Foundations of buildings ensure the safety and serviceability are upheld. A common type of
foundations used in the Netherlands is pile foundations which are typically founded on a thick sand layer in the subsurface. These pile foundations are the focus of this thesis and more specifically the methods used to design such foundations. This thesis aims to give a better understanding of the resistance of closed-ended piles in a layered soil by comparing existing pile design methods to the measured forces from the Drukpaal jacking machine. Drukpaal jacks precast concrete piles into the soil and the records collected give a valuable insight in the pile resistance in various locations and soil profiles with layered soil in the Netherlands.

The design of a pile foundations consists of the combination of two different types of methods. One will predict the base capacity of the pile foundations and the other will predict the shaft capacity. These two capacities together give the predicted bearing capacity of the pile. However, multiple base capacity and shaft capacity methods exist with varying influence zones and with that varying degrees of accuracy. In this thesis the different base and shaft capacity methods used are all based on the tip resistance as measured by a CPT. The following base capacity methods are included: Koppejan, LCPC, Filter method and the Filter method as adapted by Munta de Boorder (in this thesis referred to as the Munta de Boorder method). And for shaft capacity the NEN method and the ISO method are used.

This thesis aims to answer the following research question: What combination of capacity prediction methods for shaft and tip resistance works best to estimate the total force over depth as measured by Drukpaal?.
This question will be answered by a series of simulations of different projects completed by Drukpaal, which is a company which jacks piles into the ground and records the required force over depth.

The measurements and simulations for the various sites were compared both visually and
statistically. The Filter method with ISO gives the best visual fit.
For the statistical analysis the coefficient of variance (COV) is taken as well as the root mean squared error (RMSE) of the ratio line of the simulation (simulation divided by the measurement). Here the COV will account for the shape and the RMSE will account for the overall error. The sum of these two values is used to determine the best fit, since both of these values should be as small as possible. From this analysis it is found that Filter method in combination with ISO is overall the best combination, followed by Munta de Boorder with ISO and Filter method together with NEN.

The last aspect to be looked at is the location dependency of the combination of methods. From this it was found that the base capacity methods in combination with NEN vary a lot over the measured locations and these combinations are thus location dependent. For the base capacity, the LCPC method was also found to be location dependent in combination with ISO. So even though this combination worked really well for one of the projects (Gorinchem) it is not dependable to use because of the varying degrees of accuracy. The other three combinations; Koppejan, Filter method and Munta de Boorder together with ISO, were all found to be location independent. However, Koppejan with ISO garnered quite high values for RMSE and COV, meaning that this combination is not very accurate.

Overall, Filter method with ISO was found to give the best fit which was location independent. Munta de Boorder with ISO followed and Koppejan with ISO was found third best fit. The other combinations were found to be location dependent and thus are, based on the work in this thesis, less suitable for application in The Netherlands.