Data Fusion for Jack-Up Wind Load Prediction

Abstract In this study, wind load on a typical jack-up is calculated through CFD simulation and measured through wind tunnel tests for operational condition (OC) and extreme condition (EC). The Reduced Order Method (ROM) model is built up based on high fidelity CFD simulation results. Two data assimilation models, ROM-based Gappy POD and Extended Kalman Filter (EKF) model, are developed to fuse the measured data from wind tunnel tests with the numerical results for jack-up wind load predictions. The outcomes show that both the EKF and gappy POD are able to predict the wind loads on the jack-up platform under OC and EC with satisfying accuracy, even with only 21 measurement data. The findings of this study provide an option for fusing the numerical simulation results with wind-tunnel measurements or operational data for accurately predicting the wind load on marine vessels and offshore platforms.