Berm recession is a key factor governing the stability and design of berm breakwaters, which are commonly categorized as Hardly Reshaping (HR), Partly Reshaping (PR), or Fully Reshaping (FR). Many experimental formulas were introduced for predicting berm recession; most of them are not well suited for a probabilistic design. This study employs an extensive database to develop probabilistic formulas for the reliability design of PR and FR breakwaters. For this purpose, the influences of sequential storms on cumulative berm recession were incorporated by homogenizing data from rebuilt and cumulative tests. Bayesian Linear Regression (BLR) method was then applied to derive a comprehensive prediction formula, which was evaluated against existing empirical models. Afterwards, sensitivity analysis using Sobol indices was conducted to quantify the contribution of individual parameters. The proposed model demonstrates high accuracy and robustness across a wide range of conditions. To address the lack of reliability-based design tools, a simple BLR design formula considering only the stability number was also developed, introducing safety margins through statistical standard deviations. The performance of this simplified formula was assessed in comparison with available methods using the Active Learning and Monte Carlo simulations for a real case. The introduced concept provides a novel practical approach for reliable design of berm breakwaters.
扫码关注我们
求助内容:
应助结果提醒方式:
