Ice-induced vibration response forecast research of economical jacket platform based on machine learning methods
Sea ice may cause severe vibration and damage to economical jacket platform in ice regions.Therefore,the accurate and rapid forecast of sea ice factors is the key to sea ice management.This study builds anice-induced vibration risk forecast mode of offshore jacket platforms.A short-term forecast model of ice-induced vibration response is presented by combining field monitoring,environmental forecasting,and Elman neural network methods.Data for the winters of 2013-2014,2017-2018,and 2018-2019 are adopted to train the forecast model,and the short-term extreme response forecastis provided for offshore flexible platforms.The results show that the forecast model takes into account the influence of the ice direction on the ice-induced vibration response and avoids the uncertainty of simplification of the ice load and structure model in numerical analysis.The average forecast error of the ice environment-extreme vibration amplitude model is less than 20%,which meets the requirements of engineering applications.
万方数据
维普
