A fast multi-fidelity method with uncertainty quantification for complex data correlations: Application to vortex-induced vibrations of marine risers

We develop a fast multi-fidelity modeling method for very complex correlations between high- and low-fidelity data by working in modal space to extract the proper correlation function. apply this infer amplitude of motion flexible marine riser cross-flow, subject vortex-induced vibrations (VIV). VIV are driven an absolute instability flow, which imposes frequency (Strouhal) law that requires matching with impedance structure; is easily achieved because rapid parametric variation added mass force. As result, wavenumber spatial response within narrow bands uncertainty. Hence, error prediction can cause significant phase-related errors shape along riser, rendering low- high-fidelity complex. Working as outlined herein, dense from data, provided semi-empirical computer code VIVA, correlate few obtained experiments or fully-resolved CFD simulations, correct both phase provide predictions agree well overall response. also quantify uncertainty using Bayesian exploit formulate active learning strategy best possible location sensors providing high fidelity measurements.