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Der Einsatz von hochfesten niedriglegierten Stählen (HSLA) ist in vielen Industriesektoren, wie dem allgemeinen Bauwesen, Offshore Strukturen, Mobilkranbau usw. unumgänglich geworden. Die steigende Nachfrage an Stählen mit einer hohen Festigkeit und gleichzeitig hervorragenden Zähigkeit stellt ein ökonomisches und ökologisches Potential dieser Stähle in Vordergrund. Aktuell gültige Normvorgaben (EN ISO 10025-6) geben den Stahlherstellern Vorgaben bezüglich der chemischen Zusammensetzung, um die geforderten mechanischen Eigenschaften erreichen zu können. Die Legierungsrouten variieren jedoch von Hersteller zu Hersteller. In Betracht der Schweißeignung dieser Stähle zeigt sich das Problem, dass diese bereits bei geringen Nb- und Ti-Mikrolegierungsunterschieden im Grundwerkstoff ein divergentes metallurgisches Verhalten in der Wärmeeinflusszone (WEZ) aufweisen.
In diesem Vortrag werden die schweiß-metallurgischen Unterschiede zwischen verschieden mikrolegiertem hochfestem Feinkornbaustahl S690QL thematisiert. Zur Prüfung der Schweißnahtfestigkeit wurden mittels eines instrumentierten DIC (ARAMIS) Systems Querzugversuche an Schweiß-Querflachzugproben durchgeführt.
Due to the high damping mechanical properties of fiberboard materials, corrugated fiberboard boxes are widely used as transport packagings of dangerous goods. Since there is risk of vertical impact within the distribution system, drop tests are performed as design type tests to assess a package’s ability to withstand damage. In this context, however, little is known regarding the transient mechanical response of a filled fiberboard box. The reason is that the nature of the packaging material presents challenges in identifying the deformation mechanisms experimentally. The aim of this work is to provide a framework for predicting the damage resistance of complete, filled corrugated fiberboard boxes which are ready for transportation. Therein, drop test finite-element simulations are used and validated by experimental results. These numerical calculation models are a valuable tool for virtual product development and contribute to the optimization of the design cycle.
Zur Bewertung der Widerstandsfähigkeit von Schutzobjekten und Bauteilen gegen Explosionsbeanspruchung führt die Bundesanstalt für Materialforschung und -prüfung (BAM) regelmäßig Sprengversuche im Realmaßstab auf einem Testgelände durch.
Solche Versuche sind planungs- und ressourcenintensiv, sodass sie zunehmend durch numerische Simulationen ergänzt bzw. ersetzt werden.
Aktuelle Forschungsarbeiten zielen darauf ab, neue Berechnungsmethoden und Materialmodelle zu entwickeln, mit denen die Bestimmung der Bauteilantwort sowie die daraus resultierende Schädigung nach einem Explosionsereignis möglich sind.
Zur Validierung solcher Ansätze ist es notwendig, systematische Versuche mit unterschiedlichen Szenarien durchzuführen, bei denen die relevanten Parameter mit Hilfe verschiedener Messmethoden aufgezeichnet werden.
Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to realmeasurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducibleway such that other researcher can use this setup to validate their methodologies.
Numerical models built as virtual-twins of a real structure (digital-twins) are considered the future ofmonitoring systems. Their setup requires the estimation of unknown parameters, which are not directly measurable. Stochastic model identification is then essential, which can be computationally costly and even unfeasible when it comes to real applications. Efficient surrogate models, such as reduced-order method, can be used to overcome this limitation and provide real time model identification. Since their numerical accuracy influences the identification process, the optimal surrogate not only has to be computationally efficient, but also accurate with respect to the identified parameters. This work aims at automatically controlling the Proper Generalized Decomposition (PGD) surrogate’s numerical accuracy for parameter identification. For this purpose, a sequence of Bayesian model identification problems, in which the surrogate’s accuracy is iteratively increased, is solved with a variational Bayesian inference procedure. The effect of the numerical accuracy on the resulting posteriors probability density functions is analyzed through two metrics, the Bayes Factor (BF) and a criterion based on the Kullback-Leibler (KL) divergence. The approach is demonstrated by a simple test example and by two structural problems. The latter aims to identify spatially distributed damage, modeled with a PGD surrogate extended for log-normal random fields, in two different structures: a truss with synthetic data and a small, reinforced bridge with real measurement data. For all examples, the evolution of the KL-based and BF criteria for increased accuracy is shown and their convergence indicates when model refinement no longer affects the identification results.
High quality tubular products are essential to the oil and gas industry. Quality control during their production focuses on the non-destructive detection of surface defects. The structured light technique is a candidate for the challenge to detect, monitor and evaluate such defects in real-time.
In the present study the automatic processing of structured light measurements is performed and validated. The algorithm for the automatic Analysis of inspection data has an advantage over current data evaluation methods based on individual assessments of operators.
Bending beams and slabs are typical examples for structural elements used for reinforced concrete structures such as bridge girders, T-beams and bridge decks. Their strength related failure modes at maximum loading can be divided into bending and shear failure. The failure of beams loaded in bending can occur with or without indication. Therefore, conventional design concepts aim on failure modes with sufficient indication (e.g. large deflections or cracks), as it occurs in the case of secondary flexural compression failure. These indicating factors can also be used for Structural Health Monitoring (SHM) of civil infrastructure systems (e.g. bridges) to identify structural changes. In this context, non-destructive testing (NDT) methods offer different techniques for measuring deflections or crack formation and opening. However, profound knowledge on the determining failure modes of bending beams and their detection by NDT methods is required for the reliable application of SHM. Different NDT methods have been used in this study for analysing the load-bearing behaviour of a reinforced concrete beam in bending. The different measuring techniques are briefly described and their applicability is discussed by means of experimental results. For this purpose, the load-bearing behaviour of a reinforced concrete beam having a span of 2.75 m was investigated in a four-point bending flexural test at laboratory scale. The focus is on the characterization of determining failure modes by optical NDT and the comparison with classical measuring techniques (e.g. deformation measurements by displacement transducers). The bending beam was equipped with two single-mode (SM) sensor fibres. One fibre served as Distributed Optical Fibre Sensor (DOFS), whereas the other fibre contained Fibre Bragg Grating (FBG) sensors. In addition, optical deformation measurements using Digital Image Correlation (DIC) and Stereophotogrammetry (SP) were conducted.
The Measurement- and Model-based Structural Analysis (MeMoS) integrates a finite element model into least squares adjustment and thus allows to evaluate a mechanical model and measurements in a combined analysis. To examine the capability to detect and localise damage using this integrated analysis MeMoS, a small-scale truss bridge made of aluminium profiles is built as a test specimen for this purpose.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
Ausgehend vom sicherheitsbezogenen Aufgabenspektrum der BAM konzentriert sich das Poster auf die messtechnischen Verfahrensgrundlagen und Anwendungsbeispiele aus den Bereichen der experimentellen Bauartprüfung von RAM-Behältern in Fallprüfungen mit Wordt-Case-Szenarien, der Schadensanalyse und der Mitwirkung in F/E-Projekten