Nonlinear data-driven model order reduction applied to circuit-field magnetic problem

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Pierquin, Antoine | Henneron, Thomas

Edité par HAL CCSD ; Institute of Electrical and Electronics Engineers

International audience. As in most of the domains in physics, finite element formulation is a very common method for electromagnetic fields computation. Since many years both proper orthogonal decomposition and empirical interpolation method are also often used in a model order reduction context. If these methods are efficients, their application is intrusive because it requires an access to the matrices and the assembly step. To avoid such an aspect, a data-driven model order reduction based on proper orthogonal decomposition with an approximation of the nonlinear terms by radial basis functions interpolation is applied to a magnetostatic problem coupled with circuit equations. The nonlinear reduced order model only needs solutions of a finite element analysis to be generated.

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