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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.
Messen im Bauwesen 2018
(2018)
Der Tagungsband zur 10. Fachtagung „Messen im Bauwesen“ enthält die Beiträge der Autoren zum diesjährigen Thema „Messtechnische Anwendungen und deren Einbindung in digitale Bauwerksmodelle“ enthält.
Building Information Modeling (BIM) ermöglicht einen integralen Entwurfs-, Ausführungs- und Instandsetzungsprozess und verspricht Bauwerke von höherer Qualität bei niedrigeren Kosten und kürzeren Projektlaufzeiten. Was BIM aber im konkreten Anwendungsfall bedeutet, ist generell noch Teil eines umfassenden Diskussionsprozesses, insbesondere für die Integration der Ergebnisse von Bauwerksmessungen aus der Ausführungs- und Betriebsphase.
Die diesjährige Ausgabe der Tagung „Messen im Bauwesen“ befasst sich schwerpunktmäßig mit verschiedenen Aspekten des BIM in der bestehenden Baupraxis, beschreibt Technologien hinter BIM und zeigt die vielfältigen Möglichkeiten eines Einsatzes von Messverfahren sowohl in der Bauausführung als auch beim Lebenszyklusmanagement von Bauwerken auf. Auf Basis dieser Schwerpunktsetzung möchten wir wieder aus der Sicht des Bauingenieurs und des Geodäten von Praxisbeispielen aus Hoch- und Tiefbau berichten.
Die Vorträge sind zusammengestellt mit Blick insbesondere auf Bau- und Vermessungsingenieure in Ingenieurbüros sowie der Verwaltung in den Bereichen Planung, Ausführung und Betrieb von Infrastrukturbauwerken.
Die Weiterentwicklung der Verfahren und Techniken zur dauerhaften Überwachung von Bauwerken ist Gegenstand zahlreicher Forschungs- und Entwicklungsvorhaben. Der praktische Einsatz dieser Verfahren beschränkt sich bisher jedoch auf durchaus zahlreiche, jedes für sich jedoch sehr konkrete Einzelprobleme beschreibende Projekte. Einer flächendeckenden Anwendung stehen häufig – berechtigte oder unberechtigte – Bedenken zur Effizienz dieser Verfahren im Vergleich zu baupraktisch etablierten Verfahren wie z. B. regelmäßigen Bauwerksinspektionen entgegen. Weiterführende Aspekte wie optimierte Wartungskonzepte oder Lebensdauerprognosen zur begründeten Priorisierung von Ertüchtigungsmaßnahmen sind aufgrund des Fehlens zeitnah realisierbarer, monetärer Vorteile oftmals schwer vermittelbar. Dieser Beitrag soll einige grundlegende Ziele aktueller Monitoringkonzepte anhand von Projektbeispielen der BAM aufzeigen, um die Potentiale dieser Verfahren zu verdeutlichen und mögliche sinnvolle Anwendungsgebiete zu erschließen. Im Vordergrund dieses Übersichtsbeitrages stehen dabei die grundlegenden Ideen und Ziele dieser Projekte; bezüglich der Ergebnisse wird auf die entsprechenden Fachveröffentlichungen verwiesen.
The European Water Framework Directive (WFD) 2000/60/EC specifies a list of 33 priority water pollutants. For these substances, Environmental Quality Standards (EQS), equivalent to the maximum allowable concentrations, had been defined at very low levels.
EQS values refer to the whole water body, i.e. include contaminants which are associated to suspended solids or colloids present in the natural water. For several priority pollutants primary analytical methods capable of measuring the target analytes at EQS level in natural water are still missing. The project has developed and validated such methods for three selected compounds, namely Tributyltin (TBT), Polybrominated Diphenylether (PBDE) and Polycyclic Aromatic Hydrocarbons (PAH).