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The efforts taken within the project ‘platform MaterialDigital’ (PMD, materialdigital.de) to store FAIR data in accordance with a standard-compliant ontological representation (‘application ontology’) of a tensile test of metals at room temperature (ISO 6892-1:2019-11) will be presented. This includes the path from developing an ontology in accordance with the respective standard, converting ordinary data obtained from standard tests into the interoperable RDF format, up to connecting the ontology and data. The semantic connection of the ontology and data leads to interoperability and an enhanced ability of querying. For further reusability of data and knowledge semantically stored, the PMD core ontology (PMDco) was developed, which is a mid-level ontology in the field of MSE. The semantic connection of the tensile test application ontology to the PMDco is also presented. Moreover, Ontopanel, a tool for domain experts facilitating visual ontology development and mapping for FAIR data sharing in MSE, is introduced briefly.
This is an interactive workshop of the Plattform MaterialDigital (PMD) on Semantic Web technologies (SWT) where we delve into the world of ontology development and data structuring in the field of materials science and engineering (MSE). This workshop is designed to equip participants with essential skills in categorizing classes within ontologies, with a special emphasis on the PMD Core Ontology (PMDco). Discover the immense value of ontologies for MSE data reproducibility and reuse and harness the power of PMDco to foster your data management practices.
In this workshop, you will explore the intricacies of class categorization when developing ontologies in the MSE domain. Through interactive discussions and hands-on exercises, you will learn effective techniques for structuring and organizing ontologies to enhance data retrieval and analysis. You will gain valuable insights into best practices and considerations for class categorization, aiming at optimal data organization and management within your MSE projects.
One of the highlights of this workshop is the introduction to PMDco, a mid-level ontology in the field of MSE developed community-driven in the frame of the project PMD. Learn about PMDco, its underlying concepts, and its application in detail. Discover how PMDco provides a comprehensive framework for MSE data representation, enabling seamless integration and interoperability across different systems and platforms. In addition to exploring PMDco, this workshop will illustrate the benefits of data interoperability and SWT with respect to leveraging the full potential of MSE data.
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.
Die zunehmende geopolitische Bedeutung der Ressourcenverfügbarkeit sowie die Anforderungen an einen geschlossenen Materialkreislauf treiben die Materialforschung voran, um konventionelle Werkstoffe mit weniger kritischen Zusätzen zu legieren oder sogar vollständig mit nachhaltigeren Alternativen zu substituieren. Eine potenzielle Alternative stellen die intermetallischen Eisenaluminid-Legierungen (FeAl) dar. Im Labormaßstab wurden bereits viele Legierungskonzepte für verbesserte Hochtempera- tureigenschaften oder Duktilität erfolgreich gießtechnisch umgesetzt. Eine erfolgreiche Erprobung von FeAl-Legierungen im industriellen Maßstab stand zu Beginn des Projekts aber weiterhin aus. Ziel des Vorhabens war daher die Entwicklung von simulationsgestützten Gießkonzepten in industrienahe Gießprozesse anhand der Modelllegierung Fe-26Al-4Mo-0,5Ti-1B und die Eingrenzung der prozesstechnischen Verfahrensgrenzen durch Warmrissversuche. Erkenntnisse hieraus wurden in einen praxisorientierten, für zukünftige Anwender in KMUs zugänglichen Handlungskatalog für die gießgerechte Auslegung von Bauteilen aus Eisenaluminiden überführt. Fokus wurde insbesondere auf das Feinguss- und Kokillengussverfahren im Schleuderguss gesetzt. Neben zahlreicher Konstruktions- und Gießprozessparameter wurden auch Wärmebehandlungen und Legierungszusätze (Al, Mo, B) variiert, um den Einfluss von Legierungselementen auf Gießbarkeit, Mikrostruktur und mechanische Kennwerte zu be- stimmen. Eine umfangreiche Basis an Daten aus Mikrostrukturanalysen (Mikroskopische Bildgebung, Bestimmung von Korngrößen sowie Phasenzusammensetzungen und -anteilen, Fraktographie), mechanischen Tests (Härtemessungen, Druckversuch, Zugversuch, Warmzugversuch, Kriechversuch) sowie Messungen thermophysikalischer Eigenschaften konnte für die Modelllegierung erzeugt werden. Korrelationen dieser Informationen mit Prozessvariablen erlaubten Schlussfolgerungen zu Härtungsmechanismen und Duktilität in der Legierung und wie sie prozesstechnisch in Gieß- und Bauteilauslegung gesteuert werden können. Der erfolgreiche Abguss von hochkomplexen Bauteilgeometrien mit dünnen Wandstärken sowie optimierte Legierungszusammensetzungen zeigen Perspektiven auf neue Anwendungsfelder auf.
Das Ziel des Forschungsvorhabens ist erreicht worden.
Die hohen Betriebstemperaturen während des Einsatzes von Radialverdichterrädern in Abgasturboladern führen zu einer Änderung der ursprünglich eingestellten Mikrostruktur in der warmfesten Aluminiumlegierung EN AW-2618A (Überalterung). Grund dafür sind thermische Belastungen, die nahe der Aushärtetemperatur liegen und diese kurzzeitig sogar überschreiten können. Die Alterungsmechanismen wurden zusammen mit den Themen niederzyklische (LCF) und thermomechanische Ermüdung (TMF) sowie Kriechen bis max. 190 °C in vorangegangenen Forschungsvorhaben untersucht. Kaum untersucht war bisher das Verhalten der Legierung unter hochzyklischer Beanspruchung (HCF) sowie der Einfluss von Kerben und Lastkollektiven. Da zukünftig mit weiter steigenden Betriebstemperaturen für Radialverdichter zu rechnen ist, wurde in diesem Forschungsvorhaben das HCF-Verhalten bei 230 °C untersucht und somit bei einer Prüftemperatur, die deutlich oberhalb der Aushärtetemperatur liegt. Das Ziel des Projektes war der Aufbau einer geeigneten experimentellen Datenbasis, das Verständnis der relevanten mikrostrukturellen Prozesse sowie die Weiterentwicklung und Anpassung geeigneter Modelle und Bewertungsmethoden.
Das experimentelle Untersuchungsprogramm umfasste neben einer Basischarakterisierung des HCF-Verhaltens am Ausgangszustand T61 gezielte mechanische Versuche zur Isolierung der Einflussfakto-ren Mittelspannung (𝑅 = −1, 𝑅 = 0,1), Werkstoffüberalterung (T61, 10 h/230 °C, 1000 h/230 °C), Prüftemperatur (20 °C, 230 °C), Prüffrequenz (0,2 Hz, 20 Hz) sowie Kerbwirkung und variable Amplituden. Darauf aufbauend wurden die in den vorangegangenen Projekten entwickelten Modelle und Bewertungsmethoden angepasst und weiterentwickelt, um die genannten thermischen und mechanischen Belastungen in der Lebensdauerbewertung abzubilden.
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 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.
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 poster 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.
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.
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.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
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.
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.
PMD Core Ontology (PMDco)
(2023)
The PMD Core Ontology (PMDco) is a comprehensive framework for representing knowledge that encompasses fundamental concepts from the domains of materials science and engineering (MSE). The PMDco has been designed as a mid-level ontology to establish a connection between specific MSE application ontologies and the domain neutral concepts found in established top-level ontologies. The primary goal of the PMDco is to promote interoperability between diverse domains. PMDco's class structure is both understandable and extensible, making it an efficient tool for organizing MSE knowledge. It serves as a semantic intermediate layer that unifies MSE knowledge representations, enabling data and metadata to be systematically integrated on key terms within the MSE domain. With PMDco, it is possible to seamlessly trace data generation. The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the generation, derivation, and attribution of resources. By building on this foundation, PMDco facilitates the integration of data from various sources and the creation of complex workflows. In summary, PMDco is a valuable tool for researchers and practitioners in the MSE domains. It provides a common language for representing and sharing knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless traceability of data generation. Overall, PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain. PMDco at GitHub: https://github.com/materialdigital/core-ontology
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.
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.
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.
The PMD Core Ontology (PMDco) is a comprehensive set of building blocks produced via consensus building. The ontological building blocks provide a framework representing knowledge about fundamental concepts used in Materials Science and Engineering (MSE) today. The PMDco is a mid-level ontology that establishes connections between narrower MSE application ontologies and domain neutral concepts used in already established broader (top-level) ontologies. The primary goal of the PMDco design is to enable interoperability between various other MSE-related ontologies and other common ontologies.
PMDco’s class structure is both comprehensive and extensible, rendering it an efficient tool to structure MSE knowledge. The PMDco serves as a semantic middle-layer unifying common MSE concepts via semantic mapping to other semantic representations using well-known key terms used in the MSE domain. The PMDco enables straight-forward documentation and tracking of science data generation and in consequence enables high-quality FAIR data that allows for precise reproducibility of scientific experiments.
The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the production, derivation, and attribution of resources. Via this foundation, the PMDco enables the integration of data from various data origins and the representation of complex workflows.
In summary, the PMDco is a valuable advancement for researchers and practitioners in MSE domains. It provides a common MSE vocabulary to represent and share knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless tracing of science data. Overall, the PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain in general.
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.
The increasing importance of resource availability and closed-loop material cycles are driving materials research to reduce alloying content in conventional materials or even substitute them with more sustainable alternatives. Intermetallic iron aluminide alloys (FeAl) present a potential alternative. Many alloy concepts for improved high-temperature properties or ductility have already been successfully implemented in casting technologies on a laboratory scale. However, successful testing of FeAl alloys on an industrial scale was still pending at the beginning of the project.
Therefore, the aim of the project was to develop simulation based casting concepts for industrial casting processes using the base alloy Fe-26Al-4Mo-0.5Ti-1B and to narrow down process limits by means of hot cracking tests. Findings were transferred into practice-oriented guidelines for casting of iron aluminides, which is accessible to future applicants in SMEs. The focus was placed on centrifugal casting combined with investment casting or die casting. In addition to numerous design and casting process parameters, heat treatments and alloying additions (Al, Mo, B) were varied to determine the influence of alloying elements on castability, microstructure and mechanical properties. Data from microstructure analyses (microscopic imaging, determination of grain sizes as well as phase compositions and volume fractions, fractography), mechanical tests (hardness measurements, compression tests, ambient and high-temperature tensile tests, creep tests) as well as measurements of thermophysical properties could be generated on the base alloy. Correlations of materials data with process variables allowed conclusions to be drawn on strengthening mechanisms and ductility of the alloy and how they can be controlled in terms of processing and component design. Successful casting of highly complex components with thin wall thicknesses and optimised alloy compositions points out prospects for new fields of application.
The increasing importance of resource availability and closed-loop material cycles are driving materials research to reduce alloying content in conventional materials or even substitute them with more sustainable alternatives. Intermetallic iron aluminide alloys (FeAl) present a potential alternative. Many alloy concepts for improved high-temperature properties or ductility have already been successfully implemented in casting technologies on a laboratory scale. However, successful testing of FeAl alloys on an industrial scale was still pending at the beginning of the project.
Therefore, the aim of the project was to develop simulation-based casting concepts for industrial casting processes using the base alloy Fe-26Al-4Mo-0.5Ti-1B and to narrow down process limits by means of hot cracking tests. Findings were transferred into practice-oriented guidelines for casting of iron aluminides, which is accessible to future applicants in SMEs. The focus was placed on centrifugal casting combined with investment casting or die casting. In addition to numerous design and casting process parameters, heat treatments and alloying additions (Al, Mo, B) were varied to determine the influence of alloying elements on castability, microstructure and mechanical properties. Data from microstructure analyses (microscopic imaging, determination of grain sizes as well as phase compositions and volume fractions, fractography), mechanical tests (hardness measurements, compression tests, ambient and high-temperature tensile tests, creep tests) as well as measurements of thermophysical properties could be generated on the base alloy. Correlations of materials data with process variables allowed conclusions to be drawn on strengthening mechanisms and ductility of the alloy and how they can be controlled in terms of processing and component design. Successful casting of highly complex components with thin wall thicknesses and optimised alloy compositions points out prospects for new fields of application.
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) of the consortium Materials Science and Engineering (MatWerk) of National Research Data Infrastructure (NFDI) aims to develop, together with BAM and other Participant Projects (PP), 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 identifying 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.
Tensile Test Ontology (TTO)
(2023)
This is the stable version 2.0.1 of the PMD ontology module of the tensile test (Tensile Test Ontology - TTO) as developed on the basis of the 2019 standard ISO 6892-1: Metallic materials - Tensile Testing - Part 1: Method of test at room temperature.
The TTO was developed in the frame of the PMD project. The TTO provides conceptualizations valid for the description of tensile test and corresponding data in accordance with the respective standard. By using TTO for storing tensile test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which will lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of TTO facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of tensile test data is enhanced and data querying in combination with other aspects and data within the broad field of material science and engineering (MSE) is facilitated.
The TTO class structure forms a comprehensible and semantic layer for unified storage of data generated in a tensile test including the possibility to record data from analysis, re-evaluation and re-use. Furthermore, extensive metadata allows to assess data quality and reproduce experiments. Following the open world assumption, object properties are deliberately low restrictive and sparse.
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 elastic properties (Young's modulus, shear modulus) of Ni-based alloy Inconel IN718 were investigated between room temperature and 800 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled bar). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty.
The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.
This article reports temperature-dependent elastic properties (Young’s modulus, shear modulus) of three alloys measured by the dynamic resonance method. The alloys Ti-6Al-4V, Inconel IN718, and AISI 316 L were each investigated in a variant produced by an additive manufacturing processing route and by a conventional manufacturing processing route. The datasets include information on processing routes and parameters, heat treatments, grain size, specimen dimensions, and weight, as well as Young’s and shear modulus along with their measurement uncertainty. The process routes and methods are described in detail. The datasets were generated in an accredited testing lab, audited as BAM reference data, and are hosted in the open data repository Zenodo. Possible data usages include the verification of the correctness of the test setup via Young’s modulus comparison in low-cycle fatigue (LCF) or thermo-mechanical fatigue (TMF) testing campaigns, the design auf VHCF specimens and the use as input data for simulation purposes.
This article refers to the research article entitled “Creep-Fatigue of P92 in Service-Like Tests with Combined Stress- and Strain-Controlled Dwell Times” [1]. It presents experimental mechanical data from complex service-like creep-fatigue experiments performed isothermally at 620 °C and a low strain amplitude of 0.2 % on tempered martensite-ferritic grade P92 steel. The data sets in text file format provide cyclic deformation (min. and max. stresses) and the total (hysteresis) data of all recorded fatigue cycles for three different creep-fatigue experiments: 1) a standard relaxation fatigue (RF) test with symmetrical dwell times of three minutes introduced at minimum and maximum strain, 2) a fully strain-controlled service-like relaxation (SLR) test combining these three-minute peak strain dwells with a 30-minute dwell in between at zero strain, and 3) a partly stress-controlled service-like creep (SLC) test combining the three-minute peak strain dwells with 30-minute dwells at constant stress. Such service-like (SL) tests with additional long-term stress- and strain-controlled dwell times are non-standard, rare, and expensive, making these data very valuable. They may be used to approximate cyclic softening in the technically relevant range, for the design of complex SL experiments, or for detailed analyses of stress-strain hystereses (e.g., for stress or strain partitioning methods, for the determination of hysteresis energies (work), inelastic strain components, etc.). In addition, the latter analyses may supply important input for advanced parametric lifetime modeling of components under creep-fatigue loading or model calibration parameters.
The elastic properties (Young's modulus, shear modulus) of titanium alloy Ti-6Al-4V were investigated between room temperature and 400 °C in an additively manufactured variant (laser-based directed energy deposition with powder as feedstock, DED-LB/M) and from a conventional process route (hot rolled bar). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, microstructure, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty.
The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.
The elastic properties (Young's modulus, shear modulus) of austenitic stainless steel AISI 316L were investigated between room temperature and 900 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled sheet). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty.
The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.
Creep-fatigue of P92 in service-like tests with combined stress- and strain-controlled dwell times
(2023)
Complex service-like relaxation- and creep-fatigue tests with strain- and stress-controlled dwells and fatigue cycle durations of approx. 2200 s were performed exemplarily on a grade P92 steel at 620 ◦C in this study. The results indicate deviations in the prevailing creep mechanisms of long-term relaxation and creep dwells, affecting subsequent dwells, load shifts, and the macroscopic softening behavior quite differently. In addition, fracture surfaces and longitudinal metallographic sections reveal intergranular crack growth for complex loading with stress-controlled dwells, whereas complex strain-controlled tests enhance oxidation and transgranular crack propagation. These findings substantiate the limited transferability of relaxation-fatigue to creep-fatigue conditions.
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.
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
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.
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.
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.
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.
This is the stable version of the full-notch creep test ontology (OntoFNCT) that ontologically represents the full-notch creep test. OntoFNCT has been developed in accordance with the corresponding test standard ISO 16770:2019-09 Plastics - Determination of environmental stress cracking (ESC) of polyethylene - Full-notch creep test (FNCT).
The OntoFNCT provides conceptualizations that are supposed to be valid for the description of full-notch creep tests and associated data in accordance with the corresponding test standard. By using OntoFNCT for storing full-notch creep test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which is meant to lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of OntoFNCT facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of full-notch creep test data is enhanced and querying in combination with other aspects and data within the broad field of materials science and engineering (MSE) is facilitated.
The class structure of OntoFNCT forms a comprehensible and semantic layer for unified storage of data generated in a full-notch creep test including the possibility to record data from analysis and re-evaluation. Furthermore, extensive metadata allows to assess data quality and reliability. Following the open world assumption, object properties are deliberately low restrictive and sparse.
Unlike conventional alloys, which typically consist of one main element, high-entropy alloys (HEAs) contain five or more principal elements, which broaden chemical complexity and with it a realm of synergistic mechanisms. The AlMo0.5NbTa0.5TiZr HEA initiated a subclass of Al-containing refractory (r)HEAs that has recently drawn attention [2]. The alloy has a superalloy-resembling B2/bcc nanostructure, which inspired its name refractory high entropy superalloy (RSA). With high-temperature (HT) compressive strengths beyond conventional Ni-based superalloys, this nanostructure could be used for improved HT structural applications. However, in the application-relevant HT regime the Al-Zr-rich B2 phase decomposes to form a hexagonal Al-Zr-based intermetallic (Al4-xZr5; x: 0..1) [3,4]. This work explores the fascinating yet fatal micromechanisms associated to this phase transformation, in the context of creep, annealing and oxidation experiments performed between 800 and 1200 °C.
The material was produced by arc-melting and heat treatment in argon, which lead to grain boundaries decorated with up to 7%. Interrupted constant-load creep tests were performed under vacuum (at 10-4 Pa), at 900–1100 °C with external tensile stresses of 30–120 MPa. Oxidation experiments were separately conducted for 24 hours at 800 and 1000 °C in both dry (21% O2 + 79% N2) and humid (8% O2 + 74% N2 + 18% H2O) air. After the experiments, the samples were characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy to reveal degradation mechanisms. Crystallographic texture, orientation relationships and stabilization of an oxygen-containing iso structure (Al4-xZr5(Ox-y); y: 0..x) of the Al-Zr-rich intermetallic are found and discussed.
AbstractThis study applies Semantic Web technologies to advance Materials Science and Engineering (MSE) through the integration of diverse datasets. Focusing on a 2000 series age-hardenable aluminum alloy, we correlate mechanical and microstructural properties derived from tensile tests and dark-field transmission electron microscopy across varied aging times. An expandable knowledge graph, constructed using the Tensile Test and Precipitate Geometry Ontologies aligned with the PMD Core Ontology, facilitates this integration. This approach adheres to FAIR principles and enables sophisticated analysis via SPARQL queries, revealing correlations consistent with the Orowan mechanism. The study highlights the potential of semantic data integration in MSE, offering a new approach for data-centric research and enhanced analytical capabilities.
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.
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.
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.
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.
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.
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.
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) 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 on a prototypical basis 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 poster presentation illustrates demonstrators developed and deployed within the PMD project. Semantically anchored using the mid-level PMD Core Ontology (PMDco), they address data transformation leading to a novel data management which is based on semantic integrated data. The PMD data acquisition pipeline (DAP), which is fueled by traditional, diverse data formats, and a pipeline applying an electronic laboratory notebook (ELN) as data source are displayed. Additionally, the efficient combination of diverse datasets originating from different sources is demonstrated by the representation of a use case dealing with the well-known Orowan relation.
Die additive Fertigung (AM) metallischer Werkstoffe ist eine Technologie, die zunehmend Gegenstand von Forschungsaktivitäten und industrieller Anwendung ist. Dennoch steht sie noch vor Herausforderungen, um eine breite Nutzung in sicherheitsrelevanten Anwendungen zu erreichen. Die Hauptgründe für die Verzögerung des technologischen Durchbruchs zugunsten von AM-Metallen gegenüber konventionell hergestellten Varianten sind das Fehlen eines tieferen Verständnisses der Prozess-Struktur-Eigenschafts-Beziehungen und die begrenzte Verfügbarkeit von Daten zu den Materialeigenschaften. In diesem Kontext stellt diese Arbeit einen Beitrag sowohl zum Verständnis der Prozess-Struktur-Eigenschafts-Beziehungen als auch zur Verbesserung der Datenlage von 316L dar, einem häufig als Konstruktionswerkstoff in verschiedenen Hochtemperaturbauteilen verwendeten Werkstoff. Die Arbeit legt den Fokus auf die mittels Laser-Pulverbettschmelzen hergestellte Werkstoffvariante, PBF-LB/M/316L. Eine konventionell hergestellte Variante, HR/316L, wurde auch untersucht. Bei PBF-LB/M/316L wurde zusätzlich der Effekt ausgewählter Wärmebehandlungen ausgewertet. Die Untersuchung umfasste die Charakterisierung der mechanischen Eigenschaften und der Verformungs- und Schädigungsmechanismen bei erhöhten Prüftemperaturen bei LCF und Kriechen, wo die Daten und Wissenslage am spärlichsten ist. Außerdem hat die untersuchte PBF-LB/M/316L-Wersktoffvariante einen geringen Porositätsgrad. Somit hat diese Arbeit die Mikrostruktur stärker in den Fokus genommen als die meisten bisher in der Literatur verfügbaren Studien.
Die mechanische Prüfkampagne umfasste Zugversuche zwischen Raumtemperatur und 650 °C, LCF-Versuche zwischen Raumtemperatur und 600 °C sowie Kriechversuche bei 600 °C und 650 °C. In Ermangelung konkreter Richtlinien und Normen wurde die Charakterisierung zumeist anhand der bestehenden internationalen Prüfnormen und Probengeometrien durchgeführt. Aus jedem dieser Prüfverfahren wurden die entsprechenden Festigkeits- und Verformungskennwerte ermittelt. Darüber hinaus wurde mit Hilfe gezielter mikrostruktureller Untersuchungen ein Beitrag zum Verständnis des Zusammenhangs zwischen der Mikrostruktur und den mechanischen Eigenschaften in Bezug auf die Verformungs- und Schädigungsmechanismen geleistet.
Die Dehngrenze von PBF-LB/M/316L ist etwa doppelt so hoch wie die von HR/316L und dieser Trend setzt sich mit ansteigender Prüftemperatur fort. Die Bruchdehnung ist bei allen Prüftemperaturen geringer. PBF-LB/M/316L weist über den größten Teil der Ermüdungslebensdauer vor allem bei Raumtemperatur höhere zyklische Spannungen als HR/316L auf. Ausschließlich bei den kleinsten Dehnungs-schwingbreiten sind die Ermüdungslebensdauer ausgeprägt kürzer. Das Wechselverformungsverhalten von PBF-LB/M/316L ist durch eine Anfangsverfestigung gefolgt von einer kontinuierlichen Entfestigung charakterisiert, welche bis zum Auftreten der zum Versagen führenden Entfestigung stattfindet. Die Kriechbruchzeiten und die Dauer jeder Kriechphase sind bei allen Kombinationen von Prüfparametern bei PBF-LB/M/316 kürzer als bei HR/316L. Die Spannungsabhängigkeit von PBF-LB/M/316L ist im Vergleich zu HR/316L geringer und die Duktilität beim Kriechen kleiner. Die minimale Kriechrate wird bei allen geprüften Parameterkombinationen bei deutlich geringeren Kriechdehnungen erreicht. Eine Wärmebehandlung bei 450 °C / 4 h bewirkt keine wesentliche Änderungen der Mikrostruktur und Zugversuchseigenschaften. Eine zusätzliche Wärmebehandlung bei 900 °C / 1 h verursacht eine Abnahme der Dehngrenze des PBF-LB/M/316L. Diese blieb aber immer noch um den Faktor 1,5x höher als bei HR/316L. Die Verformungsmerkmale wurden kaum davon beeinflusst. Bezüglich des Kriechverhaltens hat die Wärmebehandlung bei 900 °C / 1 h längere sekundäre und tertiäre Kriechstadien bewirkt und die Kriechdehnung hat sich signifikant erhöht. Die Bruchbilder unterscheiden sich generell nicht nur aber vor allem mit ansteigender Prüftemperatur, bei der bei PBF-LB/M/316L oft interkristalline Rissbildung beobachtet wurde. Die Zellstruktur trägt als der Hauptfaktor zu den unterschiedlichen mechanischen Eigenschaften im Vergleich zur HR/316L-Variante bei. Darüber hinaus spielen mutmaßlich die Kornmorphologie, die Stapelfehlerenergie und der Stickstoffgehalt eine Rolle.
Additive manufacturing (AM) offers significantly greater freedom of design compared to conventional manufacturing processes since the final parts are built layer by layer. This enables metal AM, also known as metal 3D printing, to be utilized for improving efficiency and functionality, for the production of parts with very complex geometries, and rapid prototyping. However, despite many technological advancements made in recent years, several challenges hinder the mass adoption of metal AM. One of these challenges is mechanical anisotropy which describes the dependency of material properties on the material orientation. Therefore, in this work, stainless steel 316L parts produced by laser-based powder bed fusion are used to isolate and understand the root cause of anisotropy in AM parts. Furthermore, an efficient and accurate multiscale numerical framework is presented for predicting the deformation behavior of actual AM parts on the macroscale undergoing large plastic deformations. Finally, a novel constitutive model for the plastic spin is formulated to capture the influence of the microstructure evolution on the material behavior on the macroscale.
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.