Sensor arrays strategically deployed on various offshore structures may provide valuable information in addressing issues related to the complex dynamic response behavior due to varying environments, changing hydrodynamics and purposely attached engineering devices. The current work was devoted to developing techniques to (1) optimize the sensor array according to specific engineering goals, (2) use response data obtained from the sensors to evaluate structures‟ extreme responses, (3) extract modal parameters, and (4) analyze strength conditions. The computational tool developed in this study integrated genetic algorithms, modal recognition techniques, damage detection methods, time series and spectral analysis methods. Genetic algorithms, originally proposed for solving optimization problems based on natural selection, have demonstrated capabilities in obtaining the optimal sensor array configurations in extracting a single mode or two modes simultaneously. This finding laid the foundation for further modal recognition and damage analysis.
The first application discussed herein focused on response evaluation of long and flexible subsea transmission lines; specifically, evaluating the performance of flow-induced vibration suppression devices and buoyancy elements. With laboratory data, the study demonstrated that airfoil fairings, ribbon fairings and helical strakes can all effectively suppress the undesired vibrations in a uniform current; however, the first two devices were not quite effective, especially airfoil fairings, when the structures were subjected to combined loads of current and waves (though all devices significantly increased the damping). In addition, the study showed modal parameters extracted with optimized sensor arrays can help detect, locate and size damages in a structure via numerical simulation (though the performance of the methodology may decrease with localized non-uniform strength profiles and excessive marine growth).
The second application extended the methodologies from 1-D beam-like structures to 2-D plate-like structures. These studies focused on strength analyses of various ice sheet formations. The results illustrated, in spite of the exponentially increased computational volume, fine-tuned genetic algorithms can still locate near optimal sensor arrays regardless of boundary conditions and placement restrictions due to complicated Arctic environments. Furthermore, the damage detection methodology utilized herein proved to be able not only to detect weak regions but also to detect strengthened areas in ice sheets, for example an ice ridge, thus complete strength analyses of selected ice sheet formations can be conducted
