Filtern
Erscheinungsjahr
- 2020 (7) (entfernen)
Dokumenttyp
- Zeitschriftenartikel (2)
- Vortrag (2)
- Beitrag zu einem Tagungsband (1)
- Dissertation (1)
- Posterpräsentation (1)
Schlagworte
- Monitoring (7) (entfernen)
Organisationseinheit der BAM
Eingeladener Vortrag
- nein (2)
Polycarboxylate ethers (PCEs) are widely used in construction, but the exact nature of their interaction with cement is still debated. Aiming at a better understanding of the role of tricalcium Aluminate (C3A) in cement hydration, we assessed the potential of optical spectroscopy in combination with a water-soluble fluorescent organic reporter dye (S0586) to monitor the early hydration of C3A in the presence of 26 wt% CaSO4.2H2O (C3A26G-S) with and without PCE. As optical methods, steady-state fluorescence and diffuse reflectance (UV–VisDR) spectroscopy were employed. Phase characterization and particle size distribution were performed with in-situ X-ray diffraction (in-situ XRD) and dynamic light scattering (DLS). Our results show that fluorescence and UV–VisDR spectroscopy can be used to monitor the formation of metastable phases by the disaggregation of the dye S0586 in a cement paste as well as changes in ettringite formation. Addition of PCE slowed down the disaggregation of the dye as reflected by the corresponding changes of the dyes absorption and fluorescence. This prolonged induction period is a well-known side effect of PCEs and agrees with previous reported calorimetric studies and the Inhibition of gypsum dissolution observed by in-situ XRD. This demonstrates that fluorescence and UV–VisDR spectroscopy together with a suitable optical probe can provide deeper insights into the influence of PCE on C3A-gypsum hydration which could be e.g., utilized as screening method for comparing the influences
of different types of PCEs.
Recent years have seen extended use of ultrasonic techniques for concrete infrastructure assessement. They are applied for quality assurance and condition assessement at bridges, power plants, dams and other important objects. However, there are still a couple of significant limitations. They include, but are not limited to depth of penetration, imaging complex structures or early stage detections of distributed damage. The talk will give information on recent research in this area. Specifically, the application of the unique deep penetration system LAUS is shown. Ultrasonic monitoring using embedded transducers to check for subtle and sudden changes in the material is introduced as well. Comments on initiatives for validation, standardization and certification will be given.
The current practice of operating and maintaining deteriorating structural systems ensures acceptable levels of structural reliability, but it is not clear how efficient it is. Changing the current prescriptive approach to a risk-based approach has great potential to enable a more efficient management of such systems. Risk-based optimization of operation and maintenance strategies identifies the strategy that optimally balances the cost for controlling deterioration in a structural system with the achieved risk reduction. Inspections and monitoring are essential parts of operation and maintenance strategies. They are typically performed to reduce the uncertainty in the structural condition and inform decisions on future operation and maintenance actions. In risk-based optimization of operation and maintenance strategies, Bayesian updating is used to include information contained in inspection and monitoring data in the prediction of the structural reliability. All computations need to be repeated many times for different potential inspection and monitoring outcomes. This motivates the development of robust and efficient approaches to this computationally challenging task.
The reliability of deteriorating structural systems is time-variant because the loads on them and their capacities change with time. In most practical applications, the reliability analysis of deteriorating structural systems can be approached by dividing their lifetime into discrete time intervals. The time-variant reliability problem can then be represented by a series of time-invariant reliability problems. Using this methodology as a starting point, this thesis proposes a novel approach to compute the time-variant reliability of deteriorating structural systems for which inspection and monitoring data are available. The problem is formulated in a nested way in which the prediction of the structural condition is separated from the computation of the structural reliability conditional on the structural condition. Information on the structural condition provided by inspections and monitoring is included in the reliability assessment through Bayesian updating of the system deterioration model employed to predict the structural condition. The updated system reliability is obtained by coupling the updated deterioration model with a probabilistic structural model utilized to calculate the failure probability conditional on the structural condition. This approach is the first main outcome of this thesis and termed nested reliability analysis (NRA) approach. It is demonstrated in two numerical examples considering inspected and monitored steel structures subject to high-cycle fatigue.
An alternative – recently developed – approach, which also follows the strategy of discretizing time, describes deteriorating structural systems with hierarchical dynamic Bayesian networks (DBN). DBN combined with approximate or exact inference algorithms also enable the computation of the time-variant reliability of deteriorating structural systems conditional on information provided by inspection and monitoring data. In this thesis – as a proof of concept – a software prototype is developed based on the DBN approach, which can be used to assess the reliability of a corroding concrete box girder for which half-cell potential measurements are available. This is the second main outcome of this thesis.
Both approaches presented in this thesis enable an integral reliability analysis of inspected and monitored structures that accounts for system effects arising from (a) the correlation among deterioration states of different structural elements, (b) the interaction between element deterioration and system failure, and (c) the indirect information gained on the condition of all unobserved structural elements from inspecting or monitoring the condition of some structural elements. Thus, both approaches enable a systemwide risk-based optimization of operation and maintenance strategies for deteriorating structural systems.
The NRA approach can be implemented relatively easily with subset simulation, which is a sequential Monte Carlo method suitable for estimating rare event probabilities. Subset simulation is robust and considerably more efficient than crude Monte Carlo simulation. It is, however, still sampling-based and its efficiency is thus a function of the number of inspection and monitoring outcomes, as well as the value of the simulated event probabilities. The current implementation of the NRA approach performs separate subset simulation runs to estimate the reliability at different points in time. The efficiency of the NRA approach with subset simulation can be significantly improved by exploiting the fact that failure events in different years are nested. The lifetime reliability of deteriorating structural systems can thus be computed in reverse chronological order in a single subset simulation run.
The implementation of the DBN approach is much more demanding than the implementation of the NRA approach but it has two main advantages. Firstly, the graphical format of the DBN facilitates the presentation of the model and the underlying assumptions to stakeholders who are not experts in reliability analysis. Secondly, it can be combined with exact inference algorithms. In this case, its efficiency neither depends on the number of inspection and monitoring outcomes, nor on the value of the event probabilities to be calculated. However, in contrast to the NRA approach with subset simulation, the DBN approach with exact inference imposes restrictions on the number of random variables and the dependence structure that can be implemented in the model.
Die Überwachung von Bauteilen aus Stahl- oder Spannbeton mit Ultraschall hat in Labor- und Technikumsversuchen schon vielversprechende Ergebnisse gezeigt. Besonders gute Resultate wurden dabei mit eingebetteten Ultraschalltrans-ducern und bei Auswertung der Daten mit der hochsensiblen Codawelleninterferometrie erzielt. Erfasst werden können neben Temperatur- und Feuchteeffekten auch Belastungszustände und jegliche Art von Schädigung, die mit Mikro- oder Makrorissbildung einhergeht.
Seit 2019 untersucht die DFG-Forschergruppe 2825 „CoDA“ (Sprecher: Prof. Christoph Gehlen, TU München) ver-schiedenste Aspekte dieser innovativen Technologie mit dem Ziel, Einflussgrößen quantitativ zu erfassen, Umweltein-flüsse zu korrigieren und 3D-Auswerteverfahren zu verbessern. Final soll eine am Bauwerk einsatzfähige Methode ent-stehen, die klassische Monitoringverfahren ergänzt und erweitert sowie Input zu einem Update des statischen Systems liefert.
Aufgaben der BAM in der Forschergruppe ist neben Verbesserung und Adaptierung der Messsystem und Sensorik auch Langzeitversuche an einem Großobjekt und Testinstallationen an Realbauwerken. Hierzu liegen erste Ergebnisse vor, die zeigen, dass die Technologie auch außerhalb des Labors einsatzfähig ist.
Die Überwachung von Bauteilen aus Stahl- oder Spannbeton mit Ultraschall hat in Labor- und Technikumsversuchen schon vielversprechende Ergebnisse gezeigt. Besonders gute Resultate wurden dabei mit eingebetteten Ultraschalltrans-ducern und bei Auswertung der Daten mit der hochsensiblen Codawelleninterferometrie erzielt. Erfasst werden können neben Temperatur- und Feuchteeffekten auch Belastungszustände und jegliche Art von Schädigung, die mit Mikro- oder Makrorissbildung einhergeht.
Seit 2019 untersucht die DFG-Forschergruppe 2825 „CoDA“ (Sprecher: Prof. Christoph Gehlen, TU München) ver-schiedenste Aspekte dieser innovativen Technologie mit dem Ziel, Einflussgrößen quantitativ zu erfassen, Umweltein-flüsse zu korrigieren und 3D-Auswerteverfahren zu verbessern. Final soll eine am Bauwerk einsatzfähige Methode ent-stehen, die klassische Monitoringverfahren ergänzt und erweitert sowie Input zu einem Update des statischen Systems liefert.
Aufgaben der BAM in der Forschergruppe ist neben Verbesserung und Adaptierung der Messsystem und Sensorik auch Langzeitversuche an einem Großobjekt und Testinstallationen an Realbauwerken. Hierzu liegen erste Ergebnisse vor, die zeigen, dass die Technologie auch außerhalb des Labors einsatzfähig ist.
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.