Wave attenuation
Wave attenuation on World Data Ocean: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on wave attenuation in some way — the news, the analysis, the deep dives, and the occasional surprise find. A Global Hub for Ocean Intelligence 4 World Data Ocean is a centralized digital platform where researchers, scientists, and ocean enthusiasts converge to explore, analyze, and… New stories are added to this page as we find them, so check back if you want to keep up with what is happening around wave attenuation, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything World Data Ocean is covering right now.
Wave transmission and reflection by multi-row submerged restored oyster reefs: laboratory experiments and empirical predictive formulas
Restored oyster reefs offer a promising nature-based solution for coastal protection, yet hydrodynamic design guidance for multi-row configurations remains limited. This study presents empirical data and predictive formulas derived from laboratory experiments examining wave transmission and reflection across impermeable, porous, and screened porous reef layouts. Analysis of wave transmission coefficient (Kt), reflection (Kr), and dissipation (Kd2) reveals that screened porous reefs consistently demonstrated the lowest transmission levels within the tested parameters, providing practical guidance for optimized reef design.
Explicit wave height prediction model and regularity analysis for floating breakwaters based on deep symbolic regression
Accurate wave height prediction is critical for coastal engineering and aquaculture safety. This study validates a novel approach utilizing Physical Symbolic Optimization (PhySO) to model wave attenuation behind floating breakwaters. Employing real-world data from Fujian Province, the research developed explicit, interpretable formulas for significant (Hs) and maximum (Hmax) wave height prediction. Notably, the Hmax model achieves accuracy comparable to complex machine learning methods, while incident wave height emerges as the dominant controlling factor, demonstrating PhySO’s value in balancing precision and practical application.