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Eingeladener Vortrag
- nein (1)
Der vorliegende Bericht beschreibt Konzepte für eine intelligente Brücke auf der Grundlage einer zuverlässigkeitsbasierten Zustandsbewertung unter Berücksichtigung von Bauwerksinformationen, welche aus Prüfungen, Inspektionen und Überwachung gewonnen werden. Das Brückensystem wird durch ein Modell beschrieben, welches den zentralen Teil des Konzeptes darstellt. Das Modell wird in Schädigungsmodelle und ein Tragwerkssystem-Modell unterteilt. Dieses Modell wird a-priori durch die Eingangsdaten (welche etwa die Geometrie, die Materialien und die Verwendung der Brücke beschreiben) charakterisiert. Aus diesen ergeben sich dann auch die Ausgangsmodelle. Um die signifikanten Streuungen und Unsicherheiten adäquat abzubilden sind diese Modelle probabilistisch. Das Modell liefert eine sich kontinuierlich ändernde probabilistische Zustandsbewertung. Die Zustandsbewertung gibt eine Aussage über den Zustand und die Zuverlässigkeit des Brückensystems und seiner Bauteile und dient als Grundlage für die Planung und die Optimierung von Maßnahmen. Die Verwendung von Resultaten aus Inspektionen, Prüfungen und Überwachungen erfolgt durch eine Aktualisierung der Modellparameter. Die Aktualisierung beruht auf der Methode der Bayes'schen Aktualisierung und wird auf der Grundlage der entwickelten Klassifizierung der Bauwerksinformationen mit entsprechenden Methoden durchgeführt. Dieses Verfahren erlaubt es, alle Informationen in konsistenter Weise in ein einziges Modell einfließen zu lassen. Dabei wird die Genauigkeit und Aussagekraft der gewonnenen Daten und Beobachtungen explizit berücksichtigt. Durch die Aktualisierung der Modellparameter unter Berücksichtigung von Systemeffekten wird die Zustandsbewertung der Bauteile und des Brückensystems aktualisiert. Das ermöglicht die Planung und die Optimierung von Maßnahmen unter Berücksichtigung der Bauwerksinformationen. Auf diese Weise wird die intelligente Brücke mit Inspektionen und Überwachungen zu einem adaptiven System, welches sich Veränderungen anpassen kann.---------------------------------------------------------------------------------------------------------------------------------------------------------------------------This report describes concepts for an intelligent bridge on the basis of a reliability-based condition assessment utilizing inspection and monitoring data. The central part of the concept is a model describing the bridge system. The overall bridge model is comprised of deterioration models and a mechanical system model of the structure. The model is a-priori characterized by the input data (such as the geometry, the materials, and the utilization of the bridge). Significant uncertainties in the deterioration modeling as well as the load conditions motivate a probabilistic modeling. The model enables a continuously updated probabilistic condition assessment. It provides information about the condition and the reliability of the bridge system and its components and serves as a basis for the planning and the optimization of maintenance actions. Inspection, measurement, and monitoring information are included by updating the model parameters. Bayesian updating is utilized for the updating of the model parameters and is performed on the basis of the developed classification of structural information and the corresponding procedures. These methodologies allow to consistently incorporate all available information into the model and the prediction. Thereby, the precision and the validity of the data and observations are explicitly accounted for. The condition assessment of the bridge system and its components is updated by updating the model parameters, and maintenance actions can be planned and optimized taking into account all available information in a rational and consistent manner. In this way, the intelligent bridge with inspections, measurements, and monitoring information becomes an adaptive system, which has the ability to adjust to changes.
A software prototype is developed for assessing and updating the reliability of single-cell prestressed concrete box girders subjected to chloride-induced reinforcement corrosion. The underlying system model consists of two integrated sub-models: a condition model for predicting the deterioration state of the box girder and a structural model for evaluating the overall system reliability. The condition model is based on a dynamic Bayesian network (DBN) model which considers the spatial variation of the corrosion process. Inspection data are included in the calculation of the system reliability through Bayesian updating on the basis of the DBN model. To demonstrate the effect of partial inspections, the software prototype is applied to a case study of a typical highway bridge with six spans. The case study illustrates that it is possible to infer the condition of uninspected parts of the structure due to the spatial correlation of the corrosion process.
Inspection and maintenance of concrete bridges is a major cost factor in transportation infrastructure, and there is significant potential for using information gained during inspection to update predictive models of the performance and reliability of such structures. In this context, this paper presents an approach for assessing and updating the reliability of prestressed concrete bridges subjected to chloride-induced reinforcement corrosion. The system deterioration state is determined based on a Dynamic Bayesian Network (DBN) model that considers the spatial variability of the corrosion process. The overall system reliability is computed by means of a probabilistic structural model coupled with the deterioration model. Inspection data are included in the system reliability calculation through Bayesian updating on the basis of the DBN model. As proof of concept, a software prototype is developed to implement the method presented here. The software prototype is applied to a typical highway bridge and the influence of inspection information on the system deterioration state and the structural reliability is quantified taking into account the spatial correlation of the corrosion process. This work is a step towards developing a software tool that can be used by engineering practitioners to perform reliability assessments of ageing concrete bridges and update their reliability with inspection and monitoring data.
Dieser Bericht beschreibt ein Systemmodell für eine integrale Ermittlung und Prognose der Schadens- und Zustandsentwicklung der Elemente eines Brückensystems unter Berücksichtigung von Ergebnissen aus Inspektionen und Überwachung. Das Systemmodell wurde anhand eines ausgesuchten Spannbetonüberbaus in einzelliger Kastenbauweise entwickelt. Es besteht aus zwei integralen Teilmodellen: ein Modell zur Beschreibung des Systemschädigungszustandes und ein Modell zur Beschreibung der Standsicherheit. Für die Modellierung des stochastischen Systemschädigungszustandes eines Brückensystems werden dynamische Bayes'sche Netze (DBN) vorgeschlagen. Dieser Ansatz ermöglicht es, alle relevanten Schädigungsprozesse und deren stochastische Abhängigkeiten zu berücksichtigen. Ein wesentlicher Vorteil dieses Ansatzes ist es, dass DBN ideal dafür geeignet sind, Bayes'sche Aktualisierungen auf Grundlage von Informationen aus Inspektionen und Überwachungsmaßnahme auf eine effiziente und robuste Art und Weise durchzuführen. Der DBN-Ansatz ist deshalb für die Entwicklung von Software für das Erhaltungsmanagement von alternden Brückenbauwerken, die vom Benutzer keine vertieften Kenntnisse der Zuverlässigkeitstheorie verlangt, ideal geeignet. Für die Modellierung der Standsicherheit eines alternden Kastenträgers wird vereinfachend Biegeversagen des globalen Längssystems betrachtet. Zur Berechnung der maximalen Traglast eines Kastenträgers infolge des Systemschädigungszustandes wird ein plastisch-plastisches Verfahren eingesetzt, wobei die Beanspruchungen mittels der Fließgelenktheorie unter Ausnutzung der plastischen Beanspruchbarkeit der Querschnitte des Kastenträgers ermittelt werden. Ein Kastenträger versagt, wenn sich durch die Ausbildung einer ausreichend großen Anzahl von Fließgelenken eine kinematische Kette ausbildet. Dieser Modellierungsansatz berücksichtigt Redundanzen, die sich aus der plastischen Beanspruchbarkeit der Querschnitte und der statischen Unbestimmtheit eines Kastenträgers ergeben. Zum Nachweis der praktischen Einsetzbarkeit des entwickelten Systemmodells wurde ein Software-Prototyp entwickelt, der eine intuitiv benutzbare graphische Benutzeroberfläche (Front-End) mit einem Berechnungskern (Back-End) koppelt. Die aktuelle Version des Software-Prototyps implementiert ein Modell der chloridinduzierten Bewehrungskorrosion und ein Tragwerksmodell, welches das Verfahrens der stetigen Laststeigerung zur Bestimmung der maximalen Traglast des Kastenträgers auf der Grundlage eines Finite-Elemente-Modells umsetzt. Zur Durchführung von Bayes'schen Aktualisierungen des Systemschädigungszustandes auf der Grundlage des DBN-Modells implementiert der Prototyp den Likelihood-Weighting-Algorithmus. Die entwickelte Architektur des Prototyps ermöglicht eine Erweiterung der Software um weitere Schädigungsprozesse. Der entwickelte Software-Prototyp ermöglicht Benutzern ohne vertiefte Kenntnisse der Zuverlässigkeitstheorie eine Berechnung des Einflusses von Bauwerksinformationen auf den Systemschädigungszustand und die Tragsicherheit eines Kastenträgers. Auf dieser Grundlage können effiziente Inspektions- und Überwachungsmaßnahmen identifiziert und das Erhaltungsmanagement optimiert werden.
The collaborative project “Impacts of impurities in CO2 streams captured from different emitters in a regional cluster on transport, injection and storage (CLUSTER)” aimed to set up recommendations on how to define “reasonable minimum composition thresholds” that CO2 streams should meet when accessing CO2 transport pipeline networks. Within CLUSTER, we investigated potential impacts of CO2 streams with different and temporally variable compositions and mass flow rates along the whole CCS chain. Investigations included, amongst others, impacts on:
• corrosion of pipeline steel,
• pipeline network design and related transport costs,
• alteration of well bore cements,
• pressure development and rock integrity,
• geochemical reactions, and
• petrophysical and geomechanical rock properties.
All investigations are based on a generic CCS chain scenario. In this scenario, CO2 streams are captured from a spatial cluster of eleven emitters and collected in a regional pipeline network. Emitters comprise seven fossil fuel-fired power plants equipped with different capture technologies, two cement plants, one refinery and one integrated iron and steel plant. In total, 19.78 Mio t CO2 (including impurities) are captured in the emitter cluster annually. The combined CO2 stream is transported in a trunk line with a length of 400 km (100 km of these offshore) and is injected into five generic storage structures. The storage reservoirs are saline aquifers of the Buntsandstein.
The investigations revealed beneficial and deteriorating impacts of different impurities and combinations thereof. Overall, no fundamental technical obstacles for transporting, injecting and storing CO2 streams of the modelled variable compositions and mass flow rates were observed. Based on the results, the CLUSTER project team recommends not to define “minimum composition thresholds” for CO2 streams as strict threshold values for each individual impurity in the stream. Instead, CO2 stream compositions and variabilities for specific CCS projects should be constrained with regard to a set of parameters including i) the overall CO2 content, ii) maximum contents of relevant impurities or elements, iii) acceptable variability of CO2 stream composition, and iv) impurity combinations to be avoided.
In a systematic approach we synthesized a new series of fluorescent probes incorporating donor–acceptor (D-A) substituted 1,2,3-triazoles as conjugative π-linkers between the alkali metal ion receptor N-phenylaza-[18]crown-6 and different fluorophoric groups with different electron-acceptor properties (4-naphthalimide, meso-phenyl-BODIPY and 9-anthracene) and investigated their performance in organic and aqueous environments (physiological conditions). In the charge-transfer (CT) type probes 1, 2 and 7, the fluorescence is almost completely quenched by intramolecular CT (ICT) processes involving charge-separated states. In the presence of Na+ and K+ ICT is interrupted, which resulted in a lighting-up of the fluorescence in acetonitrile. Among the investigated fluoroionophores, compound 7, which contains a 9-anthracenyl moiety as the electron-accepting fluorophore, is the only probe which retains light-up features in water and works as a highly K+/Na+-selective probe under simulated physiological conditions. Virtually decoupled BODIPY-based 6 and photoinduced electron transfer (PET) type probes 3–5, where the 10-substituted anthracen-9-yl fluorophores are connected to the 1,2,3-triazole through a methylene spacer, show strong ion-induced fluorescence enhancement in acetonitrile, but not under physiological conditions. Electrochemical studies and theoretical calculations were used to assess and support the underlying mechanisms for the new ICT and PET 1,2,3-triazole fluoroionophores.
In the present study the incorporation of iron into an organic polymer, composed of formamidine subunits [R–N=C(H)–NH–R], has been examined. The catalytic ability of the recyclable material was investigated in the iron-catalyzed formation of C–C bonds. After optimization of the reaction conditions, excellent yields and chemoselectivities were feasible.
For the vast majority of ellipsometric measurements, the application of planar substrates is mandatory and requires a proper sample alignment prior to the measurement. Here, the authors present a generalized approach of how to extract the isotropic ellipsometric sample parameters from an imaging Mueller-matrix measurement even if the sample is significantly misaligned. They validate the method by layer-thickness calculations based on imaging Mueller-matrix measurements of flat crystalline silicon samples that were misaligned on purpose. Furthermore, they also exploit this method’s capabilities to perform spatially resolved layer-thickness measurements of a single-layer indium-tin-oxide coating on a fused-silica microlens without the need of realignment or repositioning of the sample during the measurement.
The authors describe and interpret curvature-related changes to the ellipsometric readout. As model system for a concave curvature, a set of three spherical microscopic indents in silicon (100) of different sizes was prepared by instrumented indentation testing using a spherical indenter. For reference, these samples were characterized by AFM to reveal the topography of each structure. The concavelike indents were analyzed by Mueller-Matrix imaging ellipsometry to extract lateral intensity images of 12 elements of the Mueller-Matrix. As a result of the detailed analysis of the image elements m22, m23, and m14, it was possible to correlate intensity changes and symmetry properties to depolarization and cross polarization induced by the edge threshold and the curved surface of the indent.