A Collection of Large-Scale Benchmark Models for Nonlinear Model Order Reduction

We provide a publicly available collection of sixteen large-scale benchmark nonlinear state-space models in this contribution. The models are written in the MATLAB language and are scalable in spatiotemporal degrees of freedom. The aim is to provide the active research community with a suite of high-dimensional nonlinear models to test the state-of-the-art nonlinear model reduction strategies. We also review some of the most-widely employed reduction methods for these models. Furthermore, we also present some parametric nonlinear models to design and validate parametric model reduction schemes.