On the recession of berm breakwaters

Le résumé fourni par la source

Berm breakwaters are coastal structures with a rather wide armor layer made of a wide range of stone sizes. These structures are allowed to reshape in response to wave action and as a result, become more stable. Prediction of berm breakwaters' recession is one of the most important tasks in the design of berm breakwaters. Hence, several experimental studies have been carried out on the stability of berm breakwaters and several formulas for predicting the recession are obtained based on them. First, the existing databases were scrutinized to provide a comprehensive databank. Then, it was used to develop a new formula for the berm recession, which includes effects of most important structural characteristics such as front slope, berm height, armor size, density and grading as well as sea state parameters such as wave height, wave period, and water depth. The proposed formula's physical reasoning and accuracy metrics indicated that it outperforms existing formulas, especially in the practical range, i.e., shallow waters with recession between 0.5 and 10 times the armour size. A sensitivity analysis of the Sirevåg berm breakwater was conducted to illuminate the performance of various formulas and the influence of different parameters, Additionally, design recommendations are provided for practitioners. • A comprehensive recession data bank within the design range was provided. • Sigurdarson and Van der Meer's (2013) formula was found to be the simplest and most accurate existing formula for berm breakwaters' recession. • A robust formula was introduced to predict the berm recession based on the governing parameters. • Sensitivity analysis was conducted using a real word case to provide more insight into the behaviour of different formulas. • Design formulas and their ranges of applicability are also provided for the practitioners.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.