Abstract
Slamming events are the source of critical design loads for small, high-speed craft. Categorization of slamming events can prove useful by identifying cases of interest for more in-depth analysis, such as high-fidelity modeling and experiments. Inspired by developments in facial recognition techniques, a quantitative method is proposed to sort slamming events using various experimental measurements. A singular value decomposition method on a matrix assembled of vectors of time-histories of rigid body motions recorded in free-to-heave-and-pitch tow tank experiments on a planing hull. While some of the categories identified in this work show distinct features in slamming accelerations consistent with previously identified categories, other categories have also been identified. These results can be used when evaluating ride quality, and design loads, and performing more in-depth studies on specific slamming categories.
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