1 - Tikana, L. A1 - Chen, Yue A1 - Skrotzki, Birgit T1 - Toward a digital materials mechanical testing lab N2 - 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. KW - General Engineering KW - General Computer Science PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-582698 DO - https://doi.org/10.1016/j.compind.2023.104016 SN - 0166-3615 VL - 153 SP - 1 EP - 15 PB - Elsevier B.V. AN - OPUS4-58269 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein T1 - Materials Mechanical Testing Ontology (MTO) N2 - 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. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Mechanical testing KW - Ontology KW - Standard PY - 2023 AN - OPUS4-58270 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Bauer, Felix A1 - Uhlemann, Patrick A1 - Rehmer, Birgit A1 - Skrotzki, Birgit T1 - KupferDigital mechanical testing datasets: Stress relaxation and low-cycle fatigue (LCF) tests N2 - 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. KW - Copper alloys KW - Dataset KW - Stress relaxation KW - Mechanical testing KW - Low-cycle fatigue. PY - 2024 DO - https://doi.org/10.5281/zenodo.10820437 PB - Zenodo CY - Geneva AN - OPUS4-59665 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit A1 - Hanke, Thomas A1 - Chen, Yue T1 - Brinell test ontology (BTO) N2 - Brinell Test Ontology (BTO) has developed for representing the Brinell testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6506-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. V3 developed using EMMO+CHAMEO top-level ontologies. V4 developed using PROVO+PMDco top-level ontologies. V5 developed using BFO+IOF top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/brinell-hardness-test GitHub: https://github.com/HosseinBeygiNasrabadi/Brinell-Test-Ontology-BTO- MatPortal: https://matportal.org/ontologies/BTO IndustryPortal: https://industryportal.enit.fr/ontologies/BTO KW - Ontology KW - Knowledge graph KW - Data mapping KW - Brinell hardness KW - FAIR data PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/brinell-hardness-test UR - https://github.com/HosseinBeygiNasrabadi/Brinell-Test-Ontology-BTO- UR - https://matportal.org/ontologies/BTO UR - https://industryportal.enit.fr/ontologies/BTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60543 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Bauer, Felix A1 - Tikana, Ladji A1 - Uhlemann, Patrick A1 - Thärig, Steffen A1 - Rehmer, Birgit A1 - Skrotzki, Birgit T1 - KupferDigital mechanical testing datasets N2 - 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. KW - Copper alloys KW - Dataset KW - Tensile testing KW - Mechanical testing KW - Hardness test PY - 2023 DO - https://doi.org/10.5281/zenodo.7670582 PB - Zenodo CY - Geneva AN - OPUS4-57038 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Digital representation of materials testing data for semantic web analytics: Tensile stress relaxation testing use case N2 - 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. KW - Digitalization KW - Tensile stress relaxation KW - Ontology KW - Mechanical testing KW - Semantic web PY - 2024 DO - https://doi.org/10.4028/p-xSmHN2 VL - 987 SP - 47 EP - 52 PB - Trans Tech Publications Ltd CY - Switzerland AN - OPUS4-61152 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein T1 - Platform MaterialDigital (PMD) approach for the integration and management of FAIR low cycle fatigue (LCF) testing data N2 - This study represents the generation and storage of findable, accessible, interoperable, and reusable (FAIR) fatigue testing data by utilizing the Platform MaterialDigital (PMD) core ontology (PMDco) as well as some containerized PMD-server applications. Based on the specifications of the ISO 12106:2017-03 standard [1] and the acquired test reports of the mechanical testing facility, a highly comprehensive process graph of the fatigue testing procedure was created. Consequently, the PROV Ontology (PROVO) and PMDco [2] were used as upper-level ontologies to model the fatigue testing ontology (FTO). A part of the FTO classes hierarchy is shown in Fig. 1, where all the concepts of test procedure, test apparatus, test piece, and test properties were respectively located in the appropriate hierarchies of pmd:Process (prov:Activity), pmd:ProcessingNode (prov:Agent), pmd:Object (prov:Entity), and pmd:ValueObject (prov:Entity) classes. FTO is publicly available via the GitLab repository [3]. Reusing these upper-level ontologies and materials testing standards not only improves FTO's compatibility with other ontologies but also ensures its acceptance and deployment in industry [4]. The fatigue testing process graph has also been designed in such a manner that it allows for the entire mapping of testing metadata. In this respect, low-cycle fatigue (LCF) experiments were carried out on several cast copper alloys at various strain ratios, and the resulting CSV test report files were stored in a public repository [5]. Eventually, the processes of mapping the experimental test data into the fatigue process graph, converting the RDF data, storage of the triples in a triple store, and SPARQL query from the obtained triples are evaluated by different PMD-based tools like PMD OntoDocker [6]. T2 - MSE2024 CY - Darmstadt, Germany DA - 24.09.2024 KW - Digitalization KW - FAIR KW - Low cycle fatigue PY - 2024 AN - OPUS4-61151 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit A1 - Hanke, Thomas A1 - Eisenbart, Miriam T1 - Mechanical testing ontology (MTO) N2 - 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 KW - Ontology KW - Mechanical testing KW - FAIR data PY - 2023 UR - https://gitlab.com/kupferdigital/ontologies/mechanical-testing-ontology/ PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-58271 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein T1 - Digital representation of materials testing data for semantic web analytics: Tensile stress relaxation testing use case N2 - 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. T2 - ICMDA 2024: 7th International Conference on Materials Design and Applications CY - Tokyo, Japan  DA - 09.04.2024 KW - Digitalization KW - Tensile stress relaxation KW - Ontology KW - Mechanical testing KW - Semantic web PY - 2024 AN - OPUS4-59979 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Fatigue test ontology (FTO) N2 - Fatigue Test Ontology (FTO) has developed for representing the fatigue testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 12106 standard. Versions info: V2 developed using PROVO+PMDco top-level ontologies. V3 developed using BFO+IOF top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/lcf-test GitHub: https://github.com/HosseinBeygiNasrabadi/Fatigue-Test-Ontology-FTO- MatPortal: https://matportal.org/ontologies/FTO IndustryPortal: https://industryportal.enit.fr/ontologies/FTO KW - Ontology KW - Fatigue testing KW - FAIR data PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/lcf-test UR - https://github.com/HosseinBeygiNasrabadi/Fatigue-Test-Ontology-FTO- UR - https://matportal.org/ontologies/FTO UR - https://industryportal.enit.fr/ontologies/FTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60547 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein T1 - Nb and Cr coating the CuNi3SiCr powders for low-power laser-based powder bed fusion processing of copper alloys N2 - The laser-based powder bed fusion (PBF-LB/M) processing of high-density copper components is mainly performed with high laser powers due to the low laser absorption of copper powders [1-2]. Metal coating the copper particles has been investigated in this research as an approach for increasing the laser absorption of the feedstock and processing of highly dense copper alloys with low-power lasers. CuNi3SiCr powders were coated with the thin and uniform metallic shells of Nb (60 ± 10 nm) using a rotating Direct Current Magnetron Sputtering Physical Vapor Deposition (DCMS-PVD) reactor. Using such metal-coated particles, copper parts of 98.14% relative density were printed with the PBF-LB/M parameters of 200 W laser powers, 800 mm/s scanning speed, 55 µm hatch distance, and 25 µm layer thickness. The X-ray computed tomography (XCT), scanning electron microscope (SEM), and energy dispersive spectroscopy (EDS) investigations show that partial oxidation of Nb-coated particles is responsible for the development of lack-of-fusion holes between the printed layers. An approach based on the nanoindentation and electron backscattered diffraction (EBSD) measurements was utilized to evaluate the correlation between the crystallographic orientations and mechanical properties of the produced samples. In this approach, arrays of indentations (Fig. 1a) were applied on four planes of the samples trimmed in different directions. The EBSD images of these indentation regions reveal the location of each indent in colored grains of different orientations. Here, a microstructure with columnar grains and a high texture intensity of 9.2 has been observed in the plane perpendicular to the building direction. This plane comprises a mixture of red-, green-, and blue-colored grains, while the measured average hardness (H) and indentation modulus (Er) were increased from red grains to green and blue ones, respectively (Fig. 1b). Eventually, the nanoindentation load-displacement curves of [001], [101], and [111] grains (Fig. 1c) were utilized for modeling the elastoplastic features of the produced samples. T2 - MSE2024 CY - Darmstadt, Germany DA - 24.09.2024 KW - Coating KW - Laser-based powder bed fusion processing KW - Copper PY - 2024 AN - OPUS4-61149 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Vickers test ontology (VTO) N2 - Vickers Test Ontology (VTO) has developed for representing the Vickers testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6507-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test GitHub: https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO- MatPortal: https://matportal.org/ontologies/VTO IndustryPortal: https://industryportal.enit.fr/ontologies/VTO KW - Ontology KW - Knowledge graph KW - Data mapping KW - Vickers hardness KW - FAIR data. PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test UR - https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO- UR - https://matportal.org/ontologies/VTO UR - https://industryportal.enit.fr/ontologies/VTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60544 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -