TY - JOUR A1 - Andrés Arcones, Daniel A1 - Weiser, M. A1 - Koutsourelakis, F. A1 - Unger, Jörg F. T1 - A Bayesian Framework for Simulation-based Digital Twins of Bridges JF - ce/papers Proceedings in civil engineering N2 - Simulation-based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditional inspection and monitoring data. By incorporating virtual sensors and predictive maintenance strategies, they have the potential to improve our understanding of the behavior and performance of bridges over time. However, as bridges age and undergo regular loading and extreme events, their tructural characteristics change, often differing from the predictions of their initial design. Digital twins must be continuously adapted to reflect these changes. In this article, we present a Bayesian framework for updating simulation-based digital twins in the context of bridges. Our approach integrates information from measurements to account for inaccuracies in the simulation model and quantify uncertainties. Through its implementation and assessment, this work demonstrates the potential for digital twins to provide a reliable and up-to-date representation of bridge behavior, helping to inform decision-making for maintenance and management. T2 - Eurostruct 2023 CY - Vienna, Austria DA - 25.09.2023 KW - Digital Twins KW - Bayesian Inference KW - Bridge Monitoring KW - Uncertainty Quantification PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586803 UR - https://eurostruct.org/eurostruct-2023/ DO - https://doi.org/10.1002/cepa.2177 SN - 2509-7075 VL - 6 IS - 5 SP - 734 EP - 740 PB - Ernst & Sohn CY - Berlin AN - OPUS4-58680 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Maiwald, Michael T1 - Integrated and Networked Systems and Processes—A Perspective for Digital Transformation in Thermal Process Engineering JF - ChemEngineering N2 - Separation technology as a sub-discipline of thermal process engineering is one of the most critical steps in the production of chemicals, essential for the quality of intermediate and end products. The discipline comprises the construction of facilities that convert raw materials into value-added products along the value chain. Conversions typically take place in repeated reaction and separation steps—either in batch or continuous processes. The end products are the result of several production and separation steps that are not only sequentially linked, but also include the treatment of unused raw materials, by-products and wastes. Production processes in the process industry are particularly susceptible to fluctuations in raw materials and other influences affecting product quality. This is a challenge, despite increasing fluctuations, to deliver targeted quality and simultaneously meet the increasing dynamics of the market, at least for high value fine chemicals. In order to survive successfully in a changed environment, chemical companies must tread new paths. This includes the potential of digital technologies. The full integration and intelligent networking of systems and processes is progressing hesitantly. This contribution aims to encourage a more holistic approach to the digitalization in thermal process engineering by introduction of integrated and networked systems and processes. KW - Smarter Sensor KW - Digitalisation KW - Digital transformation KW - Process Industry KW - Thermal Process Engineering KW - Digital Twins PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-504964 DO - https://doi.org/10.3390/chemengineering4010015 SN - 2305-7084 VL - 4 IS - 15 SP - 1 EP - 9 PB - MDPI CY - Basel AN - OPUS4-50496 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -