New research by MIT scientists may help engineers design more resilient offshore platforms. Courtesy of the researchers
Machine-learning model provides risk assessment for complex nonlinear systems, including boats and offshore platforms. Seafaring vessels and offshore platforms endure a constant battery of waves and currents. Over decades of operation, these structures can, without warning, meet head-on with a rogue wave, freak storm, or some other extreme event, with potentially damaging consequences. Now engineers at MIT have developed an algorithm that quickly pinpoints the types of extreme events that are likely to occur in a complex system, such as an ocean environment, where waves of varying magnitudes, lengths, and heights can create stress and pressure on a ship or offshore platform. The researchers can simulate the forces and stresses that extreme events - in the form of waves - may generate on a particular structure. Compared with traditional methods, the team's technique provides a much faster, more accurate risk assessment for systems that are likely to endure an extreme event at some point during their expected lifetime, by taking into account not only the statistical nature of the phenomenon but also the underlying dynamics. "With our approach, you can assess, from the preliminary design phase, how a structure will behave not to one wave but to the overall collection or family of waves that can hit this structure," says Themistoklis Sapsis, associate professor of mechanical and ocean engineering at MIT.
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