Hybrid intelligent and numerical methods to estimate the transmission coefficients of rectangular floating breakwaters

• Published in: Water science & technology. Water supply Vol. 24; no. 9; pp. 3015 - 3030
• Main Authors: Karami, Hojat, Saghi, Hasan
• Format: Journal Article
• Language: English
• Published: London IWA Publishing 01.09.2024
• Subjects: Algorithms; Aspect ratio; Breakwaters; Data transmission; Design specifications; Floating; Floating breakwaters; Fluid mechanics; Fluid-structure interaction; Harbors; Least squares; Mathematical models; Methods; Numerical methods; Performance evaluation; Regular waves; Search algorithms; Support vector machines; Velocity; Viscosity; Water depth; Wave energy; Wave height; Wave power; Wave tanks
• ISSN: 1606-9749; 1607-0798; 1607-0798
• DOI: 10.2166/ws.2024.175

Breakwaters are used to reduce incoming wave energy at harbors and shorelines. This paper presents a comparison of novel two-dimensional hybrid intelligent models for the idealization of the effects of waves on the performance of moored rectangular floating breakwaters (FBs). Fluid structure interactions (FSIs) were idealized by airy-type monochromatic regular waves generated in a numerical wave tank. The coupled Volume of Fluid-Fast Fictitious Domain (VOF-FFD) interpolation method was used to evaluate FB motions. Different forms of Least Squares Support Vector Machine Methods (LSSVMs) that utilized 183 data streams were used to model FB performance for different wave height-to-water depth ratios, dimensional aspect ratios, and specific length-to-water depth ratios. Of those, 80% were used to train the model and 20% to test it. Parametric studies have shown that during training a Least Squares Support Vector Machine Method-Bat Algorithm (LSSVM-BA) with R2 = 0.8725, MAE = 0.0276, and RMSE = 0.0488 presents the most appropriate model for the evaluation of FB performance. Notwithstanding this, during testing a Least Squares Support Vector Machine Method-Cuckoo Search (LSSVM-CS) Algorithm with corresponding values of 0.6841, 0.0519, and 0.0708 performs better.