Ingenieurbau
Filtern
Erscheinungsjahr
- 2023 (316) (entfernen)
Dokumenttyp
- Vortrag (144)
- Zeitschriftenartikel (74)
- Beitrag zu einem Tagungsband (47)
- Posterpräsentation (26)
- Forschungsbericht (7)
- Forschungsdatensatz (6)
- Buchkapitel (3)
- Beitrag zu einem Sammelband (3)
- Tagungsband (Herausgeberschaft für den kompletten Band) (2)
- Sonstiges (2)
- Dissertation (1)
- Handbuch (1)
Sprache
- Englisch (207)
- Deutsch (107)
- Französisch (1)
- Mehrsprachig (1)
Schlagworte
- Korrosion (22)
- Corrosion (12)
- Concrete (11)
- Wasserstoff (11)
- Hydrogen (10)
- Structural health monitoring (10)
- Fire (9)
- Flame retardancy (9)
- Potentialfeldmessung (9)
- LH2 (8)
Organisationseinheit der BAM
- 7 Bauwerkssicherheit (187)
- 8 Zerstörungsfreie Prüfung (65)
- 7.6 Korrosion und Korrosionsschutz (42)
- 2 Prozess- und Anlagensicherheit (39)
- 7.2 Ingenieurbau (39)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (37)
- 3 Gefahrgutumschließungen; Energiespeicher (33)
- 7.5 Technische Eigenschaften von Polymerwerkstoffen (32)
- 7.4 Baustofftechnologie (30)
- 2.1 Sicherheit von Energieträgern (26)
Paper des Monats
- ja (9)
In recent years, the use of simulation-based digital twins for monitoring and assessment of complex mechanical systems has greatly expanded. Their potential to increase the information obtained from limited data makes them an invaluable tool for a broad range of real-world applications. Nonetheless, there usually exists a discrepancy between the predicted response and the measurements of the system once built. One of the main contributors to this difference in addition to miscalibrated model parameters is the model error. Quantifying this socalled model bias (as well as proper values for the model parameters) is critical for the reliable performance of digital twins. Model bias identification is ultimately an inverse problem where information from measurements is used to update the original model. Bayesian formulations can tackle this task. Including the model bias as a parameter to be inferred enables the use of a Bayesian framework to obtain a probability distribution that represents the uncertainty between the measurements and the model. Simultaneously, this procedure can be combined with a classic parameter updating scheme to account for the trainable parameters in the original model.
This study evaluates the effectiveness of different model bias identification approaches based on Bayesian inference methods. This includes more classical approaches such as direct parameter estimation using MCMC in a Bayesian setup, as well as more recent proposals such as stat-FEM or orthogonal Gaussian Processes. Their potential use in digital twins, generalization capabilities, and computational cost is extensively analyzed.
In recent years, the use of simulation-based digital twins for monitoring and assessment of complex mechanical systems has greatly expanded. Their potential to increase the information obtained from limited data makes them an invaluable tool for a broad range of real-world applications. Nonetheless, there usually exists a discrepancy between the predicted response and the measurements of the system once built. One of the main contributors to this difference in addition to miscalibrated model parameters is the model error. Quantifying this socalled model bias (as well as proper values for the model parameters) is critical for the reliable performance of digital twins. Model bias identification is ultimately an inverse problem where information from measurements is used to update the original model. Bayesian formulations can tackle this task. Including the model bias as a parameter to be inferred enables the use of a Bayesian framework to obtain a probability distribution that represents the uncertainty between the measurements and the model. Simultaneously, this procedure can be combined with a classic parameter updating scheme to account for the trainable parameters in the original model. This study evaluates the effectiveness of different model bias identification approaches based on Bayesian inference methods. This includes more classical approaches such as direct parameter estimation using MCMC in a Bayesian setup, as well as more recent proposals such as stat- FEM or orthogonal Gaussian Processes. Their potential use in digital twins, generalization capabilities, and computational cost is extensively analyzed.
A safety or security related assessment of explosions, accidental and intentional scenarios alike, often necessitate performance of replication-tests. Such test results are necessary to clarify the causes within the scope of forensic investigations. To gain important insights into the behavior of structures and materials under such loading, field tests may also be performed in accordance with different test standards. To determine the resistance of building-structures after explosions, estimation of the residual load-bearing capacity in addition to the assessment of dynamic structural response and damage to the building components is important. In most cases an evaluation of structural integrity is based only on the visual damage, resulting in an overestimation of the residual capacity.
The Bundesanstalt für Materialforschung und -prüfung (BAM) operates the Test site for Technical Safety (TTS) on an area measuring about 12 km2 in the Federal State of Brandenburg for execution of true-to-scale explosion tests. At the TTS, building component testing was performed to assess the suitability of different non-destructive testing methods to characterize the dynamic structural response and damage resulting from the detonation of high explosives.
Different blast-loading scenarios were realized by varying the net explosive mass and the standoff distance with all scenarios representing a near-field detonation. The test object was a reinforced concrete wall 2 m high, 2.5 m wide and 20 cm thick, fixed at both vertical edges. The dynamic loading of the wall was characterized with 8 piezoelectric pressure sensors flush-mounted on the front surface, thus measuring the reflected pressures from the shock wave. The tests were conducted with the aim of characterizing the global behavior of the wall under dynamic shock loading and the resulting local damage pattern, respectively. High speed digital image correlation was implemented in combination with multiple acceleration sensors to observe the rear surface of the wall to chart the dynamic deflection during the loading and to determine the residual deformation after the loading had ceased. In addition, one test specimen was instrumented with fiber optic sensor cables, both fixed to the rebars and embedded in the concrete-matrix, respectively. Firstly, these sensors were interrogated during the blast test by a distributed acoustic sensing (DAS) device using a particularly high sampling rate to measure the shock-induced vibrations in the structure with high temporal resolution. This delivers information on dynamics of compression and tension cycles from within the structure. Secondly, the local damage-pattern emerging during the series of blasts was determined via distributed fiber optic strain sensing (DSS) by interrogating the embedded fiber optic sensors with a high spatial resolution DSS device after each blast. This enabled the characterization of non-visual damage to the structure, in particular with regard to the formation of localized cracks in the concrete matrix. The DSS was further complimented by a structure-scanner based on ultrasonic measurements.
Our contribution describes this new test approach in detail. Results of the three datasets, namely dynamic shock loading, global behavior of the test object and the local damage pattern will be presented. The suitability of the implemented measurement methods will be discussed in combination with the challenges in their application for technical safety evaluation of building components under explosive loading.
Blast tests are indispensable for investigations of accidental or intentional explosions and to evaluate the level of protection to people and equipment within critical infrastructure. Current capabilities for detailed blast effects assessment are limited to performing full-scale field testing, which, for complex scenarios, are highly resource intensive. In this regard, reliable numerical simulations are an effective alternative option. A discussion of the scope and challenges of using numerical tools for a technical-safety assessment of reinforced concrete structures under blast loading is presented. Different coupling possibilities between shock wave simulations and structural simulations with the help of practical examples is given. An outlook on the development of new methods for structural simulations currently being researched at BAM concludes the presentation.
Steelmaking slag is a by-product of steel production, of which 4.5 Mt were produced in 2020 in Germany alone. It is mainly used in road construction, earthwork and hydraulic engineering. A smaller part is returned to the metallurgical cycle, used as fertiliser or landfilled.
With this use, iron oxides still contained in steelmaking slag are lost. In addition, the possibility of producing higher-grade products from steelmaking slag is foregone. In recent decades, many researchers have investigated the production of Portland cement clinker and crude iron from basic oxygen furnace slags (BOFS) via a reductive treatment. Carbothermal treatment of liquid BOFS causes a reduction of iron oxides to metallic iron, which separates from the mineral phase due to its higher density. Simultaneously, the chemical composition of the reduced slag is adapted to that of Portland cement clinker.
In this study, German BOFS was reduced in a small-scale electric arc furnace using petrol coke as a reducing agent. The resulting low-iron mineral product has a similar chemical composition to Portland cement clinker and was rich in the tricalcium silicate solid solution alite (Ca3SiO5). Based on its chemical and mineralogical composition, similar to that of Portland cement clinker, the reduced BOFS has the potential to react comparably. In our study, the reduced BOFS produced less hydration heat than OPC, and its hydraulic reaction was delayed. However, adding gypsum has shown to accelerate the hydration rate of the reduced BOFS compared to that known from the calcium silicates of Portland cement clinker.
Further research to improve the hydraulic properties of the reduced slag is essential. If successful, producing a hydraulic binder and crude iron from BOFS has economic and ecological benefits for both the cement and steel industries.
Durch das alkalische Milieu des Porenwassers im Beton ist der Stahl normalerweise dauerhaft vor Korrosion geschützt. Unter ungünstigen Umgebungsbedingungen (Chlorideintrag, Karbonatisierung) kann die passive Deckschicht auf der Stahloberfläche zerstört werden. Der Korrosionsprozess ist initiiert. Die entstehenden Korrosionsprodukte werden zunächst vom Porengefüge des Betons aufgenommen, ohne dass es zu sichtbaren Schäden am Bauwerk führt. Im fortgeschrittenem Stadium der Korrosion können sich dann Risse und Abplatzungen bilden.
Um notwendige Sanierungsmaßnahmen sowohl aus sicherheitstechnischen Gründen als auch aus wirtschaftlichen Erwägungen rechtzeitig einzuleiten, sind frühzeitige und weitestgehend zerstörungsfreie Prüfverfahren zur Ermittlung der aktuellen Korrosionswahrscheinlichkeit der Stahlbewehrung von großer Bedeutung. Deshalb finden Methoden und Verfahren zur laufenden bzw. regelmäßigen Korrosionsüberwachung von Stahlbetonbauwerken ständig größere Beachtung, sowohl im Bereich Forschung und Entwicklung als auch in der Praxis. Die elektrochemische Potentialfeldmessung ist ein etabliertes und weit verbreitetes Verfahren zur Beurteilung des Korrosionszustandes der Bewehrung in Stahlbetonbauwerken. Mit Hilfe dieses Verfahrens können Bereiche korrodierender Bewehrung zerstörungsfrei lokalisiert werden. In der Regel kommt diese Methode bei der Detektion von chloridinduzierter Korrosion zum Einsatz.
Der Lehrgang vermittelt den Teilnehmenden in kompakter Form einen zusammenfassenden Überblick über die notwendigen Grundlagen zum Verständnis der Messmethode, der Vorbereitung und Durchführung der Messungen, der notwendigen Begleituntersuchungen sowie der Interpretation der gewonnenen Daten. Der erste Tag ist der theoretischen Ausbildung gewidmet, am zweiten Tag folgt dann die praktische Anwendung der Lerninhalte. Am dritten Tag folgt die Abnahme der praktischen und theoretischen Prüfung zur Erlangung des Sachkundenachweises.