The Netherlands is a country prone to flooding. Recent assessments led to the insight that protection levels of many flood defences should be increased. Integrating reinforcement measures is a difficult task as many dikes are situated in densely populated areas. Conventional reinforcement measures include berm construction or the implementation of sheet pile walls. The first can become very expensive in case houses are situated close to a dike, the latter is rather expensive and irreversibly changes dike composition. Geotechnical failure modes piping and slope instability are most important failure modes for Dutch river dikes. In this thesis a case study is carried out on such a dike that is disqualified for those failure modes. The dike is situated in an urban area with limited space available for reinforcement works. It is studied whether pore pressure measurements behind the dike can be used to improve the reliability estimate for piping. Subsequently it is analyzed whether implementing pressure relief wells can be used to increase dike reliability for both considered failure modes. For the case study an advanced modelling framework was used consisting of groundwater modelling software and a random field generator. The case study was divided into two parts. The first part consisted of a dike section of 100 m based on a dike section at Wijk bij Duurstede. The second part consisted of the same dike section, only now extrapolated over a length of 2 km for which variations in soil conditions become more important. First, an analysis was conducted to define the optimal amount of pore pressure sensors behind the dike. It was found that for a dike section of 100 m a total of four sensors could be used to perform reliability updates, for a dike section of 2000 m it was found that a total of six sensors could be used. For the 100 m section piping failure probability improved from 5.21E-3 per year to 1.62E-4 per year. For the 2000 m section piping failure probability improved from 5.21E-3 per year to 1.89E-4 per year. Pressure relief well implementation behind the dike was considered as a measure to increase dike reliability for both failure modes. The system was designed based on a target reliability level for slope instability. The same modelling framework was applied. An analysis was conducted and it was shown that for the 100 m section a well spacing of 50 m would sufficiently increase dike reliability for slope instability. For the 2000 m section a well spacing of 45 m was found. For the 100 m section failure probability for slope instability increased from 8.81E-5 per year to 1.22E-6 per year, failure probability for piping increased from 1.62E-4 per year to 2.03E-7 per year. For the 2000 m section failure probability for slope instability increased from 8.81E-5 per year to 1.30E-6 per year, failure probability for piping increased from 1.89E-4 per year to 1.02E-7 per year. It was shown that for both trajectories target reliability levels for all failure modes were met. For this case study it was shown that pressure relief wells provide a good design alternative for dike reinforcement in urban areas. A life cycle cost analysis was applied and it was shown that implementation of relief wells is economically attractive compared to traditional design alternatives berms and sheet pile walls. For the first relocation of houses forms an important cost driver, for the latter initial construction cost are high. Furthermore it was shown that implementation of pore pressure monitoring prior to the design of a relief well system yields a positive value of information.

Over time, degradation processes might cause damage to pattern-placed revetments. Examples of such damages are missing elements, deformation, and the loss of joint filling. However, little is known about the exact consequences of those damages. Therefore, when damage is observed during an inspection, it is estimated based upon experience what the possible consequences are. If the consequences are misjudged, this will lead to inefficient maintenance.
Better insight into the exact consequences of damages will expand the possibilities of how risk-based maintenance can be used to maintain revetments. Consequentially, maintenance interventions can be planned more efficiently, reducing the societal costs incurred due to inefficient maintenance. This study contributes to this topic by investigating whether it is possible to estimate the impact of damages on the stability and reliability of a revetment using a model.
Within the study, first, damages are analyzed based upon a literature review. Next, data of old flume experiments with Basalton and basalt revetments are analyzed to study and quantify damages. This analysis focuses on the uplift of elements, deformation around the wave impact zone (S-profile), and washed-out joint filling. Then, a finite element model (FE-model) is created to simulate the wave impact on pattern-placed revetments. The main focus of the FE-model is to study the uncertainty due to structural changes, which are the damages. The damages quantified during the analysis of the flume experiments are also included in order to be able to assess damaged revetments. Finally, the study uses the FE-model within a sensitivity analysis to study the most important uncertain parameters. Based on the samples used in the sensitivity analysis, response surfaces are fitted to obtain a model that can predict the damage for any set of parameters. Finally, these models are demonstrated in a case study of a coastal dike near Den Helder. An increase of 10 – 100 times of the failure probability has been observed for small deformations, while for medium to large deformations, the failure probability increased by 1000 – 10000 times. For no joint filling or a missing element, the failure probability increased by 10 - 100 times.
This study showed that it is possible to create a finite element model that can estimate the impact damage has on the stability and reliability of a pattern-placed revetment. The obtained results can be used within the daily practise as part of risk-based maintenance as the study provides a way to obtain a first indication of the impact of missing elements, deformation, and washed-out joint filling. Additionally, the developed methodology can be used to obtain the impact of other types of damage. Although Basalton is the primarily investigated type of top layer, analysis of the flume experiments showed that basalt revetments are subject to identical types of damage. Therefore, it is expected that the findings within this study can be applied to a broader range of top layer elements with similar characteristics to Basalton (e.g. basalt, C-Star, and Hydroblocks).

Maturity model is widely known as an assessment tool to understand an organization management capabilities and identifying potential improvement. The model demonstrates informative results towards the organization management maturity but hard to acknowledge the influence of potential improvement towards the organization’s asset performance. There have not yet been a study on measuring the asset performance conditional of the organization management maturity. This research objective is to develop an approach to translates maturity model to an asset lifecycle cost and performance by using Dynamic Bayesian Network (DBN). This research uses semi-hypothetical case to see how the model might unfold and to learn the possibility of maturity model development. The chosen hypothetical case is the organizational decision-making process of grass revetment maintenance during winter season based on information management maturity. The output of the DBN is the expected annual cost of the asset for a grass revetment maintenance conditional to organization information management maturity. The result is analyzed by using Value of Information (VOI) which enables us to understand the influence of information management maturity towards the asset lifecycle cost. This research has led us to the conclusion that it is feasible to associate asset lifecycle cost and performance with the organization information management maturity by translating the case into a DBN. In general, this research can potentially lead to a better application on the maturity model and might be used for the organization decision process. This study is the first step towards enhancing our understanding of maturity model application and its implication towards the asset performance.

In the Netherlands, robust dike and dam design is a major concern in the context of flood defence. Due to heterogeneity of the subsoil on which these structures are founded, the validity range of in situ tests decreases drastically. Consequently, large uncertainties regarding spatial variation of soil stratification and soil layer parameters are incorporated in the cross-sectional reliability requirements, resulting in conservative designs. This thesis presents a Machine Learning application, which, by learning locally measured information and analysing high spatial resolution surface settlement data, can provide insights into spatial variation of soil stratification. Through the analysis of these insights, the uncertainties regarding spatial variability in cross-sectional reliability requirements can be reduced, which leads to less conservatism in dike and dam construction.