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Sand densification around the pile has traditionally been regarded as an explanation for the grain migration and soil subsidence that often occur around cyclic laterally loaded piles embedded in sand. Supported by new empirical evidence, this paper proposes that, additionally to some soil densification around the pile, the main cause for the continuous "steady-state" grain migration is a convective cell flow of sand grains in the vicinities of the pile head. Such convective flow would be caused by a ratcheting mechanism triggered by the cyclic low-frequency lateral displacements of the pile. Furthermore, the experimental results suggest that the limit between the convective cell and the static soil is marked by a distinct direct shear surface. This might shed some light into the complex phenomena related to the pile-soil interaction in the upper layers of the bedding, which are normally the main contributor for the lateral load-bearing capacity of piles.

A mechanical structure supported by nonlinear springs subjected to an external load is considered. If all mechanical parameters of the system were known, the displacement of the system subjected to this load could be easily calculated. If not all of the parameters are known, but the load and the displacement are measured at one location, an inverse problem exists. In the presented problem the nonlinear springs are unknown and have to be determined. At first glance a problem needs to be solved, which is underdetermined due to the number of unknown variables. However, evolutionary computing can be applied to solve this inverse, nonlinear and multimodal problem. Sometimes a prior knowledge exists on certain system properties, which is difficult to implement into analytical or numerical solver. This knowledge can play a decisive role in identifying the system properties and it can be easily included as boundary condition when applying evolutionary algorithm. This article examines how and under what conditions the spring resistances can be identified. The procedure is exemplified at a mechanical system of a pile foundation.

A comprehensive numerical model for the analysis of offshore foundations under a general transient loading is presented here. The theoretical basis of the model lies on the Swansea formulation of Biot's equations of dynamic poroelasticity combined with a constitutive model that reproduces key aspects of cyclic soil behaviour in the frame of the theory of generalised plasticity. On the practical side, the adoption of appropriate finite element formulations may prevent the appearance of spurious numerical instabilities of the pore pressure field. In this respect, the use of a coupled enhanced-strain element is here proposed. On the other hand, the practicality of the presented model depends ultimately on its computational efficiency. Some practical recommendations concerning the solution strategies, the matrix storage/handling procedures and the parallel multi-processor computation are here provided. Finally, the performance of the model with a benchmark study case and its practical application to analyse the soil–structure interaction of an offshore monopile under a realistic transient storm loading are discussed.

This paper deals with the system identification of a mechanical structure supported by nonlinear springs subjected to an external load. If all mechanical parameters of the system were known, the displacement of the system subjected to this load could be easily calculated. However, the monitoring applications often deal with the inverse problem. The loads and displacements of the system are known and certain mechanical Parameters of the system are sought. The solution of such inverse problems can be difficult, especially when they have a nonlinear and multimodal character, which often makes them appear intractable at first sight. However, evolutionary computing can be applied to solve this inverse, nonlinear and multimodal problem. Sometimes a prior knowledge exists on certain system properties, which is difficult to implement into analytical or numerical solvers. This knowledge can play a decisive role in identifying the System properties and it can be easily included as a boundary condition when applying evolutionary algorithms.
This article discusses how and under what conditions the unknown spring resistances can be identified. The practical application of this procedure is exemplified here with the mechanical system of a pile foundation.