Assessment of classical and approximated models estimating regular waves kinematics. (1st November 2016)

• Record Type: Journal Article
• Authors: De Serio, Francesca; Mossa, Michele
• Is Part Of: Ocean engineering. Volume 126(2016)
• Page Start: 176
• Page End: 186
• Publication Date: 2016-11-01
• Subjects: Regular waves -- Kinematics -- Theoretical models -- Approximate models; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2016.09.005
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: The planning and management of many coastal activities require the knowledge of the wave mechanics in a target area. Many theoretical models have been developed to describe the evolution of a regular wave, with different levels of accuracy, but it is hard to evaluate which model is the most suitable one to reproduce a precise marine process. In this regard, an experimental program, started up at the Technical University of Bari, aims to provide some useful references to practitioners in the field. The present work enriches the existing experimental dataset and analyzes two new experimental regular breaking waves, examined in the shoaling zone. Their cross-shore and vertical velocities have been measured together with their elevations by means of a 2D Laser Doppler Anemometer and a resistive gauge, respectively. Several classical theories and approximate methods have been used to reproduce the waves kinematics, in order to test their validity and applicability. Mainly, the study outlines that i) an increasing error in the reproduction of the wave kinematics is observed while increasing its non linearities; ii) approximate methods tend to better perform in comparison with classical theories, even if in some cases they are more sensitive to the surface boundary conditions. Highlights: Classical and approximated models for reproducing regular waves kinematics are analyzed. Errors generally increase with increasing non linearities. The linear method in frequency domain provides the best estimates.