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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.