The Automated Parameter Determination project aims to provide advanced geotechnical models parameters from in-situ tests in a transparent and flexible process. The framework was initially developed for coarse-grained soils, and it was needed to be expanded to all types of common soils. This report presents the expansion of the APD database to deal with fine-grained soils, claylike soils specifically. The APD variability assessment framework is customised to deal with log-transformed correlations’ uncertainty. Moreover, it is found a large dependency on Atterberg limits for claylike soils parametrisation. Only one set of correlations from CPT database is found in literature to obtain these limits, for which a new set is developed based on critical state soil mechanics and the assumption that the CPT friction sleeve is similar to the remoulded undrained shear strength. The proposed correlation is validated with a published database, showing acceptable results with similar variability when compared to the existing equation. A first validation of the complete model parameters for fine-grained soils using Plaxis Hardening Soil with small strain stiffness model is achieved. The Plaxis Soil Test facility is used and the results are compared with triaxial and oedometer tests, showing good results in compressibility characterisation and low estimation of friction angle, possibly attributed to organic and silt content. The friction angle characterisation is discussed, and it is concluded that a better estimation for fine-grained soils is needed to be studied. Further studies on soils in between claylike and sandlike behaviour is needed, as well for organics.

In situ tests, such as the cone penetration test (CPT), are a popular tool for geotechnical engineers because they are an efficient and economical method for routine site characterisation, soil profiling and estimation of constitutive properties of soil. The main problem with interpreting in situ test results is the large amount of empiricism that engineers have to rely on. Furthermore, the rise in complexity of constitutive soil models have made soil interpretation from experimental data ever more challenging. Constitutive models in numerical analyses are used to simulate the stress-strain response of soils and each model is governed by a set of parameters that quantifies the mechanical behaviour of soil. A consequence for the increased complexity of a constitutive model is the increased number of parameters to be defined from a larger number of experimental tests. This is why parameter determination is still one of the most challenging tasks faced by geotechnical engineers. The challenges in soil interpretation from experimental data have led to an increasing demand for a more efficient parameter determination system for performing more reliable numerical simulations in geotechnical engineering. This study explores the applicability of graphs to develop a generic system for the determination of constitutive model parameters from in situ test results. Graphs are mathematical structures used to model pairwise relations between objects in a network and benefit from their ability to visualise complex problems. In the same manner, the use of graphs in a parameter determination system could generate valid relations, or paths, between parameters in a network. This should give the user of the system, i.e., the geotechnical engineer, both insight in and control over the system. The proposed strategy aims to increase the confidence of derived parameters from in situ test results. It should eventually provide guidance for the user in selecting the right constitutive model and corresponding parameters for the considered application, in order to use the full potential of numerical analysis. This study presents a proof of concept for an automated system to determine constitutive model parameters from in situ test results. Key aspects of the system are: transparency and adaptability. The system is kept transparent, since users are able to verify how available information (i.e., expertise by the engineer) is used by the system to arrive at a solution. The system is kept adaptable, since users can add their expertise into the system without having to make modifications to the system and since developers can easily expand the system in the future. This study illustrates how a system can automatically generate paths between parameters in a network (i.e., a graph),using the external database (e.g., a spreadsheet) as input by the geotechnical engineer. The focus of this system is on determining engineering parameters based on CPT data for coarse-grained soils. However, the universality of the system allows the system to be extended to a wider range of soils and in situ tests. Separate ongoing research efforts are devoted to further validating and tweaking of the system.

The determination of geotechnical parameters from in-situ tests heavily relies on the use of empirical correlations relating field measurements to soil properties. A large number of these correlations can be found across the literature, each of them yielding a different outcome for the parameter value. This results in a high variability of the potential results, which is not necessarily properly accounted for in the current geotechnical engineering practice. A new approach using graphs has recently been proposed by van Berkom [1] to automatically generate multiple parameter values based on a given set of correlations and equations. The present thesis assesses the quality of the estimates obtained from this new graph system and investigates how multiples outcomes can be combined into a unique result. The quality of the parameter’s estimates is appraised both in terms of accuracy or uncertainty, and in terms of validity. The combination of results from multiple methods showed that it is possible to either build confidence or distrust in the combined outcome depending of the consistency of the contributing results. As a result, this framework enabled a quantitative description of the inter-correlations variability. The conceptual framework has been then applied to geotechnical parameters and CPT-based correlations for coarse-grained soils. The range of applicability of the correlations (e.g. soil type, state of consolidation) is a critical factor that actively influences the final outcome of the system. This automatic system demonstrated its ability to produce parameter values relatively close to
the values obtained with the current practices. Further validation is required to assess the overall performance of the system on a broader scale.

In this study, the assessment of the KIJK dike follows the new guidelines given by POV-M 2018 using PLAXIS. The macrostability assessment and design of the dike is examined for two cases. In the first case the dike is assessed based on the in-situ conditions (Green dike) whereas in the second case a cantilever sheet pile wall is used in the design (Blue dike) to strengthen the dike. Prior to the analysis the interpretation of the available laboratory data that were executed according to the new protocol (WBI 2017) and the parameter determination of the necessary input parameters of the considered constitutive models (SHANSEP NGI-ADP, Hardening Soil, Soft Soil models) is established. The undrained shear strength (su) of the SHANSEP NGI-ADP model is based on the SHANSEP concept and the normalised su (S (NC, OC)) and the strength increase exponent (m) parameters are needed. For the HS and the SS models the effective strength parameters φ and c are required.
The FoS is determined with the use of the strength reduction method. Moreover, the CSSM framework is coupled with the SHANSEP (Stress History and Normalized Soil Engineering Properties) concept enabling the incorporation of the effect of stress history and the stress path characterizing the undrained shear strength in the design. The CSSM framework is applied in the design by determining the strength parameters of clays from an axial strain level equal to 25% under triaxial compression whereas for peats at 40% shear strain level under direct simple shearing conditions. In this study the strength parameters were additionally determined from the service conditions strain levels which are the 2% and 5% strain levels for clays and peats, respectively. The necessary strength parameters for the constitutive models are determined in the considered strain levels exposing their influence for both clays and peats. Moreover, the study includes the examination of the constitutive models at a single element level conducted in the Soil Test facility available in PLAXIS. When it comes to the design analysis, it was found that the SHANSEP NGI-ADP model fits properly the su determined from a cone penetration test. The HS and SS models based on the effective strength parameters may result in an undrained shear strength profile which deviates from the su that the soils exhibits in the field.
The study points out that both the strain level dependency of the strength parameters and the selection of the constitutive model at critical loading influence the results in terms of the developed failure plane and the FoS, especially in the case of Green dikes. The study also elaborates the response of the models in regard to the design requirements for the calculation of displacements and the structural forces. Finally, this study answers the knowledge gap regarding how the strain level influences the strength of the examined soils and how this should be translated in the design along with the explanation on the effects of the selected constitutive model on the results.

The uncertainties in undrained macro-stability analysis of dikes lead to overdimensioned and inefficient designs. The undrained shear strength (su¬), which describes the strength of clay and peat layers, is important information for the macro-stability analysis of a dike. The cone factor (Nc) gives a linear correlation between undrained shear strength (su¬) of the soil and the cone resistance (qc) from a cone penetration test (CPT)¬. In practice the uncertainty on this correlation, given by the variation coefficient, is high, especially it overestimates the su for high values of qc. As a result, a large reduction factor (RF) is taken into account between the expected value of su and the characteristic value of su used in calculations.
In literature the cone factor (Nc) is assumed to depend on the soil stiffness, the cone roughness and the initial soil stress state (∆). Including the initial soil stress state, or more specifically the horizontal soil stresses (σ’h0), in the cone factor determination can lead to a reduction of the variation coefficient. Based on literature and a numerical analysis it is found that including the initial soil stress state in the determination of Nc can lead to a difference of 10% in cone factor. However, the difference is less than 10% for most measures due to the relatively similar stress conditions over a large part of the cross section of a dike. In addition, a theoretical application of the initial soil stress state (Δ) shows that the overestimation of su for high values of qc cannot be solved by including it as found in literature.
A case study on the Hollandse IJsseldijk project has been conducted to back up the theoretical approach with experimental measurements. As a conclusion it is found that the variation coefficient is reduced slightly taking into account the initial horizontal soil stresses, resulting in a decrease of the reduction factor (RF) of 2-3%. Taking this small improvement and remaining unknowns in the calculation into account, it is concluded that including a measure of the in-situ soil stress state (Δ) in the determination of the cone factor (Nc) does not result in a significant reduction of the present uncertainties in dike assessment with existing approaches.