Real-time dynamic and structural behavior estimation of a steel lazy wave riser through finite-element-based digital twin and hull-motion sensor

Abstract

A digital twin (DT) method is proposed to estimate the dynamic and structural behaviors of a Steel Lazy Wave Riser (SLWR) under environmental conditions. This method uses a 1D finite element (FE) riser model that can include various loads and boundary conditions measured from sensors. We selected a spread-moored Floating Production Storage and Offloading (FPSO) vessel to validate the proposed method, which hosts multiple Production and Injection SLWRs. Using the time-domain dynamics simulation program, we built a reference model considering the fully coupled FPSO with mooring lines and risers in various wind/wave/current conditions. The synthetic sensor data, which represents the motions and internal fluid density changes, were generated from the simulation of the reference model. Then, two riser DT models, the Top Oscillation Model (TOM) and the Two-Point Oscillation Model (TPOM), were built, considering only a single riser made of the 1D FE model. TOM employed vessel motions as boundary conditions while internal fluid density and ocean current could be inputted as external loads. TPOM incorporated an additional motion sensor attached to the riser. The motion data obtained from the reference model were first inputted into the respective riser DT models. Next, we further evaluated their performance with and without the estimated ocean currents and slugs of internal fluid. The time histories, spectra, and statistical data of displacements and stresses along the riser were systematically compared and analyzed for various test cases and environments. While the hull-motion sensor alone can provide practically acceptable results using the developed methodology, additional consideration of current load and internal fluid's density variation improves the overall riser monitoring performance. The present method can significantly reduce the number of sensors compared to traditional riser monitoring methods.