TY - CONF A1 - Unger, Jörg F. A1 - Robens-Radermacher, Annika A1 - Tamsen, Erik T1 - Data provenance - from experimental data to trustworthy simulation models and standards T2 - CMSS23 N2 - FAIR (findable, accessible, interoperable and reusable) data usage is one of the main principals that many of the research and funding organizations include in their strategic plans, which means that following the main principals of FAIR data is required in many research projects. The definition of data being FAIR is very general, and when implementing that for a specific application or project or even setting a standardized procedure within a working group, a company or a research community, many challenges arise. In this contribution, an overview about our experience with different methods, tools and procedures is outlined. We begin with a motivation on potential use cases for the applications of FAIR data with increasing complexity starting from a reproducible research paper over collaborative projects with multiple participants such as Round-Robin tests up to data-based models within standardization codes, applications in machine learning or parameter estimation of physics-based simulation models. In a second part, different options for structuring the data are discussed. On the one hand, this includes a discussion on how to define actual data structures and in particular metadata schema, and on the other hand, two different systems for storing the data are discussed. The first one is the openBIS system, which is an open-source Lab notebook and PostgreSQL based data management system. A second option are a semantic representations using RDF based ontologies for the domain of interest. In a third section, requirements for workflow tools to automate data processing are discussed and their integration into reproducible data analysis is presented with an outlook on required information to be stored as metadata in the database. Finally, the presented procedures are exemplarily demonstrated for the calibration of a temperature dependent constitutive model for additively manufactured mortar. Metadata schemata for a rheological measurement setup are derived and implemented in an openBIS database. After a short review of a potential numerical model predicting the structural build-up behaviour, the automatic workflow to use the stored data for model parameter estimation is demonstrated. T2 - 4th International Congress on Materials & Structural Stability CY - Rabat, Morocco DA - 08.03.2023 KW - Data provenance KW - Experimental data to trustworthy KW - Simulation models and Standards PY - 2023 UR - https://www.rsc-cmss23.asmatec.org/RILEM%20Committees%20Program.php SP - 1 EP - 9 CY - Rabat, Morocco AN - OPUS4-57349 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika A1 - Unger, Jörg F. A1 - Mezhov, Alexander A1 - Schmidt, Wolfram ED - Biondini, F. ED - Frangopo, D. M. T1 - Temperature dependent modelling approach for early age behavior of printable mortars T2 - Life-Cycle of Structures and Infrastructure Systems N2 - Structural build-up describes the stability and early-age strength development of fresh mortar used in 3D printing. lt is influenced by several factors, i.e. the composition of the print­ able material, the printing regime, and the ambient conditions. The existing modelling approaches for structural build-up usually define the model parameters for a specific material composition with­ out considering the influence of the ambient conditions. The goal of this contribution is to explicitly include the temperature dependency in the modelling approach. Temperature changes have signifi­ cant impact on the structural build-up process: an increase of the temperature leads to a faster dissol­ ution of cement phases and accelerates hydration. The proposed extended model includes temperature dependency using the Arrhenius theory. The new model parameters are successfully calibrated based on Viskomat measurement data using Bayesian inference. Furthermore, a higher impact of the temperature in the re-flocculation as in the structuration stage is observed. T2 - The Eighth International Symposium on Life-Cycle Civil Engineering (IALCCE 2023) CY - Milano, Italien DA - 02.07.2023 KW - 3D concrete printing KW - Material characterization KW - Structural build-up KW - Thixotropy KW - Model calibration PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-582175 SN - 978-1-003-32302-0 DO - https://doi.org/10.1201/9781003323020-146 SN - 978-1-003-32302-0 VL - 1st Edition SP - 1193 EP - 1200 PB - CRC Press AN - OPUS4-58217 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pirskawetz, Stephan A1 - Gründer, Klaus-Peter A1 - Kadoke, Daniel A1 - Unger, Jörg F. T1 - Überwachung von Stahlbetonbrücken - Ein Modellprojekt T2 - DGZfP-Berichtsband N2 - Die Brücken im Netz der Bundesverkehrswege sind überwiegend in einem ausreichenden bis guten Zustand. Allerdings steigt der Unterhalts- und Sanierungsaufwand aufgrund des inzwischen hohen Alters vieler Brücken sowie des ständig wachsenden Schwerlastverkehrs. Techniken zur Einschätzung der verbleibenden Lebensdauer von Brücken sowie zur dauerhaften Beobachtung des Tragverhaltens bzw. des Erfolges von Sanierungsmaßnahmen werden daher für den sicheren und wirtschaftlichen Betrieb dringend benötigt. Zur Evaluierung dafür geeigneter holistischer Ansätze wurde in der BAM das Projekt BLEIB - Bewertung, Lebensdauerprognose und Instandsetzung von Brückenbauwerken - ins Leben gerufen. Ein zentrales Ergebnis des Projektes ist eine extern vorgespannte Stahlbetonbrücke als Zweifeldträger mit einer Gesamtlänge von 24 m, die für den Test verschiedenster Sensorsysteme, zur Validierung numerischer Modelle und zur Erprobung von Sanierungs- und Verstärkungsmaßnahmen entwickelt wurde. Für die Simulation unterschiedlicher Schädigungsgrade kann die Vorspannung der Brücke variiert werden. Die Brücke wird mit beweglichen Gewichten belastet und über einen Shaker zum Schwingen angeregt. Das Brückenmodell wurde bewusst geschädigt, indem die Vorspannung der Struktur erstmalig schrittweise bis auf null reduziert wurde. Unter der Eigenlast verformte sich die Brücke, wodurch eine Rissbildung im Beton einsetzte. Die Zugspannung, die zuvor durch die Vorspannung aufgenommen wurde, übernahm Schritt für Schritt der Beton. Als die Zugspannungen die relativ geringe Zugfestigkeit des Betons überstiegen, begann dieser zu reißen und die schlaffe Bewehrung der Struktur nahm die Spannungen auf. Dieser Versuch wurde unter anderem von Schallemissionsmessungen begleitet. Der Rissbildungsprozess konnte damit, bei gleichzeitiger Aufzeichnung der Vorspannung, früh detektiert und die Risse geortet werden. Die Ergebnisse korrelieren gut mit den Ergebnissen der stereophotogrammetrischen Verformungsmessungen der Struktur. T2 - 22. Kolloquium Schallemission und 3. Anwenderseminar Zustandsüberwachung mit geführten Wellen CY - Karlsruhe, Germany DA - 27.03.2019 KW - Brückenmonitoring KW - Schallemissionsanalyse PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-477878 SN - 978-3-947971-00-8 VL - 169 SP - 1 EP - 5 PB - Deutsche Gesellschaft für Zerstörungsfreie Prüfung (DGZfP) CY - Berlin AN - OPUS4-47787 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meng, Birgit A1 - Dehn, F. A1 - Unger, Jörg F. A1 - Shepherd, D. A. A1 - Tamsen, Erik A1 - Pirskawetz, Stephan T1 - Wissensbasierte Digitalisierung von betontechnologischen Materialdaten T2 - Sonderausgabe des Online-Journals ce/papers von Wiley N2 - Die sprunghaft zunehmende Wichtigkeit von FAIR- und Open-Data für die Qualitätssicherung, aber auch für die Nachnutzbarkeit von Daten und den Erkenntnisfortschritt führt zu enormem Flandlungsbedarf in Forschung und Entwicklung. Damit verbunden laufen derzeit vielfältige, ambitionierte Aktionen, z. B. bezüglich der Erstellung von Ontologien und Wissensgraphen. Das Knowhow entwickelt sich rasant, die Ansätze zur Implementation entstehen in verschiedenen Fachwelten bzw. mit unterschiedlichen Zielsetzungen parallel, so dass recht heterogene Herangehensweisen resultieren. Diese Veröffentlichung fokussiert auf Arbeiten, die derzeit als möglichst ganzheitlicher Ansatz für Materialdaten im Rahmen der Digitalisierungsinitiative „Plattform MaterialDigital" vorangetrieben werden. Die Autoren bearbeiten baustoffbezogene Aspekte im Verbundprojekt „LeBeDigital - Lebenszyklus von Beton". Zielsetzung ist die digitale Beschreibung des Materialverhaltens von Beton über den kompletten Herstellungsprozess eines Fertigteils mit einer Integration von Daten und Modellen innerhalb eines Workflows zur probabilistischen Material- und Prozessoptimierung. Es wird über die Vorgehensweise und die dabei gewonnenen Erfahrungen berichtet, nicht ohne den Blick auf die oft unterschätzte Komplexität der Thematik zu lenken. T2 - Internationale Baustofftagung (ibausil) CY - Weimar, Germany DA - 13.09.2023 KW - Beton KW - Digitalisierung KW - Materialdaten KW - Datenmanagement KW - FAIR-Prinzip KW - Metadaten KW - Ontologie KW - Wissengraph PY - 2023 UR - https://www.uni-weimar.de/de/bauingenieurwesen/institute/fib/ibausil/ VL - 2023 SP - 1 EP - 11 PB - Sonderausgabe des Online-Journals ce/papers von Wiley AN - OPUS4-58315 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kindrachuk, Vitaliy A1 - Titscher, Thomas A1 - Hirthammer, Volker A1 - Unger, Jörg F. ED - Meschke, G. ED - Pichler, B. ED - Rots, J.G. T1 - A continuum damage model for the simulation of concrete under cyclic loading T2 - Computational modelling of concrete structures N2 - Lifetime aspects including fatigue failure of concrete structures were traditionally only of minor importance. Because of the growing interest in maxing out the capacities of concrete, its fatigue failure under compression has become an issue. A variety of interacting phenomena such as e.g. loss of prestress, degradation due to chemical reactions or creep and shrinkage influence the fatigue resistance. Failure due to cyclic loads is generally not instantaneous, but characterized by a steady damage accumulation. Therefore, a reliable numerical model to predict the performance of concrete over its lifetime is required, which accurately captures order effects and full three-dimensional stress states. Many constitutive models for concrete are currently available, which are applicable for specific loading regimes, different time scales and different resolution scales. However, a key limitation of those models is that they generally do not address issues related to fatigue on a structural level. Very few models can be found in the literature that reproduce deterioration of concrete under repeated loading-unloading cycles. This is due to the computational effort necessary to explicitly resolve every cycle which exceeds the currently available computational resources. The limitation can only be overcome by the application of multiscale methods in time. The objective of the paper is the development of numerical methods for the simulation of concrete under fatigue loading using temporal multiscale methods. First, a continuum damage model for concrete is developed with a focus on fatigue under compressive stresses [1]. This includes the possibility to model stress redistributions and capture size effects. In contrast to cycle based approaches, where damage is accumulated based on the number of full stress cycles, a strain based approach is developed that can capture cyclic degradation under variable loading cycles including different amplitudes and loading frequencies. The model is designed to represent failure under static loading as a particular case of fatigue failure after a single loading cycle. As a consequence, most of the material parameters can be deduced from static tests. Only a limit set of additional constitutive parameters is required to accurately describe the evolution under fatigue loading. Another advantage of the proposed model is the possibility to directly incorporate other multi-physics effects such as creep and shrinkage or thermal loading on the constitutive level. Second, a multiscale approach in time is presented to enable structural computations of fatigue failure with a reduced computational effort. The damage rate within the short time scale corresponding to a single cycle is computed based on a Fourier based approach [2]. This evolution equation is then solved on the long time scale using different implicit and explicit time integration schemes. Their performance and some limitations for specific loading regimes is discussed. Finally, the developed methods will be validated and compared to experimental data. [1] Vitaliy Kindrachuk, Marc Thiele, Jörg F. Unger. Constitutive modeling of creep-fatigue interaction for normal strength concrete under compression, International Journal of Fatigue, 78:81-94, 2015 [2] Vitaliy Kindrachuk, Jörg F. Unger. A Fourier transformation-based temporal integration scheme for viscoplastic solids subjected to fatigue deterioration, International Journal of Fatigue, 100:215-228, 2017 T2 - Conference on Computational Modelling of concrete and concrete structures (EURO_C 2018') CY - Bad Hofgastein, Austria DA - 26.02.2018 KW - Fatigue KW - Concrete KW - Damage PY - 2018 SN - 978-1-138-74117-1 DO - https://doi.org/10.1201/9781315182964-19 SP - 155 EP - 164 PB - CRC Press, Taylor & Francis Group CY - Boca Raton, Lodon, New York, Leiden AN - OPUS4-47999 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Andres Arcones, Daniel A1 - Weiser, M. A1 - Koutsourelakis, F.-S. A1 - Unger, Jörg F. T1 - Evaluation of Model Bias Identification Approaches Based on Bayesian Inference and Applications to Digital Twins N2 - In recent years, the use of simulation-based digital twins for monitoring and assessment of complex mechanical systems has greatly expanded. Their potential to increase the information obtained from limited data makes them an invaluable tool for a broad range of real-world applications. Nonetheless, there usually exists a discrepancy between the predicted response and the measurements of the system once built. One of the main contributors to this difference in addition to miscalibrated model parameters is the model error. Quantifying this socalled model bias (as well as proper values for the model parameters) is critical for the reliable performance of digital twins. Model bias identification is ultimately an inverse problem where information from measurements is used to update the original model. Bayesian formulations can tackle this task. Including the model bias as a parameter to be inferred enables the use of a Bayesian framework to obtain a probability distribution that represents the uncertainty between the measurements and the model. Simultaneously, this procedure can be combined with a classic parameter updating scheme to account for the trainable parameters in the original model. This study evaluates the effectiveness of different model bias identification approaches based on Bayesian inference methods. This includes more classical approaches such as direct parameter estimation using MCMC in a Bayesian setup, as well as more recent proposals such as stat-FEM or orthogonal Gaussian Processes. Their potential use in digital twins, generalization capabilities, and computational cost is extensively analyzed. T2 - 5th ECCOMAS Thematic Conference on Uncertainty Quantificationin Computational Sciences and Engineering CY - Athen, Greece DA - 12.06.2023 KW - Model bias KW - Bayesian Uncertainty Quantification KW - Digital Twins KW - Gaussian Processes KW - Statistical Finite Element Method PY - 2023 UR - https://2023.uncecomp.org/ SP - 1 EP - 15 AN - OPUS4-58227 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -