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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.
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.
Offshore piles have to withstand predominantly cyclic axial loads when they are installed in multi-pile configurations, as in jacket foundations. The dimensions of the pile are governed by both the internal capacity and the fatigue behaviour of the steel cross-section as well as by its external capacity in the pile-soil interaction. Owing to the large numbers of piled foundations required for current and future offshore wind farms, there is an urgent need to optimize the dimensions and related costs of single piles. With regard to the pile capacity, two major topics of research are the determination of possible capacity gains due to pile ageing effects and proper consideration of cyclic degradation. In order to investigate both effects, a large-scale testing facility has been constructed at the BAM TTS site in Horstwalde near Berlin. This open-air facility allows large tubular driven piles to be loaded cyclically in both tension and compression while studying the ageing effects by introducing delays between the testing campaigns. First results already show a moderate increase in pile capacity over time. Concerning the anticipated capacity degradation of cyclically loaded piles, preliminary results show an unexpected behaviour. Additional tests are currently being conducted for further clarification.