This thesis discusses the characterization of the undrained shear strength, S_u from the net cone resistance, q_net of clay in Dutch sites using Hierarchical Bayesian Modelling (HBM). The performance of the HBM is compared with the current practice methods of the site characterization which propose either the use of only site–specific observations (unpooled models) or the whole data simultaneously (pooled models). HBM can incorporate information from multiple sources such as prior knowledge of the engineers and behaviour met in the examined and the neighbouring sites. The use of different sources of information has been proposed by Eurocode-7 without providing a formal / mathematical procedure.
Literature studies have highlighted the potential benefits of incorporating the HBM into the characterization of the geotechnical parameter values. Therefore, this thesis aims to assess whether HBM can enhance the geotechnical decision-making by precisely quantifying the uncertainty in the geotechnical parameter values and making more accurate predictions of them. The impact of using input from the HBM results in a reliability analysis of a dike slope is examined as well.
First, a considerable number of paired q_net–S_u measurements is collected, and subsequently is divided into groups. Different statistical models are employed to describe this collected data. Two components characterize a statistical model; the functional form which is the relationship between S_u and q_net and the pooling family (pooled, unpooled and HBM), the method followed to train the statistical model parameters. The statistical models are applied in a comparative study to select the fittest one and to compare the behaviour of the HBM to the other pooling families. The comparative study is performed by applying the Bayesian Data Analysis (BDA) whose applicability is ensured by applying it in an artificial example using artificial data.
The first result of the BDA with real data is the comparison of the HBM with the current practice pooled and unpooled models suggesting the ln⁡〖S_u 〗-ln⁡〖q_net 〗 HBM as the fittest model. The HBM estimations for the statistical model parameters fall between the current practice’s methods and they experience lower uncertainty by borrowing information from the neighbouring sites to make site-specific estimations. Between the current practice and the HBM, the latter predicts the S_u with lower uncertainty.
The reliability analysis using input from the HBM yields different reliability indices than those proposed by the current practice models. This situation combined with the choice of the HBM after following the BDA workflow propose that the HBM can lead to safer and more economic design.
Overall, the use of the HBM for predicting the S_u from q_net with grouped data can be beneficial for the engineering practice. First, the HBM reduces the uncertainty of the statistical model parameters without inheriting extreme values and provides more certain prediction for the S_u accounting for the prior engineering knowledge and the behaviour met in neighbouring sites. Additionally, performing reliability analysis of a dike slope exhibits that the use of HBM derived values can suggest safer and more economic design over the standard approach.

This study focuses on the assessment of the reliability of the geobag wall system within the context of the Koningsgracht renewal project. The objective is to identify and understand the most sensitive phase during the project’s execution by conducting a comprehensive probabilistic analysis.

The geobag wall, a temporarily constructed component of Koningsgracht, emerges as the focal point of sensitivity in this study. Unlike other project elements, such as historic structures and conventional engineering components, the geobag wall possesses unique characteristics, notably its composition of individual geobags and the use of jute geotextile, which could result into individual instability.

The research delves into the analysis of failure mechanisms and limit states for the geobag wall, considering both the monolithic structure and potential local failures within its segments. The failure modes found include horizontal sliding, overturning and the rupture of the geotextile. Various parameters are examined to calculate factors of safety. To account for uncertainties inherent in geological and structural parameters, probabilistic methods are employed. Monte Carlo simulation and the First-Order-Second-Moment (FOSM) method are utilized to model the behavior of the geobag wall under different scenarios, encompassing a wide range of parameter combinations.

Correlations between parameters are introduced to simulate spatial variability, ensuring that the values of geological and structural factors align reasonably with one another. This approach reflects the real-world complexities of geotechnical systems. The analysis reveals intriguing results, with factors such as friction angle playing a significant role in horizontal sliding and overturning, while textile rupture remains relatively independent of geological parameters and heavily reliant on tensile strength of the jute geotextile. Additionally, wall dimensions, particularly height and width, are found to
exert a substantial influence on various failure modes.

Ultimately, the probabilistic analysis yields insights into the reliability of the geobag wall system. The study indicates a 1.625 · 10−4 probability of failure for the geobag wall system considering a Factor of Safety (FOS) of 1.0, aligning with the overall reliability of the Koningsgracht renewal method.

Dikes protect people and lands all around the globe. With rising sea levels, the importance of well-designed dikes has never been more essential. One of the main factors that can compromise the stability of dikes are macro-instabilities. Macro-instabilities can cause dikes to lose their water bearing potential, leading to floods. Methods are developed to as accurately as possible determine the probability that a macro-instability takes place in order to prevent it. Therefore, recent advancements include the remaining strength after macro-instability, which may be able to prevent flooding. The foremost methods to determine this remaining strength after macro-instability use D-Stability or the Material Point Method (MPM). Both D-Stability and MPM have advantages and disadvantages. D-Stability can quickly determine the probability that a macro-instability takes place, but cannot model the process of failure, and must therefore simplify this process to estimate the remaining strength. MPM on the other hand can accurately model what happens after a macro-instability, but has a much larger computational cost, especially for probabilistic computations. By supplementing D-Stability and MPM, this thesis proposes a method that exploits the advantages of both methods and mitigates the disadvantages. For a dike with a single clay layer, a connection was made between D-Stability and MPM, allowing dike profiles to be transferred back and forth. In order to make this connection, the SHANSEP undrained shear strength model was successfully implemented in MPM. By using the quick probabilistic D-Stability calculation and the post-failure modeling option of MPM, the probability of failure and the effect of failure can be quickly determined. By taking into account the effect of failure, the method can determine the probability of flooding, without simplifying the failure process. The method can also be used to determine if flooding via retrogressive failure or a larger single instability is more likely. The method was tested via a case study and verified via a RMPM Monte Carlo analysis. For the case study, the probability of flooding was 5.189*10-3 compared to an initial probability of failure of 7.22*10-1, a reduction in the order of 139. This probability of flooding compared well to the probability of flooding of 5.308*10-3computed using the more accurate and computationally expensive RMPM. Based on these first results, the proposed method is a viable method to assess the probability of flooding after macro-instability for clay dikes.

The application of reliability analysis in geotechnical engineering is relatively new compared to the other sections of civil engineering such as structural engineering and hydraulic engineering. However, due to its increases use in recent years, reliability analysis is planned to be included extensively in the upcoming Eurocode 7 (EN 1997). This research aims to compare the accuracy and efficiency between the applications of 22 selected reliability methods in 9 selected geotechnical engineering problems with various number of independent variables and modes of failure. The accuracy of the reliability methods are determined based on the Probability of Failure (Pf) errors, while the efficiency is based on the number of realizations (N) each method needs. The Monte Carlo Simulation is found to be the most accurate method despite its shortcomings in efficiency (ranked as the least efficient). Moreover, the FOSM method is found to be the most efficient despite its serious shortcoming in accuracy where it is also ranked as the most inaccurate. However, putting both accuracy and efficiency into account, the AK-MCS 0 order is proven to be the best method when applied to the discussed geotechnical engineering problems. The research also points out the necessity to perform multiple reliability methods for each geotechnical engineering problem.

The design and construction of quay walls are processes that exist for many centuries and have become more complex and challenging in current engineering practice. For the design of quay walls a number of guidelines and design codes have been developed over the years. These give the requirements that a quay wall structure should meet, but do also provide some guidance in which steps to take in order to arrive at a proper final design. The relevance of undrained soil behavior, described using critical state soil mechanics, for the analysis of quay wall stability is yet unknown. The main objective of this research is to investigate the possibilities to use the alternative design approach for modelling soil behavior in the design processes of a quay wall. For this, three case studies have been elaborated. The three case studies represents soil profiles consisting 1) predominantly sandy soils, 2) normally consolidated clay and 3) overconsolidated clay. The differences between the analyses and outcomes of the conventional approach and the new approach have been compared for each case study. Based on the quantitative results of case study 1 and 3, the difference in outcome between the conventional and alternative design approaches is between 0 and 10% for both displacements and sectional forces. The outcome of case study 2 is not in line with the results of case 1 and 3. Based on the results of the first case study with sandy soil profile, the alternative design approach applied in this report is not a valid option for the design of a quay wall due to the absence of undrained soil conditions.
For a soil profile consisting clay, the magnitude of preconsolidation of the soil plays an important role. For the alternative design approach, increasing values of pre-loading results in decreasing values of sectional forces and displacements of the wall. This effect is stronger in comparison to the conventional design approach. In further research the aim should be to increase the reliability of the alternative design approach. This can be done by using in-situ measurements of the displacements of the wall to validate if the model represents the reality accurately.

Recent development have caused that the policy regarding the installation of onshore wind turbines on embankments has changed to 'Yes, provided that ...' in the Netherlands. (Simplified) approaches are available within professional practice to analyse the risk of liquefaction, but are considered to be conservative. In this thesis, a methodology is formulated to model the key aspects of liquefaction of a soil layer underneath a dike system subjected to cyclic loading by an onshore wind turbine. The key aspects are defined as: cyclic loading, soil-structure interaction and consolidation behaviour. A modification to the model of Seed and Rahman (1978) is implemented in this thesis.
The applicable modelling conditions (quasi-static or dynamic) are investigated for the current situation. The analysis is performed using analytic and numerical models (Plaxis 2D). Both models conclude that the loads induced by the wind turbine can be modelled as quasi-static as the loads are sufficiently slow to neglect inertia effects. The influence of the cyclic loads by the wind turbine on the liquefiable soil layer is determined by the Cyclic Stress Ratio (CSR). The influence due to the soil-structure interaction is determined using a Finite Element Analysis (Plaxis 2D). The Hardening Soil small strain model gives a more accurate prediction of the CSR in the soil, as the soil response is stiffer during un/re-loading. The presence of the embankment results in various modes of shearing in the soil, e.g. triaxial compression, triaxial extension and direct simple shear. The CSR does not include the effect of static shear stresses and various modes of shearing in the soil. This effect should rather be accounted by the Cyclic Resistance Ratio (CRR). The consolidation behaviour modelled using the model of Seed and Rahman (1978) which applies the consolidation equation with generation term. The model is able to model partial consolidation, which is defined as a state where excess pore pressures can be generated and dissipate simultaneously. The generation term is based on an empirical relationship of the development of pore pressures. The model is implemented using a Finite Difference Method in a cylindrical coordinate system to represent the dissipation behaviour of a granular soil. The method allows to model the consolidation characteristics in radial and vertical direction, a layered soil, the load intensity and the loading frequency. As a result, the maximum pore pressure ratio in the soil reduces. A limitation of the model is its uncoupled nature. Therefore, no strains are determined. The constitutive behaviour inherent to the liquefaction phenomena, such as plastic deformations, is lacking. Oostpolderdijk is used as a case study to compare the modified method of Seed and Rahman (1978) to the reference engineering method and the method of Boulanger and Idriss (2014). The comparison with Boulanger and Idriss (2014) suggests that the modified model gives reasonable results. The application of the modified method results in a more favourable result compared to the reference engineering method. However, a sensitivity analysis shows that liquefaction can’t be ruled out because the sensitivity to permeability is high.

Given its geographical location and history, water defense is of utmost importance for the Netherlands. Structural Health Monitoring (SHM) offers a promising approach for system identification of hydraulic structures in this water defense system. The aim of SHM is to set sensors on structures and use the monitored responses to identify structural parameters of interest. However, many pertaining questions are unanswered concerning realistic hydraulic structures and monitoring systems: What type of sensors (e.g. strain gauge, SAAF, etc.) can and should be used in the monitoring system? How many sensors are needed, where and when to install these sensors? What is the influence of construction stages of structures on system identification? Considering the evaluation of a structure, what is the influence of system identification as well as construction stages on reliability (failure probability) of structures? Considering practical implementation: which computational algorithm is suitable and feasible? How to construct a proper surrogate model of the mechanical model to reduce computational time?
To answer these questions, a single anchored sheet pile wall is studied using a probabilistic approach. The sheet pile wall is modeled using the finite element (FE) method, synthetic data are used and Bayesian approach is adopted to cope with measurement uncertainty and model uncertainty. The information conveyed by sensors is quantified by the Kullback–Leibler (KL) divergence between prior and posterior distributions. Moreover, the correlation in model uncertainty of various structural responses is quantified by comparing a full-scale experiment from the literature and a corresponding calibrated 3D finite element model.
The results show that:
• A combination of different sensor types (in our case they are SAAF and strain gauge) should be used in the monitoring system (e.g. the combination of four different types of sensors outperforms the strain sensors on the sheet pile wall by conveying 40% more information with respect to the former); 
• Even limited number of sensors can convey sufficient information. In our case, 3 sensors placed at proper locations can convey 90% information carried by 6, 8 and 9 sensors considering different responses. They should be installed as early as possible;
• The failure probability computed using posterior from system identification largely decreases compared with that computed using prior (the ratio of prior and posterior failure probabilities can go up to 15¹⁰ in our case); 
• Delay of the start of monitoring during the construction stages decreases the information conveyed by sensors in system identification (the conveyed information can decrease by 50% in our case) and increases the computed failure probability in reliability analysis: the ratio of prior and posterior failure probabilities can be as large as 30¹⁰ ); 
• MultiNest performs well in Bayesian inference in high dimensional problems; 
• Gaussian process regression (GPR) with anisotropic radial basis function (RBF) kernel and white kernel as well as an adaptive infilling criterion is capable of constructing an accurate surrogate model even when it goes to high dimensionality. The error of surrogate model prediction can be explicitly explained.
To my knowledge the work presented in this thesis is the first application of combined system identification and reliability assessment for hydraulic structures, and the first detailed analysis of the effect of sensor installation time on system identification and structural reliability of hydraulic structures.
The findings imply that probabilistic system identification is a promising approach to substantially reduce our uncertainty in modelling hydraulic structures and in turns to increase their calculated safety. The approach has the potential to extend the working life of aging hydraulics structures and save costly strengthening and replacement. The analysis framework can also be applied to other structures in civil engineering.

Throughout the years the requirements of sheet pile walls have changed. Therefore reassessment of these structure's reliability is of importance. In this thesis, Bayesian updating is used for the reliability updating task. Updating processes require measurements of the structure under known conditions. Although for practical and economical reasons failure measurements of structures are seldomely available. Therefore the research focusses on whether it is possible to update a sheet pile wall's reliability using service domain measurements instead. Parameter updating methods generally return the statistically most likely parameter values for producing the observations. Using a theoretical sheet pile wall case, it is tested if the Bayesian updating method is able to effectively return the true soil parameter values as the most likely parameter set. The results show that the Bayesian updating method is very capable of approaching the used observations with the updated model response. Also the updated values of the most influential parameters show evolution in the direction of their true values. But the method does have difficulties with returning the true soil parameter values, even when applied to a theoretical case and with the use of elaborate observation configurations. Recommendations are given on further research concerning the use of the Bayesian updating method, the different influences on its performance and method application limitations.

Uncertainties in the soil parameters play a major role in the design of quay walls. In the current design approach, partial factors are prescribed to account for uncertainties in the soil, as well as for other types of uncertainties. This semi-probabilistic (level I) design approach needs to result in a reliable design for a range of quay structures and for multiple soil stratifications. It is therefore expected that, in general, this method results in overdimensioning of the structure. Whether this assumption holds, is investigated in this thesis by carrying out a reliability analysis for two quay walls in the Port of Rotterdam. The first case study covers a simple double-anchored combi-wall, whereas in the second case study a quay wall with relieving platform is considered.
Only the most relevant failure mechanisms were considered, which are yielding of the combi-wall, yielding of the anchor bar, shear failure of the grout body and soil mechanical failure. These failure mechanisms are complex soil-structure interaction problems. Therefore, both the soil and the quay structure have been modelled with the finite element program Plaxis 2D, using the Hardening soil model. For performing the probabilistic calculations on this model, the probabilistic module ProbAna has been used. This is a package developed by Plaxis which couples several types of reliability methods to the finite element software of Plaxis 2D. As the computational effort is relatively large when using FEM, the First Order Reliability Method (FORM) was used over sampling methods like Directional Sampling and Crude Monte Carlo simulation.
The results for the simple quay wall showed that the reliability level was sufficient for all considered limit states. Hence, almost all partial factors derived on this quay wall were lower than currently prescribed by the Eurocode. In the second case study, a quay wall with relieving platform, monitoring data of multiple years was used for calibration of the Plaxis-model. Thereafter, the reliability for the limit states yielding of the wall and soil mechanical failure was evaluated. It turned out that for both limit states, the reliability index was too low compared to the target reliability.
Although each case study concerned a different type of quay wall, the results reveal that choices made in the design, either optimistic or pessimistic, can have large influence on the reliability. Perhaps just as important, are the assumptions made regarding the stochastic description of the soil. It is still under discussion up to what distance soil parameters are correlated in space and how spatial averaging should be applied. Reference calculations showed that choices regarding the amount of independent soil layers and the degree of spatial averaging have a large influence on the reliability. More fundamental research to these topics is therefore recommended.