TY - THES A1 - Berchtold, Florian T1 - Metamodel for complex scenarios in fire risk analysis of road tunnels N2 - The risk analysis of road tunnels faces a growing complexity in fire scenarios, e.g. caused by new energy carriers. Essentially, such complex scenarios involve many interactions between the tunnel users, the fire source and the safety measures. One example is the alarm of tunnel users either initiated by the perception of smoke or by the fire alarm system. To consider these interactions for the quantification of consequences, e.g. fatalities, risk analysis requires a complex model. However, the complex model can compute in practice only few discrete scenarios due to its high computational cost, whereas risk analysis generally needs the consequences of a high number of random scenarios. Metamodels can solve this contradiction. They are able to approximate the consequences of many random scenarios with low computational cost based on the consequences of few discrete scenarios computed with the complex model. The efficiency of metamodels depends on the required number of these discrete scenarios. In this sense, this dissertation proposes an efficient metamodel within an innovative methodology for risk analysis of road tunnels to allow to consider an increased complexity of scenarios. This metamodel applies the following methods or models: the projection array-based design method specifies the experimental design for the discrete scenarios; the combination of the fire model FDS and the microscopic evacuation model FDS+Evac constitutes the complex model; and moving least squares produces the response surface model. The response surface model approximates the consequences of the random scenarios and therewith introduces an uncertainty, called metamodel uncertainty, which is quantified with the prediction interval method. Additionally, stochastic individual characteristics of tunnel users in discrete scenarios computed with FDS+Evac attribute evacuation uncertainties to the consequences. An original development in this dissertation, the ’direct approach’, directly transfers the evacuation uncertainties of the discrete scenarios to any random scenario. The evaluation of the metamodel in this dissertation shows following results. Firstly, the response surface model sufficiently represents the consequences of the complex model. Secondly, the metamodel uncertainty is also essential for this representation, but the prediction interval method reveals a drawback in the risk analysis. Potential approaches to deal with this drawback are discussed. Finally, the direct approach reproduces the evacuation uncertainty of the complex model which then clearly affects the consequences of random scenarios. Therefore, the consideration of the evacuation uncertainty plays an important role for the risk analysis. Furthermore, the projection array-based design method was adapted in this dissertation with two approaches, namely the combination of the experimental designs for FDS and FDS+Evac as well as their sequential refinement. Both approaches contribute to the efficiency of the metamodel. These results lead to following conclusions. Firstly, the metamodel efficiently integrates the consequences of discrete scenarios into risk analysis and thus allows to consider an increased complexity. Secondly, the metamodel is an advancement for risk analysis not only for road tunnelsbutalsomoregeneralinfiresafetyengineering. Forthesetworeasons,themetamodel might be interesting for other methodologies for risk analysis. In addition, the metamodel is generic and is therefore widely applicable on other issues beside from risk analysis, e.g. to assess the safety of structures related to time-consuming experiments depending on multiple variables. N2 - Risikoanalysen für Straßentunnel müssen eine immer größere Komplexität in Brandszenarien berücksichtigen, beispielsweise verursacht durch neue Energieträger. Dabei hängt die Komplexität von Szenarien mit einer Vielzahl von Interaktionen zwischen den Tunnelnutzern, der Brandquelle und den Sicherheitsmaßnahmen zusammen. Zum Beispiel werden Tunnelnutzer entweder direkt durch Rauch oder durch die Brandmeldeanlage alarmiert. Um die Interaktionen bei der Berechnung der Konsequenzen, wie z.B. getötete Personen, zu berücksichtigen, benötigen Risikoanalysen komplexe Modelle. Allerdings können komplexe Modelle wegen ihres hohen Zeitaufwandes nur wenige diskrete Szenarien simulieren, wohingegen Risikoanalysen auf Konsequenzen einer Vielzahl von Zufallsszenarien basieren. Als Lösung dieses Widerspruchs kommen Metamodelle in Betracht. Sie können die Konsequenzen von vielen Zufallsszenarien innerhalb kurzer Zeit näherungsweise berechnen und verwenden dafür die Konsequenzen von wenigen mit dem komplexen Modell simulierten diskreten Szenarien. Die Effizienz von Metamodellen hängt dabei mit der nötigen Anzahl von diskreten Szenarien zusammen. Demnach wird in dieser Dissertation ein effizientes Metamodell in eine selbst erstellteMethodikzurRisikoanalysefürStraßentunnelintegriert,umdamiteinehöhereKomplexität der Szenarien einbeziehen zu können. Das Metamodell setzt sich aus folgenden Methoden und Modellen zusammen: die ’projection array-based design’-Methode definiert den Simulationsplan für die diskreten Szenarien; eine Kombination aus dem Brandmodell FDS und dem mikroskopischen Evakuierungsmodell FDS+Evac bildet das komplexe Modell; und ’moving least squares’ dient zur Erstellung des Antwortflächenmodells. DasAntwortflächenmodellberechnetnäherungsweisedieKonsequenzen der Zufallsszenarien und erzeugt dadurch eine Unsicherheit, die Metamodellunsicherheit. Sie wird mit der ’prediction interval’-Methode bestimmt. Zusätzlich verursachen individuelle Eigenschaften der Tunnelnutzer in den mit FDS+Evac simulierten diskreten Szenarien Evakuierungsunsicherheiten in den Konsequenzen. Ein in der Dissertation neu entwickelter Ansatz, der ’direkte Ansatz’, überträgt die Evakuierungsunsicherheit der diskreten Szenarien unmittelbar auf die Zufallsszenarien. Die Untersuchung des Metamodels in der Dissertation führte zu folgenden Ergebnissen. Erstens,dasAntwortflächenmodellbildetdieKonsequenzenderdiskretenSzenarienausreichend genau ab. Zweitens, dazu trägt die Metamodellunsicherheit wesentlich bei. Allerdings zeigt die ’prediction-interval’-Methode einen Nachteil für die Risikoanalyse. Zur Lösung dieses Nachteils werden potentielle Ansätze diskutiert. Und drittens, der direkte Ansatz gibt die Evakuierungsunsicherheiten des komplexen Modells wieder, welche dann die Konsequenzen der Zufallsszenarien deutlich beeinflussen. Aus diesem Grund ist die Evakuierungsunsicherheit für die Risikoanalyse wichtig. Zusätzlich wurde die ’projection array-based design’Methode in dieser Dissertation mit zwei Ansätzen angepasst: der Verknüpfung beider Simulationspläne für FDS und FDS+Evac sowie deren schrittweisen Verfeinerung. Die Effizienz des Metamodels wird durch beide Ansätze erhöht. Diese Ergebnisse führen zu folgenden Schlussfolgerungen: erstens, das Metamodell integriert die Konsequenzen der diskreten Szenarien auf eine effiziente Weise in die Risikoanalyse und ermöglicht dadurch die Berücksichtigung einer höheren Komplexität; und zweitens, das Metamodell stellt einen Fortschritt für Risikoanalysen nicht nur für Straßentunnel sondern auch allgemein im Brandingenieurwesen dar. Aus diesen beiden Gründen kann das Metamodell für andere Methodiken zur Risikoanalyse interessant sein. Zudem ist das Metamodel flexibel auf andere Problemstellungen außerhalb der Risikoanalyse anwendbar, wie z.B. der Bewertung der Bauwerkssicherheit, welche von zeitaufwändigen Untersuchung und mehreren Variablen abhängt. KW - Metamodel KW - Surrogate KW - Uncertainty KW - Risk KW - Consequence KW - Fire KW - Evacuation KW - Tunnel PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:hbz:468-20200114-101029-6 DO - https://doi.org/10.25926/evq8-h241 SP - 1 EP - 171 PB - Bergische Universität Wuppertal CY - Wuppertal AN - OPUS4-51039 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Schneider, Ronald T1 - Time-variant reliability of deteriorating structural systems conditional on inspection and monitoring data N2 - 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. T3 - BAM Dissertationsreihe - 168 KW - Reliability KW - Structural systems KW - Deterioration KW - Bayesian analysis KW - Inspection KW - Monitoring KW - Zuverlässigkeit KW - Tragstrukturen KW - Schädigungsprozesse KW - Bayes'sche Analyse KW - Inspektion KW - Monitoring PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-512977 SN - 1613-4249 VL - 168 SP - 1 EP - 188 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-51297 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -