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Additive manufacturing of concrete structures is a novel and emerging technology. Freecontouring in civil engineering, which allows for entirely new designs, is a significant advantage. Inthe future, lower construction costs are expected with increased construction speeds and decreasingrequired materials and workers. However, architects and civil engineers rely on a certain quality ofexecution to fulfil construction standards. Although several techniques and approaches demonstratethe advantages, quality control during printing is highly challenging and rarely applied. Due to thecontinuous mixing process commonly used in 3D concrete printing, it is impossible to exclude varia-tions in the dry mixture or water content, and a test sample cannot be taken as a representative samplefor the whole structure. Although mortar properties vary only locally, a defect in one layer duringprinting could affect the entire integrity of the whole structure . Therefore, real-time process monitor-ing is required to record and document the printing process.At the Bundesanstalt für Materialforschung und -prüfung (BAM) a new test rig for the additive man-ufacturing of concrete is built. The primary purpose is measuring and monitoring the properties of amortar during the printing process.The following study investigates an approach for calculating yield stress and plastic viscosity based onexperimentally recorded pressure data. The calculations assume that fresh mortar behaves as a Bing-ham fluid and that the Buckingham-Reiner-equation is applicable. A test setup consisting of rigid pipeswith integrated pressure sensors at different positions is utilized.Monitoring the printing process with different sensors is crucial for the quality control of an ongoingprocess.
Corrosion monitoring of reinforced concrete structures:The DGZfP specification B12 Collaboration
(2023)
Corrosion monitoring of reinforced or prestressed concrete structures has becomeincreasingly important in recent years. Areas of application include componentsthat are no longer accessible after completion or where potential fieldmeasurements cannot be carried out due to existing coatings. Corrosion monitoringcan also be used to monitor the progress of corrosion in corroding systems, e.g. toprove the success of repair measures according to repair principle 8 in accordancewith EN 1504‐9 or repair method 8.3 in accordance with the DIBt repair guideline.It also could be used to prove the functionality of cathodic corrosion protectionsystems in accordance with ISO 12696. Despite the increasing importance ofcorrosion monitoring, no guidelines orrecommendations existed until 2018. Thisgap was closed by the English version of specification B12,“Corrosion Monitoringof Reinforced and Prestressed Concrete Structures,”of the German Society for Non‐Destructive Testing, which was published in 2021. This article introducesspecification B12 by explaining the basicmeasurement principles and illustratingthe potential of corrosion monitoring in new and existing buildings.
Monitoring 4.0/5.0
(2021)
Mehr als 10 % des deutschen Bruttoinlandsprodukts werden für Investitionen imBausektor eingesetzt. Die unmittelbar folgende Erkenntnis, dass eine zukunftsorientierte, nachhaltige Umgestaltung unserer Gesellschaft nicht ohne einen substanziellen Beitrag des Bausektors gelingen kann, hat sich mittlerweile weitgehend durchgesetzt. Die Komplexität der zugehörigen technischen Herausforderungen ist jedoch nicht zu unterschätzen.
Reliability analysis of deteriorating structural systems requires the solution of time-variant reliability problems.
In the general case, both the capacity of and the loads on the structure vary with time. This analysis can be approached by approximation through a series of time-invariant reliability problems, which is a potentially effective strategy for cases where direct solutions of the time-variant reliability problem are challenging, e.g. for structural systems with many elements or arbitrary load processes. In this contribution, we thoroughly Review the formulation of the equivalent time-invariant reliability problems and extend this approximation to structures for which inspection and monitoring data is available. Thereafter, we present methods for efficiently evaluating the reliability over time. In particular, we propose the combination of sampling-based methods with a FORM (first-order reliability method) approximation of the series system reliability problem that arises in the computation of the lifetime reliability. The framework and algorithms are demonstrated on a set of numerical examples, which include the computation of the reliability conditional on inspection data.
Korrosionsmonitoring von Stahl- oder Spannbetonbauwerken hat in den vergangenen Jahren als Ergänzung zur herkömmlichen Bauwerksuntersuchung deutlich an Relevanz gewonnen. Einsatzgebiete sind z. B. Bauteile, die nach Fertigstellung nicht mehr zugänglich sind oder an denen aufgrund vorhandener Beschichtungen keine Potentialfeldmessungen durchgeführt werden können. Weiterhin kann Korrosionsmonitoring auch für die Überwachung des Korrosionsfortschritts an korrodierenden Systemen z. B. zum Nachweis des Instandsetzungserfolgs bei Anwendung des Prinzips W-Cl gemäß Instandsetzungsrichtlinie des DAfStb oder zum Funktionsnachweis bei KKS-Installationen nach DIN EN ISO 12696 eingesetzt werden. Trotz zunehmender Bedeutung Existieren für das Korrosionsmonitoring bis dato keine Richtlinien oder Handlungsempfehlungen. Diese Lücke soll das Merkblatt B12 „Korrosionsmonitoring von Stahl- und Spannbetonbauwerken“ der Deutschen Gesellschaft für
zerstörungsfreie Prüfung DGZfP füllen, das im Frühjahr 2018
veröffentlicht wurde. In diesem Beitrag werden das Merkblatt B12 vorgestellt, die grundlegenden Messprinzipien erläutert und anhand von Anwendungsbeispielen das Potenzial von Korrosionsmonitoring bei Neubau- und Bestandsobjekten illustriert.
This article introduces an approach and framework for the quantification of the value of structural health monitoring (SHM) in the context of the structural risk and integrity management for systems. The quantification of the value of SHM builds upon the Bayesian decision and utility theory, which facilitates the assessment of the value of information associated with SHM. The principal approach for the quantification of the value of SHM is formulated by modeling the fundamental decision of performing SHM or not in conjunction with their expected utilities. The expected utilities are calculated accounting for the probabilistic performance of a system in conjunction with the associated structural integrity and risk management actions throughout the life cycle, the associated benefits, structural risks, and costs and when performing SHM, the SHM information, their probabilistic outcomes, and costs. The calculation of the expected utilities necessitates a comprehensive and rigorous modeling, which is introduced close to the original formulations and for which analysis characteristics and simplifications are described and derived. The framework provides the basis for the optimization of the structural risk and integrity management based on utility gains including or excluding SHM and inspection information. Studies of fatigue deteriorating structural Systems and their characteristics (1) provide decision Support for the performance of SHM, (2) explicate the influence of the structural component and system characteristics on the value of SHM, and (3) demonstrate how an integral optimization of SHM and inspection strategies for an efficient structural risk and integrity management can be performed.