Black, FelixSchulze, PhilippUnger, Benjamin2023-08-102023-08-1020212311-5521185804085Xhttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-134095http://elib.uni-stuttgart.de/handle/11682/13409http://dx.doi.org/10.18419/opus-13390We propose a new hyper-reduction method for a recently introduced nonlinear model reduction framework based on dynamically transformed basis functions and especially well-suited for transport-dominated systems. Furthermore, we discuss applying this new method to a wildland fire model whose dynamics feature traveling combustion waves and local ignition and is thus challenging for classical model reduction schemes based on linear subspaces. The new hyper-reduction framework allows us to construct parameter-dependent reduced-order models (ROMs) with efficient offline/online decomposition. The numerical experiments demonstrate that the ROMs obtained by the novel method outperform those obtained by a classical approach using the proper orthogonal decomposition and the discrete empirical interpolation method in terms of run time and accuracy.eninfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/510550article2021-09-13