Structural reliability applied to deep excavations. Coupling reliability methods with finite elements.

Civil Engineering and Geoscience

Re-assessing reliability based on survived loads

The reliability of flood defenses is often dictated by large uncertainties in the hydraulic loading and the structural resistance. Additional information decreases uncertainty, however, acquiring it is often costly. One source of information, even though in many cases readily available, is hardly used – survived loads. This article shows how data on survived load conditions can be incorporated in reliability analysis by means of Bayesian techniques. The theory is illustrated by simple and realistic examples. In contrast to other sources of information, reassessing structures using survived load data always leads to higher reliability or lower probability of failure. Furthermore, attention is given to the expected development of failure in time. This may be relevant for situations, where the safety requirements of a structure are stated in terms of a design or inspection period. For both, re-assessing reliability based on (one time) survived loads as well as the expected increase of reliability in time, the examples show significant impact. Use of this knowledge may, consequently, safe cost of construction or reinforcement.Hydraulic EngineeringCivil Engineering and Geoscience

Value of information in levee monitoring and inspection (poster)

Hydraulic EngineeringCivil Engineering and Geoscience

On reducing piping uncertainties: A Bayesian decision approach

Dikes and levees play a crucial role in flood protection in deltaic areas such as the Netherlands. Internal erosion piping or under-seepage is a major cause of levee failures and a main contributor to the probability of failure of river levees due to the large (mostly geotechnical) uncertainties. The present thesis investigates how geotechnical uncertainties can be reduced and how we can provide input for rational investment decisions for uncertainty reduction measures such as monitoring or site investigation. The general trade-off is between investing in uncertain reduction and realizing cost reductions of retrofitting measures necessary to achieve the required reliability target. The key ingredients of the approach are Bayesian posterior and decision analysis. Posterior analysis allows us to update the piping reliability with new information; Bayesian decision analysis enables us to estimate the consequences and costs of the considered decision options. The goal of the decision analysis is to identify the strategy with the least expected cost which meets the reliability target as set by the safety standard. The essential strategy options are (a) investing in uncertainty reduction and (b) retrofitting (i.e., taking physical measures to increase the structural reliability). Within each strategy we optimize the "design parameters" such as the site investigation density or the width of piping berms. Several sources of information are investigated in this thesis, the first being field performance observations made during substantial loading conditions such as seepage or sand boils. Whereas earlier studies only considered survival information (in Dutch: "bewezen sterkte"), the proposed approach allows to incorporate much more detailed performance observations indicating good or poor performance of the levee. The case study results suggest that the probability of piping failure can decrease or increase roughly one order of magnitude depending on the prior uncertainties and the observation made. Another source of information is monitoring the response of the hydraulic head in the aquifer, which can have a considerable effect on the piping reliability, because it provides information on the geo-hydrological properties in the foundation of the levee. The same holds for site investigation such as soundings, which allow us to "map" the stratification including the thickness of the blanket layer, which is very important for the sub-mechanisms uplift and heave. Pre-posterior decision analysis enables us to determine the optimal monitoring configuration or site investigation density such that the sum of investigation cost and expected retrofitting cost is minimized. The application examples elaborated in this thesis suggest that investments in back-analysis of historical observations, monitoring and site investigation can be very cost-effective. The results also show that a framework which does not consider the benefits of risk reduction beyond meeting the reliability target is sub-optimal in an overall risk sense.Hydraulic EngineeringCivil Engineering and Geoscience

Updating piping probabilities with survived historical loads

Piping, also called under-seepage, is an internal erosion mechanism, which can cause the failure of dikes or other flood defence structures. The uncertainty in the resistance of a flood defence against piping is usually large, causing high probabilities of failure for this mechanism. A considerable part of this uncertainty is of epistemic nature, which can be reduced by incorporating extra information. It is shown how the knowledge of historically survived water levels, the main load factor, can be integrated into the probability distribution of the piping resistance variables by means of Bayesian Updating. The effects are demonstrated by means of a realistic numerical example.Hydraulic EngineeringCivil Engineering and Geoscience

A Factor of Safety for Geotechnical Characterization

Hydraulic EngineeringCivil Engineering and Geoscience

Briefing: Lessons learned from failures of flood defences

Failure of flood defences during extreme events can lead to enormous damage and loss of life. This paper presents lessons learned from investigations of flood events over recent years, including the 2005 flooding in New Orleans, USA, caused by hurricane Katrina. Based on these findings, new developments in the field of research, design and engineering of flood defences are discussed, such as the introduction of risk-based approaches and better utilisation of failure data, field observations and monitoring. Such approaches are crucial to allow extrapolation for more extreme load conditions due to climate change, with anticipated sea level rise and increasing precipitation.Hydraulic EngineeringCivil Engineering and Geoscience

Developments in Levee Reliability and Flood Risk Analysis in the Netherlands

This paper presents and overview of advances in flood risk and levee reliability analysis in the Netherlands. It is described how new safety standards – in the form of a target failure probability – have been derived on the basis of nationwide flood risk assessments which taken into account both economic risk and risk to life. The process for derivation of semi-probabilistic design codes (i.e. factors of safety) for various geotechnical failure mechanisms of flood defences is described and it is shown how these semi-probabilistic requirements are consistent with the target probabilities of failure and ultimately with the underlying flood risk acceptance criteria. The newly introduced approach also raises challenges like the introduction of fully reliability based design and assessment techniques, but it also provides opportunities such as the use of reliability updating and data assimilation, which will be highlighted after discussing the framework and its overall coherence.Hydraulic EngineeringCivil Engineering and Geoscience

Bayesian Inference of Piping Model Uncertainties Based on Field Observations

This paper presents a Bayesian model to determine the model uncertainty of a critical horizontal gradient model for piping for dikes, such a Lane and Bligh. A Bayesian model is needed for two reasons. First, there is a large overlap in cases that failed and survived. Second, the evidence of the failed cases is limited .The model consists of a non-informative prior that is combined with likelihood functions for failed and survived cases. This involves modeling the mean and standard deviation of the model uncertainty as random variables. For survived cases we know the limit state function was larger than 0 for the observed water level. For failed cases we know the limit state function was smaller than 0; or Z = 0; which is a less conservative assumption. This information is used to determine the likelihood functions for failed and survived cases. The prior and likelihoods are combined to find the posterior distributions of the mean and standard distribution of the model uncertainty. Using integration, this finally results in the (lognormal) distribution of the model uncertainty. The model is applied to the data of Bligh and Lane and shows both a high mean and high standard deviation of the model uncertainty, where the model of Lane performs better than Bligh. It is recommended to tailor the proposed model to dikes by making a different distinction between horizontal and vertical erosion. Furthermore, it is recommended to apply the model to more dike specific data since the Bligh data mainly consists of dams instead of dikes.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris

Economic optimization of coastal flood defense systems

Coastal flood defense systems can consist of multiple lines of defense. In case of a system with a front and a rear defense (e.g. a storm surge barrier and levees), the front defense can improve the reliability of the rear defense by reducing the load on this rear defense. This paper develops a framework in order to assess whether including the influence of such a load reduction influences the economically optimal safety targets of both defenses. The economic optimization is carried out using two approaches: a simplified method developed to explore the behavior of the economic optimization with a front and rear defense, and a numerical framework geared towards practical applications. The numerical framework provides more flexibility in defining risk, cost and damage functions, and emphasizes on the applicability and tractability of the necessary steps from an engineering perspective. Both approaches are used in a hypothetical case study in order to quantify the effect of including a load reduction on the economically optimal safety targets. The results indicate that if a front defense can create a significant risk reduction in a cost efficient manner, more efficient economically optimal safety targets can be found by including the load reduction.prHydraulic Structures and Flood Ris