Characterizing the soil uncertainty in the Port of Rotterdam for the probabilistic design of a pile foundation

Abstract

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.