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Fatigue test ontology (FTO)
(2024)
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
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
Tensile test ontology (TTO)
(2024)
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
Vickers test ontology (VTO)
(2024)
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
Brinell test ontology (BTO)
(2024)
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
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.
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.
Due to the advantages of Laser Powder Bed Fusion (PBF-LB), i.e., design freedom and the possibility to manufacture parts with filigree structures, and the considerable amount of knowledge available for 316L in its conventional variant, the mechanical behavior, and related microstructure-property relationships of PBF-LB/316L are increasingly subject of research. However, many aspects regarding the - application-relevant - mechanical behavior at high temperatures are not yet fully understood. Here, we present the results of an experimental study on the LCF behavior of PBF-LB/316L featuring a low defect population, which makes this study more microstructure-focused than most of the studies in the literature. The LCF tests were performed between room temperature (RT) and 600 °C. The mechanical response is characterized by strain-life curves, and hysteresis and cyclic deformation curves. The damage and deformation mechanisms are studied with X-ray computed tomography, and optical and electron microscopy. The PBF-LB/M/316L was heat treated at 450 °C for 4 h, and a hot‑rolled (HR) 316L variant with a fully recrystallized equiaxed microstructure was tested as a reference. Besides, selected investigations were performed after a subsequent heat treatment at 900 °C for 1 h. The PBF-LB/316L exhibits higher cyclic stresses than HR/316L for most of the fatigue life, especially at room temperature. At the smallest strain amplitudes, the fatigue lives of PBF-LB/M/316L are markedly shorter than in HR/316L. The main damage mechanisms are multiple cracking at slip bands (RT) and intergranular cracking (600 °C). Neither the melt pool boundaries nor the gas porosity have a significant influence on the LCF damage mechanism. The cyclic stress-strain deformation behavior of PBF-LB/M/316L features an initial hardening followed by a continuous softening. The additional heat treatment at 900 °C for 1 h led to decreased cyclic stresses, and a longer fatigue life.
The strength of age-hardenable aluminum alloys is based on the controlled formation of nm-sized precipitates, which represent obstacles to dislocation movement. Transmission electron microscopy (TEM) is generally used to identify precipitate types and orientations and to determine their size. This geometric quantification (e.g., length, diameter) is often performed by manual image analysis, which is very time consuming and sometimes poses reproducibility problems. The present work aims at the digital representation of this characterization method by proposing an automatable digital approach. Based on DF-TEM images of different precipitation states of alloy EN AW-2618A, a modularizable digital workflow is described for the quantitative analysis of precipitate dimensions. The integration of this workflow into a data pipeline concept is also presented. The semantic structuring of data allows data to be shared and reused for other applications and purposes, which enables interoperability.
The influence of test temperature and frequency on the fatigue life of the alloy EN AW-2618A (2618A) was characterized. The overaged condition (T61 followed by 1000 h/230 °C) was investigated in load-controlled tests with a stress ratio of R = -1 and two test frequencies (0.2 Hz, 20 Hz) at room temperature and at 230°C, respectively. An increase in the test temperature reduces fatigue life, whereby this effect is more pronounced at lower stress amplitudes. Decreasing the test frequency in tests at high temperatures further reduces the service life.
Following the new paradigm of materials development, design and optimization, digitalization is the main goal in materials sciences (MS) 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 (findability, accessibility, interoperability, reusability) 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-understandable and human-readable knowledge representations needed for data management, retrieval, and (re)use.
The project ‘platform MaterialDigital’ (PMD) is part of an initiative that 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 added values 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 ontologically 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 to store data in accordance with a testing standard compliant ontological representation of a tensile test of metals at room temperature (ISO 6892-1:2019-11). This includes the path from developing an ontology in accordance with the respective standard 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 enhanced reusability of data and knowledge from synthesis, production, and characterization of materials, the PMD core ontology (PMDco) was developed as mid-level ontology in the field of MSE. The semantic connection of the tensile test ontology (TTO) to the PMDco leads to enhanced expressivity and interoperability.
Moreover, as a best practice example, generation and acquisition of test data semantically connected to the ontology (data mapping) was realized by applying an electronic laboratory notebook (ELN). Corresponding tensile tests were performed by materials science students at university. This enabled a fully digitally integrated experimental procedure that can be transferred to other test series and experiments. In addition to facilitating the acquisition, analysis, processing, and (re)usability of data, this also raises the awareness of students with respect to data structuring and semantic technologies in the sense of education and training. The entire data pipeline is further seamlessly integrable in a laboratory information management system (LIMS). More specifically, the integration of semantic conceptualization and knowledge graphs may become essential parts in LIMS as this would be very beneficial. Therefore, some first approaches of SWT integration in LIMS will also be presented briefly.
The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations.
Digital Transformation in Materials Science: Insights From the Platform MaterialDigital (PMD)
(2024)
The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations.
Age-hardenable aluminum alloys undergo precise heat treatments to yield nanometer-sized precipitates that increase their strength and durability by hindering the dislocation mobility. Tensile tests provide mechanical properties, while microstructure evaluation relies on transmission electron microscopy (TEM), specifically the use of dark-field TEM images for precise dimensional analysis of the precipitates. However, this manual process is time consuming, skill dependent, and prone to errors and reproducibility issues.
Our primary goal is to digitally represent these processes while adhering to FAIR principles. Ontologies play a critical role in facilitating semantic annotation of (meta)data and form the basis for advanced data management. Publishing raw data, digital workflows, and ontologies ensures reproducibility.
This work introduces innovative solutions to traditional bottlenecks and offers new perspectives on digitalization challenges in materials science. We support advanced data management by leveraging knowledge graphs and foster collaborative and open data ecosystems that potentially revolutionize materials research and discovery.
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.
This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures.
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.
Laser Powder Bed Fusion (PBF-LB/M) of AISI 316L stainless steel has gained popularity due to its exceptional capacity to produce complex geometries and hierarchical microstructures, which can increase the yield strength while maintaining good ductility. Nevertheless, owing to high thermal gradients encountered during the process, the as printed 316L stainless steel often exhibit microstructural heterogeneities and residual stresses, which can limit its performance in demanding environments. Hence, employing heat treatments which balance the reduction of residual stresses while retaining improved static strength may be beneficial in various scenarios and applications. This study investigates the impact of post-processing heat treatments on the microstructure of 316L stainless steel manufactured via PBF-LB/M, along with its correlation with micro-hardness properties. To this end, 6 different heat treatments, i.e., 450 °C for 4h, 700 °C for 1h, 700 °C for 3h, 800 °C for 1h, 800 °C for 3h, and 900 °C for 1h, were applied to different specimens and Vickers hardness measurements (HV1) were performed in all states. At 800 °C, although the cellular structure appears to be retained, there is an observable increase in cellular size. However, while treatments exceeding 900 °C indicate no significant grain growth compared to other conditions, the cellular structure is entirely dissolved, which leads to a reduced Vickers hardness. The effect of the heat treatments on other microstructural features such as grain size and morphology, melt pool boundaries (MPB), crystallographic texture, chemical segregation, dispersoids and phase stability are also discussed in the present work
The general term additive manufacturing (AM) encompasses processes that enable the production of parts in a single manufacturing step. Among these, laser powder bed fusion (PBF-LB) is one of the most commonly used to produce metal components. In essence, a laser locally melts powder particles in a powder bed layer-by-layer to incrementally build a part. As a result, this process offers immense manufacturing flexibility and superior geometric design capabilities compared to conventional processes. However, these advantages come at a cost: the localized processing inevitably induces large thermal gradients, resulting in the formation of large thermal stress during manufacturing. In the best case, residual stress remains in the final parts produced as a footprint of this thermal stress. Since residual stress is well known to exacerbate the structural integrity of components, their assessment is important in two respects. First, to optimize process parameter to minimize residual stress magnitudes. Second, to study their effect on the structural integrity of components (e.g., validation of numerical models). Therefore, a reliable experimental assessment of residual stress is an important factor for the successful application of PBF-LB. In this context, diffraction-based techniques allow the non-destructive characterization of the residual stress. In essence, lattice strain is calculated from interplanar distances by application of Braggs law. From the known lattice strain, macroscopic stress can be determined using Hooke’s law. To allow the accurate assessment of the residual stress distribution by such methods, a couple of challenges in regard of the characteristic PBF-LB microstructures need to be overcome.
This presentation highlights some of the challenges regarding the accurate assessment of residual stress in PBF-LB on the example of the Nickel-based alloy Inconel 718. The most significant influencing factors are the use of the correct diffraction elastic constants, the choice of the stress-free reference, and the consideration of the crystallographic texture. Further, it is shown that laboratory X-ray diffraction methods characterizing residual stress at the surface are biased by the inherent surface roughness. Overall, the impact of the characteristic microstructure is most significant for the selection of the correct diffraction elastic constants. In view of the localized melting and solidification, no significant gradients of the stress-free reference are observed, even though the cell-like solidification sub-structure is known to be heterogeneous on the micro-scale.
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.
Laser powder bed fusion (PBF-LB/M) of metallic alloys is a layer-wise additive manufacturing process that provides significant scope for more efficient designs of components, benefiting performance and weight, leading to efficiency improvements for various sectors of industry. However, to benefit from these design freedoms, knowledge of the high produced induced residual stress and mechanical property anisotropy associated with the unique microstructures is critical. X-ray and neutron diffraction are considered the benchmark for non-destructive characterization of surface and bulk internal residual stress. The latter, characterized by the high penetration power in most engineering alloys, allows for the use of a diffraction angle close to 90° enabling a near cubic sampling volume to be specified. However, the complex microstructures of columnar growth with inherent crystallographic texture typically produced during PBF-LB/M of metallics present significant challenges to the assumptions typically required for time efficient determination of residual stress. These challenges include the selection of an appropriate set of diffraction elastic constants and a representative lattice plane suitable for residual stress analysis. In this contribution, the selection of a suitable lattice plane family for residual stress analysis is explored. Furthermore, the determination of an appropriate set of diffraction and single-crystal elastic constants depending on the underlying microstructure is addressed.
In-situ loading experiments have been performed at the Swiss Spallation Neutron Source with the main scope to study the deformation behaviour of laser powder bed fused Inconel 718. Cylindrical tensile bars have been subjected to an increasing mechanical load. At pre-defined steps, neutron diffraction data has been collected. After reaching the yield limit, unloads have been performed to study the accumulation of intergranular strain among various lattice plane families.
Relation of craze to crack length during slow crack growth phenomena in high‐density polyethylene
(2024)
The craze‐crack mechanism occurring in high‐density polyethylene (HDPE) causing slow crack growth and environmental stress cracking is investigated in detail with respect to the relation of crack length and the related craze zone. This is essential for the understanding of the resulting features of the formed fracture surface and their interpretation in the context of the transition from crack propagation to ductile shear deformation. It turns out that an already formed craze zone does not inevitably result in formation of a propagating crack, but could also undergo ductile failure. For the examination, the full notch creep test (FNCT) was employed with a subsequent advanced fracture surface analysis that was performed using various imaging techniques: light microscopy, laser scanning microscopy, scanning electron microscopy, and X‐ray micro computed tomography scan. FNCT specimens were progressively damaged for increasing durations under standard test conditions applying Arkopal, the standard surfactant solution, and biodiesel as test media were used to analyze the stepwise growth of cracks and crazes. From considerations based on well‐established fracture mechanics approaches, a theoretical correlation between the length of the actual crack and the length of the preceding craze zone was established that could be evidenced and affirmed by FNCT fracture surface analysis. Moreover, the yield strength of a HDPE material exposed to a certain medium as detected by a classic tensile test was found to be the crucial value of true stress to induce the transition from crack propagation due to the craze‐crack mechanism to shear deformation during FNCT measurements.
Highlights
- Progress of crack formation in high‐density polyethylene is analyzed by different imaging techniques
- Determined growth rates depend on distinction between craze zone and crack
- The ratio of the present crack to the anteceding craze zone is validated theoretically
- The transition from crack propagation to ductile shear deformation is identified
- An already formed craze zone may still fail by ductile mechanisms