Built environments developed on compressible soils are susceptible to land deformation. The spatiotemporal monitoring and analysis of these deformations are necessary for sustainable development of cities. Techniques such as Interferometric Synthetic Aperture Radar (InSAR) or predictions based on soil mechanics using in situ characterization, such as Cone Penetration Testing (CPT) can be used for assessing such land deformations. Despite the combined advantages of these two methods, the relationship between them has not yet been investigated. Therefore, the major objective of this study is to reconcile InSAR measurements and CPT measurements using machine learning techniques in an attempt to better predict land deformation.

@en

Water fluxes in slopes are affected by climatic conditions and vegetation cover, which influence the effective stress and stability. The vegetation cover is the intermediate layer between the atmosphere and the slope surface that alter water balance in the slope through evapotranspiration and leaf interception. This paper studies the datadriven approach for predicting the macro stability of an example grass-covered dike based on actual data and also synthetic data provided by numerical modelling. Two numerical models are integrated in this study. The water balance in the root zone is simulated through a crop model, whereas the hydro-mechanical and safety analysis of the example dike is done using a two-dimensional Finite Element model. The considered period for these analyses is 10 years (3650 daily instances) which will be used to generate a time-series dataset for a secondary dike in The Netherlands. The features included in the dataset are parameters that (i) have a meaningful relationship with the dike Factor of safety (FoS), and (ii) can be observed using satellite remote sensing. The output dataset is used to train a Random Forest regressor as a supervised Machine Learning (ML) algorithm. The results of this proof-of-concept study indicate a strong correlation between the numerically estimated FoS and the MLpredicted one. Therefore, it can be suggested that the utilized parameters can be used in a data-driven predictive tool to identify vulnerable zones along a dike without a need for running expensive numerical simulations.@en

A novel pile-driving technique, named Gentle Driving of Piles (GDP), that combines axial low-frequency and torsional high-frequency vibrations has been developed and tested recently. During the experimental campaign, several piles were installed onshore, making use of the GDP shaker. Besides those, a number of additional piles were installed using conventional pile-driving techniques, i.e. impact piling and axial vibratory driving. After the completion of the installation phase, the installed piles have been subjected to impact hammer tests with the following goals. First, the in-situ dynamic properties of the pile-soil system have been identified. Second, the post-installation soil state has been investigated, along with its evolution in time for each pile driving scenario. Preliminary analyses, of the data collected during the impact tests show dissimilar trends in the overall dynamic response between the piles installed with impact hammer and those installed with the axial and the GDP shakers.This observation suggests a difference in the post-installation dynamic behaviour of the pile-soil systems related to different pile-driving techniques. In this paper, a first attempt is made to identify the differences in the overall pile-soil dynamic behaviour of the piles installed by means of the three different pile-driving techniques.

@en

In this study, installation of jacked piles in sand is simulated using Press-Replace Method (PRM) and Material Point Method (MPM) and the results are compared together. This comparison is important because a realistic and yet efficient simulation of installation of jacked piles is an appealing step towards the design and analysis of this type of displacement piles. It is shown that PRM as a method that is founded on small-strain finite element method can produce pile and soil responses that are in a promising agreement with those of MPM which is a finite-deformation analysis method.@en

This paper presents a semianalytical solution for axially loaded pile groups in multilayered, linear-elastic soil profiles. The piles in the group can have circular, square, or rectangular cross sections. The soil displacement surrounding a pile group is linked to the axial displacement experienced by each of the piles in the group. The method is based on assigning a displacement decay function to every pile in the group and then summing up for all piles in the group the product of the axial displacement of each pile and its associated decay function. The governing differential equations describing the response of the soil and piles are derived by applying the principle of virtual work and calculus of variations to the pile-soil system. The governing differential equations predicting the response of the piles are solved analytically using the method of eigenvalues and eigenvectors, whereas the differential equations describing the soil decay functions are solved numerically using the finite-difference method. The method produces displacement fields that are very close to those produced by the FEM but with less computational effort.

@en