Structure-preserving reduced-order modelling of Korteweg de Vries equation
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Computationally efficient, structure-preserving reduced-order methods are developed for the Korteweg de Vries (KdV) equations in Hamiltonian form. The KdV equation is discretized in space by finite differences. The resulting skew-gradient system of ordinary differential equations (ODEs) is integrated with the linearly implicit Kahan's method, which preserves the Hamiltonian approximately. We have shown, using proper orthogonal decomposition (POD), the Hamiltonian structure of the full-order model (FOM) is preserved by the reduced-order model (ROM). The quadratic nonlinear terms of the KdV equation are evaluated efficiently by the use of tensorial methods, clearly separating the offline-online cost of the FOMs and ROMs. The accuracy of the reduced solutions, preservation of the Hamiltonian, momentum and mass, and computational speed-up gained by ROMs are demonstrated for the one-dimensional KdV equation, coupled KdV equations and two-dimensional Zakharov-Kuznetzov equation with soliton solutions
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