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An analytical expression for the frequency response function of a coupled pedestrian-bridge system is presented and evaluated using an experimental measurement campaign performed on the Folke Bernadotte Bridge in Stockholm, Sweden. A finite element model and the modal models that consider the human–structure interaction effect are calibrated with respect to the measurements. The properties of the spring–mass–damper model representing the pedestrians were identified, considering the different structural modes of the system. Good agreement was obtained between the experimental and theoretical frequency response functions. A sensitivity analysis of the obtained solution was performed, validating the determined analytical expression for the frequency response function of the coupled pedestrian-bridge system that takes into account the human–structure interaction effect.
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.
Owners or operators of offshore wind farms perform inspections to collect information on the condition of the wind turbine support structures and perform repairs if required. These activities are costly and should be optimized. Risk-based methods can be applied to identify inspection and repair strategies that ensure an optimal balance between the expected total service life cost of inspection and repair, and the achieved risk reduction. Such an optimization requires explicit modeling of repairs. In this paper, the impact of different repair models on the results of a risk-based optimization of inspection and repair strategies is quantified in a numerical example considering a jacket-type steel frame subject to high-cycle fatigue. The example showed that, in this specific application, there is no need for detailed modeling of the behavior of repaired welded connections.
Identifying optimal inspection and repair strategies for offshore jacket structures is a challenging task. We pre-sent an approach, which is based on recent developments in the field of risk-based operation and maintenance planning at the structural system level. The approach utilizes heuristics to define inspection and repair strate-gies at the system level and to reduce the search space of possible strategies. For each defined strategy, the expected service life cost of inspection, repair and failure is evaluated based on simulated inspection and re-pair histories. Subset simulation is applied to compute the conditional repair and failure probabilities required for this analysis. It also forms the basis for simulating inspection and repair histories. The strategy that mini-mizes the expected service life cost is the optimal one in the set of pre-selected strategies. The underlying condition and performance model accounts for the stochastic dependence among the deterioration states of the different structural elements and the structural redundancy. The approach is demonstrated in a case study considering a jacket-type frame. In this study, we essentially vary the inspection interval, the minimum num-ber of inspected components and the target reliability, and identify the combination that minimizes the ex-pected total service life cost.
Identifying optimal inspection and repair strategies for offshore jacket structures is a challenging task. We pre-sent an approach, which is based on recent developments in the field of risk-based operation and maintenance planning at the structural system level. The approach utilizes heuristics to define inspection and repair strate-gies at the system level and to reduce the search space of possible strategies. For each defined strategy, the expected service life cost of inspection, repair and failure is evaluated based on simulated inspection and re-pair histories. Subset simulation is applied to compute the conditional repair and failure probabilities required for this analysis. It also forms the basis for simulating inspection and repair histories. The strategy that mini-mizes the expected service life cost is the optimal one in the set of pre-selected strategies. The underlying condition and performance model accounts for the stochastic dependence among the deterioration states of the different structural elements and the structural redundancy. The approach is demonstrated in a case study considering a jacket-type frame. In this study, we essentially vary the inspection interval, the minimum num-ber of inspected components and the target reliability, and identify the combination that minimizes the ex-pected total service life cost.
The presentation is divided in two parts, each evaluates a different aspect of safety.
It starts with the analysis of consequences resulting from worst case ruptures of gas cylinders. The number of harmed persons and fatalities dependent from the pressure-volume product and the kind of stored gas. In parallel, there is a national accepted rule for accepted failure rates depending from this pV-product created by BAM. When combining both aspects it become clear that the pressure-volume product can be used as a good indicator for consequences. At a level of about 120 MPa m3 the maximum consequence starts to become catastrophic character. This shows the reason why the representatives of DIN insisted in limiting relevant pV-limits for tubes and cylinders to 1 Mio. bar litres.
The second part gives a raff overview on the parameters influencing the acceptance rates of borderline basic populations. This is added by some slides giving an idea for the improvement of the minimum burst requirement and finally completed by a proposal for improved acceptance criteria for the burst test.
The basic idea is: an increased pV-product of tubes has the be reflected by an increased safety level.
The presentation explains the intended way of BAM in tackling the safety issues in the project TAHYA.
The way how the term “safety” is used in TAHYA leads to the need for a more risk-based understanding of safety. Based on this, the Monte Carlo simulation is used to show where the weak points of current regulations are. Thus, a concept for optimization of relevant regulations, codes and standards will be elaborated during the project. For this purpose, it is helpful to improve the currently operated tool for Monte Carlo simulation, which will need additional data for monitoring the outcome. Strength data, that will be determined by BAM and the other partners during the already agreed test program can be used for this purpose without additional effort.
Fires in road tunnels constitute complex scenarios with interactions between the fire, tunnel users and safety measures. More and more methodologies for risk analysis quantify the consequences of these scenarios with complex models. Examples for complex models are the computational fluid dynamics model Fire Dynamics Simulator (FDS) and the microscopic evacuation model FDS+Evac. However, the high computational effort of complex models often limits the number of scenarios in practice. To balance this drawback, the scenarios are often simplified. Accordingly, there is a challenge to consider complex scenarios in risk analysis.
To face this challenge, we improved the metamodel used in the methodology for risk analysis presented on ISTSS 2016. In general, a metamodel quickly interpolates the consequences of few scenarios simulated with the complex models to a large number of arbitrary scenarios used in risk analysis. Now, our metamodel consists of the projection array-based design, the moving least squares method, and the prediction interval to quantify the metamodel uncertainty. Additionally, we adapted the projection array-based design in two ways: the focus of the sequential refinement on regions with high metamodel uncertainties; and the combination of two experimental designs for FDS and FDS+Evac.
To scrutinise the metamodel, we analysed the effects of three sequential refinement steps on the metamodel itself and on the results of risk analysis. We observed convergence in both after the second step (ten scenarios in FDS, 192 scenarios in FDS+Evac). In comparison to ISTSS 2016, we then ran 20 scenarios in FDS and 800 scenarios in FDS+Evac. Thus, we reduced the number of scenarios remarkably with the improved metamodel. In conclusion, we can now efficiently integrate complex scenarios in risk analysis. We further emphasise that the metamodel is broadly applicable on various experimental or modelling issues in fire safety engineering.
Featuring a detailed analysis of current approval requirements and the relevant safety assessment methods for gas cylinders in general and with main focus on composite cylinders for storing ompressed natural gas and hydrogen, this book demonstrates how current regulations and standards limit the ability to reduce cost and weight. Based on this data, it then highlights the potential offered by the proposed approval procedure based on probabilistic safety assessment.
After addressing the economic potential of probabilistic safety assessments, the book details working procedures and improving cycles and (slow) bursts as methods for assessing residual strength. It then discusses methods for statistically evaluating test data, as well as sample- size and distribution character considerations. A definition of sample strength is elaborated in terms of the performance sheets developed by the author. On this basis, it discusses safety as a property of service life and interpreted as an issue of degradation, and explores aspects of artificial aging for simulating the end-of-life reliability level. Lastly, the book considers control and inspection aspects: quality of production, degradation prediction using destructive sample tests parallel to operation, retesting periods and correcting for underand overestimates of safe lifetime.
Presented in schematic diagrams, illustrations and tables, this information enables manufacturers and operators to use this new approach in practice and supports the improvement of current regulations and standards.
Methodologies on fire risk analysis in road tunnels consider numerous factors affecting risks (risk indicators) and express the results by risk measures. But only few comprehensive studies on effects of risk indicators on risk measures are available. For this reason, this study quantifies the effects and highlights the most important risk indicators with the aim to Support further developments in risk analysis. Therefore, a system model of a road tunnel was developed to determine the risk measures.
The system model can be divided into three parts: the fire part connected to the fire model Fire Dynamics Simulator (FDS); the evacuation part connected to the evacuation model FDS+Evac; and the frequency part connected to a model to calculate the frequency of fires. This study shows that the parts of the system model (and their most important risk indicators) affect the risk measures in the following order: first, fire part (maximum heat release rate); second, evacuation part (maximum preevacuation time); and, third, frequency part (specific frequency of fire). The plausibility of These results is discussed with view to experiences from experimental studies and past fire incidents.
Conclusively, further research can focus on these most important risk indicators with the aim to optimise risk analysis.