The Amaliahaven project in the Port of Rotterdam involves the construction of quay walls and a back crane track. Given the enormous quantities of foundation piles and anchors included in the design, it was decided to collect and store the installation data in a uniform and structured manner. The goal was to improve quality control and support site supervision through efficient data analysis and, in addition, to acquire new knowledge. This paper presents a framework for automated data collection and validation. Despite the high level of automation, manual verifications of the data through Site Acceptance Tests remain crucial. The data of driven foundation piles can be used quite easily by site supervisors and geotechnical engineers when assessing the load-bearing capacity of these piles. In fact, the initial knowledge from the coarsemeshed CPT grid is updated with additional insights obtained from the fine-meshed pile installation grid. For grouted anchors, there is significant improvement potential to create added value based on the recorded data. The findings of this paper can play a crucial role in the quality control procedure of foundation piles and can serve as direct input for reverse engineering of quay walls, and presumably also for other types of port infrastructure.@en

In this study, driving records of 18 open-ended steel tubular piles installed in dense sandy soil conditions at five sites in the Netherlands were utilized to evaluate models that are currently used in practice for predicting the static soil resistance during driving (SRD), as well as a recently developed method, known as the Unified Method. Since the Unified Method is a static axial capacity-CPT-based design method, slight modifications to the originally proposed formulas were examined to allow estimation of the SRD. This paper presents a modified format of the Unified Method and its performance is assessed by comparing predicted with measured hammer blow count profiles. It is eventually shown that the modified Unified Method leads to overall improved blow count predictions compared to current approaches.@en