We propose a novel trajectory-optimized cluster-based network model (tCNM) for nonlinear
model order reduction from time-resolved data following Li et al.[“Cluster-based network
model,” J. Fluid Mech. 906, A21 (2021)] and improving the accuracy for a given number of
centroids. The starting point is k-meansþþ clustering, which minimizes the representation
error of the snapshots by their closest centroids. The dynamics is presented by “flights”
between the centroids. The proposed trajectory-optimized clustering aims to reduce the …