This thesis focuses on 76 pairs of Cone Penetration Tests and boreholes that include Kreftenheye, out of a full database of nearly 200 pairs from TNO - Geological Survey of the Netherlands, generally reaching depths up to 40 meters. The thesis presents this analysis, showing the geological and geotechnical patterns and variations within the Kreftenheye Formation and how the integration of geological and geotechnical knowledge can lead to more effective engineering designs.

Quay walls are often designed with Finite Element models (FE models) to take into account the complex soil-structure interaction and highly non-linear soil behavior. However, the effect of temperature variations is uncertain if it is taken into account in the design of the quay walls at the Port of Rotterdam.

Nowadays, new quay walls are often equipped with sensors that collect information about their behavior. These quay walls are known as smart quay walls. The measurement data of smart quay walls could be used to validate FE models and reduce parameter uncertainties. This could lead to an optimization of the functionality of the quay walls.

Smart quay walls have been observed to show much higher strain levels in the anchors during summer compared to the winter period. According to strain records, differences of up to 10% and 20% seem to be present, which is quite high. The objective of this thesis is to verify the effect of temperature on anchor force in quay walls using the data of smart quay walls.

The data analysis that took place analyzed data from five different quay walls (HHTT, SIF, EMO, Brammen terminal, Brittanniëhaven). Deformations, strains, anchor forces, groundwater levels and temperatures are some of the measurements that were investigated in order to understand the quay wall reaction to the seasonal temperature fluctuation effect. The most useful measurement data proved to be the deformations of the combi walls and the anchor forces in the MV-piles.

This research will eventually highlight the results of the extensive data analysis from different smart quay walls, while it will further prove that quay walls are affected by the effect of seasonal temperature fluctuation. The gain is that with the available data, it is verified that the wall is moving back and forth depending on the season. However, the deformations are minor compared to the deformations of the dredging period.

After data analysis, a FE model was set up to predict the deformations and anchor forces of the quay wall during seasonal temperature fluctuations. For the parameter determination, CPTs, later research projects, design records and triaxial tests were used. Regarding the FE model, the case that was used is the HES Hartel Tank Terminal (HHTT-quay), which is a smart quay wall in the port of Rotterdam. HHTT quay wall was selected as the most well monitored quay wall regarding the needs of this research. Moreover, the HHTT-quay consists of sections with and without a relieving platform. Both types were considered in this thesis.

Then comes the validation of the FE model with the measurement data. Moreover, having a FE model in PLAXIS 2D which can realistically model the cycle heating effects, could be used both to estimate deformations due to climate change effect, as well as the anchor forces leading to better quay wall design for the future.

As with all of the cycle effects, heating and cooling of the quay wall could cause deformations that after many years of operation of a quay wall could lead to excessive deformations. Additionally, increasing temperature will cause higher temperature fluctuations, which means larger cycles. Therefore, further research with more cycles, better quality data and a FEM that could calculate the cycle heating effects is crucial to a better understanding of the cycle phenomenon.

The Dutch pile design method, NEN9997-1, classifies screw and screw-injection piles as fully displacing. For these pile types, the design code prescribes a base factor αp 0.63 and shaft factor αs in sand of 0.009. However, an ongoing TU Delft research programme on these pile types has indicated findings conflicting with NEN9997-1. This thesis investigates whether screw and screw-injection piles should be classified as fully displacing piles and how the design process can be improved, through the interpretation of existing load tests.
The thesis compares measurements of pile load tests to the load-settlement behaviour of fully displacing and (partly) soil replacing piles, including the effect of limiting qc to a maximum of 15 MPa for shaft friction. From appropriately instrumented tests, αp and αs factors are determined and compared to the prescribed factors. Additionally, a shear box test is performed in order to investigate debonding between the grout body and steel tube of a screw-injection pile.
Interpretation of the load tests strongly signify that the load-settlement behaviour of screw and screw-injection piles does not resemble that of fully displacing piles, but rather (partly) soil replacing piles. Determined values of αp range from 0.23 to 0.35, while values for αs in sand range from 0.011 to 0.012. Limiting qc along the shaft is shown to produce less realistic capacity and behaviour predictions when compared to measured test data. The shear box experiments indicate that in dense soils with high qc values, debonding between the grout and steel tube of a screw-injection pile under high load can occur.

In recent years, distributed fiber optic sensing (DFOS) technology has been widely used in monitoring the strains developed in the structures.
The main focus of this report is to identify strains distribution while hammering/
jacking pile and analyzing the uncertainties between the theoretical, measured strain through datalogger in concrete and steel piles. This assessment is done to gain confidence over the feasibility of using DFOS technology. Fiber optic cables are embedded all along the length of the concrete and steel piles with ends connected to the datalogger. To confirm the accuracy of the datalogger, other strain measuring devices like load cell and strain gauges are also glued to the piles. For both the piles load with in the yield limit is applied and strains are measured. fTb 2505 datalogger posses high accuracy with lower spatial resolution where as Luna Odisi datalogger has high spatial resolution and less accuracy which can be directly reflected through the strains obtained from both datalogger. Results obtained from steel pile reflects that strains obtained from Luna Odisi datalogger and load cell matches with in the accuracy and with no slippage . But for concrete piles fTb 2505 datalogger shows more fluctuating strains as compared to the strain gauges with uncertainties included in both the devices.

The Port of Rotterdam (PoR) is the largest port in Europe and in order to maintain its status, it would need to expand. For the expansion, an extensive survey of the subsurface is needed for the construction of new port areas and its geotechnical structures. As part of designing the geotechnical structures, the subsurface is often modelled as multiple homogeneous soil layers. However the soil properties are in reality heterogeneous and spatially variable. The spatial variability of a soil property is characterized by a mean, a standard deviation and the scale of fluctuation. The scale of fluctuation is the distance over which a soil property is significantly correlated and it is limited to the soil layer of that soil property. Therefore the change in the geological layering of the soil because of external depositional factors such as river, sea and wind can influence the scales of fluctuations and the resulting geotechnical design.

The objective of this thesis is to look at the spatial variability in the vertical direction of the Pleistocene sand from the Kreftenheye and Boxtel Formation in the Port of Rotterdam and see if the river Meuse has any influence on the spatial variability in the vertical direction. An additional question is asked if the spatial variability has any influence on the computation of the pile base capacity for a single foundation pile and what are the implications of the answer to that question. To answer these questions, four sites in the Maasvlakte, Botlek and Pernis were selected and the cone penetration tests (CPTs) taken at the twelve sites were used for this thesis. An empirical method which uses CPT data to identify soil layers was used to identify the Pleistocene sand layer in the CPT data. The first part of the thesis uses the cone resistance data of the CPTs to estimate the spatial variability of the sites. The second part of the thesis focuses on the additional research question by using random field theory. Per site, the mean, standard deviation and vertical scale of fluctuation θ_v were used to generate simulations of cone resistance data. For each combination of standard deviation and θ_v 500 simulations were carried out. For each simulation the pile base capacity was computed with two CPT-based averaging methods, Koppejan method and LCPC method. The coefficient of variation of pile base capacity is used to measure the uncertainty of the computed pile base capacity.

The results show that the range θ_v values are: 0.26 – 2 m in the Maasvlakte, 0.24 – 1.76 m in the Botlek and 0.14 – 1.18 m in Pernis. In terms of the mean θ_v, you see a gradual increase from the upstream area (Pernis) to the downstream area (Maasvlakte). The increase is from 0.27 – 0.63 m in Pernis to 0.64 – 0.80 m in Botlek to 0.84 – 1.86 m in Maasvlakte. However, it is not clear if this is due to the Meuse or due to the existence of sublayers in the geological formation or due to some other factor. Further investigation is needed before a conclusive answer can be given. The answer for the second part is that as long θ_v is significantly larger than the pile diameter D (θ_v ≥ 4D), it does not influence the uncertainty of the computed pile base capacity. However, the mean and standard deviation of cone resistance does influence the uncertainty of the computed pile base capacities. Finally, it is observed that spatial variability does not play a role in the uncertainty of the computed pile base capacity if the coefficient of variation of the cone resistance c_v (q_c) is small (c_v (q_c) ≤ 0.15). The implication for the uncertainty of the computed pile base capacity and therefore the pile design is that one can afford to have a less accurate description of the spatial variability from using fewer CPTs if θ_v ≥ 4D. The same holds true if c_v(q_c) ≤ 0.15.