Improving predictions of vortex induced vibrations via generalizable hydrodynamic databases across several current incidence angles

Vortex induced vibrations is a withstanding ubiquitous problem in the marine industry. Although seemingly simple, cylindrical structures in cross-flows originate extremely complex and, at times, chaotic hydrodynamics which are not fully understood nowadays. One of the biggest industries driving economic development that has had to deal which this problem is Offshore Oil & Gas. Key to a safe oil extraction, marine risers have to operate and withstand the erratic process that arises from the fluid-structure interaction of marine risers with vortex induced hydrodynamic forces. In the following paper we put forward a methodology to assimilate large amounts of data into empirical models. In doing so, we hope to bring attention to the potential that sensors and data collected by them can have in improving predictions of VIV phenomena. Although we leverage a semi-empirical VIV prediction tool (VIVA), the optimization methods used to extract robust hydrodynamic databases for a Steel Catenary Riser (SCR) are not limited to this method. The performance of the extracted databases are systematically cross-validated. To the authors' best knowledge, an extensive cross-validation of this methodology has not been performed in previous studies.