A Bayesian approach to the quantification of extremal responses in simulated dynamic structures

Prediction of the extremal responses of dynamic structures is a vital step in the risk management of offshore assets. Often when modelling structural response the outputs are dependent on covariates defined on a continuous input domain. We demonstrate a methodology to allow for continuous covariates in extremal modelling by building latent variable models, whereby output dependencies are incorporated by smooth processes in the latent parameters. This allows information from close-by input regions to be shared when forming inference at unseen inputs. We illustrate the methodology using a computational simulation of Floating Production Storage and Offloading (FPSO)vessel motions, modelled as functions of the peak wave period. We provide methodologies and diagnostics for the modelling of the time-domain maxima, quantiles, and threshold exceedance data. There are three contributions made by this research: a methodology to predict the extremal outputs from a time-domain simulator, with incorporation of continuous covariate knowledge; significant speed increase when using the developed methodology as a computational proxy to the simulator; and a framework for the probabilistic quantification of the output uncertainty of the extremal data.