TY - JOUR A1 - Herrmann, Ralf T1 - Digitalisierung sichert die Bauwerke von gestern und das Wissen von morgen N2 - Die moderne Gesellschaft in Deutschland und Europa profitiert von der hervorragenden baulichen Infrastruktur, die für uns viele Aspekte aus den Bereichen Mobilität, Energieversorgung, Transport, Umweltschutz, (Nah-)Erholung und Gefahrenabwehr zur Alltäglichkeit werden lassen und uns ein hohes Gefühl der technischen Sicherheit vermitteln. Viele der Annehmlichkeiten, wie beispielweise ein Hochgeschwindigkeitseisenbahnverkehrsnetz, zuverlässige Stromversorgung im europäischen Verbundsystem und ein immenser Personen-, Güter- und Warenverkehr auf der Straße, zu Wasser und in der Luft ist ohne eine leistungsfähige, resiliente und zuverlässige bauliche Infrastruktur undenkbar. KW - Bauwerksmonitoring KW - Bauwerksdiagnostik KW - Digitalisierung PY - 2022 DO - https://doi.org/10.1002/bate.202270303 SN - 1437-0999 SN - 0932-8351 VL - 99 IS - 3 SP - 161 EP - 162 PB - Ernst & Sohn GmbH CY - Berlin AN - OPUS4-54557 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Recknagel, Christoph A1 - Hoppe, Johannes A1 - Eilers, M. T1 - Technische Lieferbedingungen für die Dichtungsschicht aus einer Polymerbitumen-Schweißbahn zur Herstellung von Brückenbelägen auf Beton TL/TP-ING - Teil 7: Brückenbeläge, Abschnitt 1 N2 - In den "Technischen Lieferbedingungen für die Dichtungsschicht aus einer Polymerbitumen-Schweißbahn zur Herstellung von Brückenbelägen auf Beton" (TL BEL-B 1) sind die Regelungen über die erforderlichen Voraussetzungen zur Verwendung von Polymerbitumen-Schweißbahnen zur Ausbildung einer Dichtungsschicht aus einer einlagigen Polymerbitumen-Schweißbahn auf Beton aufgeführt. Sie umfassen den grundsätzlichen Nachweis der Funktionsfähigkeit und Dauerhaftigkeit sowie die Sicherstellung des nachgewiesenen Qualitätsniveaus. KW - Brückenbeläge KW - Asphaltbauweise KW - PmB Schweißbahn KW - Technische Anforderungen PY - 2022 SN - 978-3-86446-325-9 VL - 783/1 SP - 1 EP - 8 PB - FGSV Verlag GmbH CY - Köln AN - OPUS4-54853 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Unger, Jörg F. T1 - Combining Data and Simulation Models in real time - A Digital Twin for Bridge monitoring N2 - Im Rahmen des Vortrages wurde das Konzept eines digitalen Zwillings vorgestellt und an verschiedenen Beispielen angefangen von einem Laborversuch über Kleinversuche bis zum Realmaßstab dargestellt. N2 - During the lecture, the concept of a digital twin was presented and illustrated with various examples starting from a laboratory experiment to small-scale and real-scale experiments. T2 - EURAD Second Annual Event (2022) CY - Online meeting DA - 28.03.2022 KW - Digital Twin KW - Bridge Monitoring KW - Simulation Models PY - 2022 UR - https://igdtp.eu/event/eurad-annual-event-2/ AN - OPUS4-54639 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Titscher, Thomas T1 - Model calibration and damage detection for a digital twin N2 - Numerical models are an essential tool in predicting and monitoring the behavior of civil structures. Inferring the model parameters is a challenging tasks as they are often measured indirectly and are affected by uncertainties. Digital twins couple those models with real-world data and can introduce additional, systematic sensor uncertainties related to the sensor calibration, i.e. uncertain offsets and calibration factors. In this work, the challenges of data processing, parameter identification, model selection and damage detection are explored using a lab-scale cable stayed bridge demonstrator. By combining force measurements in the cables with displacement measurements from both laser and stereo-photogrammetry systems, the elastic parameters of a three-dimensional finite element beam model are inferred. Depending on the number of sensors and the number of datasets used, parametrizing the sensor offsets and factors, leads to model with over 100 parameters. With a real-time solution of the problem in mind, a highly efficient analytical variational Bayesian approach is used to solve it within seconds. An analysis of the required assumptions and limitations of the approach, especially w.r.t. to the computed evidence, is provided by a comparison with dynamic nested sampling in a simplified problem. Finally, by inferring the value of additional damage parameters along the bridge, the method is successfully used to detect the location of an artificially introduced weak spot in the demonstrator bridge. T2 - ECCOMAS 2022 CY - Oslo, Norway DA - 05.06.2022 KW - Bayesian identification KW - Digital twin KW - Variational Bayesian KW - Damage detection PY - 2022 AN - OPUS4-55083 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Diercks, Philipp T1 - Multiscale modeling of heterogeneous structures based on a localized model order reduction approach N2 - Many of today’s problems in engineering demand reliable and accurate prediction of failure mechanisms of mechanical structures. Herein, it is necessary to take into account the heterogeneous structure on the lower scale, to capture the underlying physical phenomena. However, this poses a great challenge to the numerical solution as the computational cost is significantly increased by resolving the lower scale in the model. Moreover, in applications where scale separation as the basis of classical homogenization schemes does not hold, the influence of the lower scale on the upper scale has to be modelled directly. This work aims to develop an efficient concurrent methodology to model heterogeneous structures combining the variational multiscale method (VMM) [1] and model order reduction techniques (e. g. [2]). First, the influence of the lower scale on the upper scale can be taken into account following the additive split of the displacement field as in the VMM. Here, also a decomposition of the global domain into subdomains, each containing a fine grid discretization of the lower scale, is introduced. Second, reduced approximation spaces for the upper and lower scale solution are constructed by exploring possible solutions for each subdomain based on a representative unit cell. The local reduced spaces are designed such that local contributions of each subdomain can be coupled in a conforming way. Thus, the resulting global system is sparse and reduced in size compared to the direct numerical simulation, leading to a faster solution of the problem. The authors gratefully acknowledge financial support by the German Research Foundation (DFG), project number 394350870, and by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC Grant agreement No. 818473). T2 - The 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) 2022 CY - Oslo, Norway DA - 05.06.2022 KW - Multiscale methods KW - Variational multiscale method KW - Domain decomposition KW - Model order reduction PY - 2022 AN - OPUS4-55117 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Tamsen, Erik T1 - Towards an automatic optimization framework for performance oriented precast concrete design N2 - Concrete has a long history in the construction industry and is currently one of the most widely used building materials. Especially precast concrete elements are frequently utilized in construction projects for standardized applications, increasing the quality of the composite material, as well as reducing the required building time. Despite the accumulated knowledge, continuous research and development in this field is essential due to the complexity of the composite combined with the ever-growing number of applications and requirements. Especially in view of global climate change, design aspects as CO2 emissions and resource efficiency require new mix designs and optimization strategies. A result of the material’s high complexity and heterogeneity on multiple scales is that utilizing the full potential with changing demands is highly challenging, even for the established industry. We propose a framework based on an ontology, which automatically combines experimental data with numerical simulations. This not only simplifies experimental knowledge transfer, but allows the model calibration and the resulting simulation predictions to be reproducible and interpretable. This research shows a way towards a more performance oriented material design. Within this talk we present our workflow for an automated simulation of a precast element, demonstrating the interaction of the ontology and the finite element simulation. We show the automatic calibration of our early-age concrete model [1, 2], to improve the prediction of the optimal time for the removal of the form work. T2 - The 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) 2022 CY - Oslo, Norway DA - 05.06.2022 KW - Performance oriented concrete design KW - Early-age concrete KW - Precast concrete KW - Ontology KW - Optimization workflow PY - 2022 AN - OPUS4-55302 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias A1 - El-Athman, Rukeia T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 SN - 978-1-032-35623-5 SN - 978-1-003-32264-1 DO - https://doi.org/10.1201/9781003322641-127 SP - 1061 EP - 1068 PB - CRC Press CY - Boca Raton AN - OPUS4-55493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Herrmann, Ralf T1 - Structural Health Monitoring am Großen Fallturm der BAM N2 - In diesem Beitrag wird die Structural Health Monitoring Kampagne am Großen Fallturm der BAM vorgestellt. T2 - Seminar "Zerstörungsfreie Prüfung" CY - Online meeting DA - 13.01.2022 KW - Belastungsversuch KW - Großer Fallturm Horstwalde KW - Schwingungsdynamik KW - Modalanalyse PY - 2022 AN - OPUS4-55478 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Nerger, Deborah A1 - Moosavi, Robabeh A1 - Grunwald, Marcel T1 - Discussion on data evaluation of tomographic and numerical results N2 - The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation. T2 - 26th International Conference on Structural Mechanics in Reactor Technology CY - Potsdam, Germany DA - 10.07.2022 KW - Impact damage on reinforced concrete KW - Tomographic damage evaluation KW - Numerical damage simulation PY - 2022 SP - 1 EP - 8 AN - OPUS4-55474 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk T1 - Discussion on data evaluation of tomographic and numerical results N2 - The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation. T2 - 26th International Conference on Structural Mechanics in Reactor Technology CY - Potsdam, Germany DA - 10.07.2022 KW - Impact damage of reinforced concrete KW - Tomographic damage evaluation KW - Numerical simulation of impact damage PY - 2022 AN - OPUS4-55476 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -