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Kurzfassung: Textilbewehrter Carbonbeton wird derzeit in vielen Bereichen der Bauindustrie als Hochleistungsverbundwerkstoff eingesetzt. Der Verbundwerkstoff besteht aus Beton und einer nicht‐metallischen Bewehrung aus Carbonfasern in Stab‐ oder Gitterform. Der innovative Werkstoff hat neben vielversprechenden Materialeigenschaften wie Zugverhalten und der Dichte auch eine hohe elektrische Leitfähigkeit. Die letztgenannte Eigenschaft kann genutzt werden, um Wärme im Bauteil zu erzeugen und dadurch z.B. im Verbundwerkstoff den Hydratationsprozess des Betons zu beschleunigen. Zur Verwendung der elektrisch leitenden textilen Carbonbewehrung wurden baustellentaugliche Kontaktierungsverfahren für unterschiedliche Tränkungsmaterialien entwickelt und bewertet, sowie die elektrischen Eigenschaften wie Leistung und Carbonwiderstand der verwendeten Carbonbewehrungen bestimmt. Darauf aufbauend wurde die Temperaturverteilung der Bewehrungen in Abhängigkeit unterschiedlicher Stromflüsse untersucht. Die Untersuchungen ermöglichten die Quantifizierung und Charakterisierung des Einflusses des Tränkungsmaterials sowie der Geometrie des Faserstranges auf die Strom‐ und Temperaturverteilungen. [ABSTRACT FROM AUTHOR]

Prediction of the bridge temperature using monitoring data and machine learning In this paper, the nonlinear or rather transient relationship between the air temperature and the building temperature is simulated by a machine learning model. Based on this modelling, different use cases for the application of machine learning regression methods to monitoring data are presented, which resulted from practical questions. Basic knowledge of neural networks will be given and for the calculations, long‐term monitoring data of valley bridges from VDE 8 are used. It is shown, for example, that these methods can be used to detect and compensate measurement errors or to predict the behaviour of structures. The results show that these methods, have a great potential for the evaluation of large amounts of data since no physical models are required. The paper focuses more on the application of AI methods rather than on the mathematical or theoretical background of the methods. [ABSTRACT FROM AUTHOR]

Facing concrete shells of sandwich walls under thermal loads Within the framework of a research project funded by the Zukunft Bau research initiative of the Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB), the Chair of Concrete and Masonry Structures of the Technical University of Munich (TUM) performs extensive thermal investigations on precast concrete sandwich wall panels with different facing shells taking in to account numerous boundary conditions. So far, building facades made of precast concrete sandwich panels are mainly realized by utilizing reinforced concrete members with a facing shell thickness of about 70 to 100 mm. Among other things, the thickness results from the required concrete cover to protect the reinforcing steel against corrosion permantly. By applying recent developments such as e.g. textile reinforcement and high performance concrete it is possible to build versatile facing shells, which thanks to the corrosion‐resistant textile reinforcement and the achievable high strength may be designed with a reduced shell thickness of about 20 to 30 mm. With respect to this perspective, the aim of the above mentioned research project is to both numerically and experimentally derive realistic temperature values and gradients and provide an appropriate design approach for engineering practice. Hereby, in addition to various numerical analyses, the main focus is laid on the development of a full‐scale in‐situ test setup and the investigation of the actual temperature behavior of large facing shells with a thickness of 30 and 80 mm respectively over one entire weather period (365 days). Complementary laboratory investigations by means of a project‐specifically developed multifunctional climate chamber (simulation of different weather scenarios) conclude the research project. [ABSTRACT FROM AUTHOR]