TY - CONF A1 - Völker, Christoph T1 - Integration von Forschungsdaten im Bereich zerstörungsfreien Prüfung (ZfP) im Bauwesen N2 - Der Vortrag gibt einen Überblick zu Fragestellungen, Herausforderungen und Nutzen von semantischer Datenintegration im Forschungsbereich der zerstörungsfreien Prüfung im Bauwesen. T2 - 1. KDA Kolloquium der BAM CY - Berlin, Germany DA - 29.03.2019 KW - Digitalisierung KW - Ontology KW - ZfP KW - Beton KW - Datenanalyse PY - 2019 AN - OPUS4-50026 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zia, Ghezal Ahmad Jan A1 - Hanke, Thomas A1 - Skrotzki, Birgit A1 - Völker, Christoph A1 - Bayerlein, Bernd T1 - Enhancing Reproducibility in Precipitate Analysis: A FAIR Approach with Automated Dark-Field Transmission Electron Microscope Image Processing N2 - 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. KW - Industrial and Manufacturing Engineering KW - General Materials Science KW - Automated image analysis KW - FAIR research data management KW - Reproducibility KW - microstructural changes PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-593905 DO - https://doi.org/10.1007/s40192-023-00331-5 SN - 2193-9772 SP - 1 EP - 15 PB - Springer Science and Business Media LLC CY - Heidelberg AN - OPUS4-59390 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Hanke, T. A1 - Muth, Thilo A1 - Riedel, Jens A1 - Schilling, Markus A1 - Schweizer, C. A1 - Skrotzki, Birgit A1 - Todor, A. A1 - Moreno Torres, Benjami A1 - Unger, Jörg F. A1 - Völker, Christoph A1 - Olbricht, Jürgen T1 - A Perspective on Digital Knowledge Representation in Materials Science and Engineering N2 - The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples. In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge. KW - Data infrastructures KW - Digital representations KW - Digital workflows KW - Knowledge graphs KW - Materials informatics KW - Ontologies KW - Vocabulary providers PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546729 DO - https://doi.org/10.1002/adem.202101176 SN - 1438-1656 SP - 1 EP - 14 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-54672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Shokouhi, P. T1 - Data aggregation for improved honeycomb detection in concrete using machine learning-based algorithms N2 - We present the results of several machine learning (ML)- inspired data fusion algorithms applied to multi-sensory nondestructive testing (NDT) data. Our dataset consists of Impact-Echo (IE), Ultrasonic Pulse Echo (US) and Ground Penetrating Radar (GPR) data collected on large-scale concrete specimens with built–in simulated honeycombing defects. The main objective is to improve the detectability of honeycombs by fusing the information from the three different sensors. We describe normalization, feature detection and optimal feature selection. We have used unsupervised and supervised ML, i.e., classification and clustering, for data fusion. We demonstrate the advantage of data fusion in reducing the false positives up to 10% compared to the best single sensor, thus, improving the detectability of the defects. The methods were evaluated on a concrete specimen. The effectiveness of the proposed approach was demonstrated on a separate full-scale concrete specimen. The results indicate the transportability of the conclusions from one specimen to the other. T2 - NDT-CE 2015 - International symposium non-destructive testing in civil engineering CY - Berlin, Germany DA - 15.09.2015 KW - Data fusion KW - Concrete evaluation KW - Honeycombing KW - Machine learning KW - Clustering PY - 2015 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-350968 UR - https://www.ndt.net/?id=18364 SN - 1435-4934 VL - 20 IS - 11 SP - 1 EP - 8 PB - NDT.net CY - Kirchwald AN - OPUS4-35096 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Krause, Martin A1 - Mauke, R. A1 - Effner, Ute A1 - Milmann, Boris A1 - Völker, Christoph A1 - Wiggenhauser, Herbert T1 - Ultrasonic testing of a sealing construction made of salt concrete in an underground disposal facility for radioactive waste N2 - For the closure of radioactive waste disposal facilities engineered barriers- so called “drift seals” are used. The purpose of these barriers is to constrain the possible infiltration of brine and to prevent the migration of radionuclides into the biosphere. In a rock salt mine a large scale in-situ experiment of a sealing construction made of salt concrete was set up to prove the technical feasibility and operability of such barriers. In order to investigate the integrity of this structure, non-destructive ultrasonic measurements were carried out. Therefore two different methods were applied at the front side of the test-barrier: 1 Reflection measurements from boreholes 2 Ultrasonic imaging by means of scanning ultrasonic echo methods This extended abstract is a short version of an article to be published in a special edition of ASCE Journal that will briefly describe the sealing construction, the application of the non-destructive ultrasonic measurement methods and their adaptation to the onsite conditions -as well as parts of the obtained results. From this a concept for the systematic investigation of possible contribution of ultrasonic methods for quality assurance of sealing structures may be deduced. T2 - NDT-CE 2015 - International symposium non-destructive testing in civil engineering CY - Berlin, Germany DA - 2015-09-15 KW - Ultrasonic reflection measurement KW - Dry contact transducers in boreholes KW - Interface salt-concrete / rock salt KW - Ultrasonic imaging of internal reflectors PY - 2015 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-346203 UR - http://www.ndt.net/?id=18304 SN - 1435-4934 VL - 20 IS - 11 SP - 1 EP - 4 PB - NDT.net CY - Kirchwald AN - OPUS4-34620 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Karafiludis, Stephanos A1 - Standl, Jacob A1 - Ryll, Tom W. A1 - Schwab, Alexander A1 - Prinz, Carsten A1 - Wolf, Jakob B. A1 - Kruschwitz, Sabine A1 - Emmerling, Franziska A1 - Völker, Christoph A1 - Stawski, Tomasz M. T1 - High-Entropy Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization N2 - Transition metal phosphates (TMPs) are extensively explored for electrochemical and catalytical applications due to their structural versatility and chemical stability. Within this material class, novel high-entropy metal phosphates (HEMPs)─containing multiple transition metals combined into a single-phase structure─are particularly promising, as their compositional complexity can significantly enhance functional properties. However, the discovery of suitable HEMP compositions is hindered by the vast compositional design space and complex or very specific synthesis conditions. Here, we present a data-driven strategy combining automated wet-chemical synthesis with a Sequential Learning App for Materials Discovery (SLAMD) framework (Random Forest regression model) to efficiently explore and optimize HEMP compositions. Using a limited set of initial experiments, we identified multimetal compositions in a single-phase crystalline solid. The model successfully predicted a novel Co0.3Ni0.3Fe0.2Cd0.1Mn0.1 phosphate octahydrate phase, validated experimentally, demonstrating the effectiveness of the machine learning approach. This work highlights the potential of integrating automated synthesis platforms with data-driven algorithms to accelerate the discovery of high-entropy materials, offering an efficient design pathway to advanced functional materials. KW - Metal phosphates KW - High entropy KW - Sequential learning KW - Automated synthesis KW - MAP KW - Random forest KW - Machine learning PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-641554 DO - https://doi.org/10.1021/acs.cgd.5c00549 SN - 1528-7483 VL - 25 IS - 19 SP - 7989 EP - 8001 PB - American Chemical Society (ACS) CY - Washington, DC AN - OPUS4-64155 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stawski, Tomasz A1 - Karafiludis, Stephanos A1 - Standl, Jakob A1 - Ryll, Tom A1 - Schwab, Alexander A1 - Prinz, Carsten A1 - Wolf, Jakob A1 - Kruschwitz, Sabine A1 - Emmerling, Franziska A1 - Völker, Christoph T1 - High-Entropy Metal Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization N2 - To accelerate high-entropy metal phosphate (HEMP) discovery, we employed a Random Forest regression model within a SLAMD framework. Trained on limited initial data, the model efficiently explored the vast compositional space to predict a novel five-metal phosphate, which was then successfully synthesized and validated experimentally. T2 - AI4 Materials Science and Testing 2025 CY - Berlin, Germany DA - 06.11.2025 KW - Metal phosphates KW - High-entropy KW - Sequential learning PY - 2025 AN - OPUS4-64686 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Recknagel, Christoph A1 - Geburtig, Anja A1 - Wachtendorf, Volker T1 - Die Kunst der Fuge im Glasfassadenbau N2 - Ingenieurbauwerke wie Brücken, hoch beanspruchte Verkehrsflächen oder auch Hochhäuser und deren Bauwerksteile wie z.B. Hochhausfassaden werden aus technischen und ästhetischen Gründen durch Fugen in Einzelabschnitte unterteilt. Zur Sicherstellung der Gebrauchsfähigkeit und zum Schutz des Gesamtbauwerks, aber in zunehmendem Maße auch zur statisch-konstruktiven Anbindung der Bauwerksteile, werden diese Fugenspalte in aller Regel durch spezielle Fugenfüllsysteme verschlossen. Aufgrund der hohen Sicherheitsrelevanz bei Fugenfüllungen im Glasfassadenbau fordert das Baurecht auch bei diesen Bauprodukten als Voraussetzung für die baupraktische Verwendbarkeit neben dem Nachweis der Funktionsfähigkeit auch den Nachweis der Dauerhaftigkeit. Da die hierfür bekannten Nachweismethoden zur Dauerhaftigkeit keine allgemeine Zulassungsakzeptanz finden, kann das ästhetische, bauphysikalische und ökonomische Potential von modernen geklebten Ganzglasfassaden (sogenannte SSG-Fassaden) in der Baupraxis der Bundesrepublik Deutschland derzeit nicht ausgenutzt werden. Grund dafür sind die ungenügend erfassten und in den Bewertungsverfahren simulierten Wechselwirkungen derartiger Baukonstruktionen mit der Umwelt. In diesem Beitrag soll am Beispiel moderner Fugen im Glasfassadenbau (SSG-Fassaden) eine ganzheitliche gebrauchsbezogene Versuchsmethodik zur kontrollierten Ansprache der Funktionsfähigkeit und Dauerhaftigkeit von Fugensystemen unter realitätsnah und reproduzierbar simulierten Umwelteinwirkungen vorgestellt werden. Dazu werden die maßgebenden Umwelteinflüsse und die Quantifizierung der daraus folgenden Beanspruchungen auf derartige Fugensysteme dargestellt. Basierend darauf werden eine repräsentative Beanspruchungsfunktion zur Nachstellung der maßgebenden Umwelteinflüsse und Beanspruchungen auf das System Tragrahmen - Fugenfüllung- Glasscheibe sowie eine geeignete Probendimensionierung abgeleitet. In der Konsequenz werden die Erkenntnisse in den Aufbau einer neuartigen komplexen Versuchseinrichtung überführt. Funktionsprinzip und Leistungsparameter dieser Anlage zur Umweltsimulation werden vorgestellt. Die Möglichkeiten der Systemkennzeichnung werden vorgestellt. Erste Versuchsergebnisse zeigen das Potential der neuartigen Bewertungsmethodik auf, die Kunst der Fuge im Bauwesen gebrauchsorientiert weiter zu entwickeln. T2 - 44. Jahrestagung der GUS 2015 CY - Stutensee-Blankenloch, Germany DA - 25.03.2015 KW - Umweltsimulation KW - Dauerhaftigkeit KW - Funktionsverhalten KW - Neue Untersuchungsmethodik PY - 2015 SN - 978-3-9816286-4-7 SP - 125 EP - 139 AN - OPUS4-33040 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -