This work proposes the ROMES (Reduced-Order-Model Error Surrogates) method for statistical closure modeling of reduced-order models for stationary systems. The method constructs statistical models to characterize the error incurred by reduced-order …
This work presents a technique for statistically modeling errors introduced by reduced-order models. The method employs Gaussian-process regression to construct a mapping from a small number of computationally inexpensive 'error indicators' to a …