Litcius/Paper detail

Magnetic Field Simulation With Data-Driven Material Modeling

Herbert De Gersem, Armin Galetzka, Ion Gabriel Ion, Dimitrios Loukrezis, Ulrich Romer

2020IEEE Transactions on Magnetics28 citationsDOIOpen Access PDF

Abstract

This article develops a data-driven magnetostatic finite-element (FE) solver that directly exploits the measured material data instead of a material curve constructed from it. The distances between the field solution and the measurement points are minimized while enforcing Maxwell's equations. The minimization problem is solved by employing the Lagrange multiplier approach. The procedure wraps the FE method within an outer data-driven iteration. The method is capable of considering anisotropic materials and is adapted to deal with models featuring a combination of exact material knowledge and measured material data. Thereto, three approaches with an increasing level of intrusivity according to the FE formulation are proposed. The numerical results for a quadrupole-magnet model show that data-driven field simulation is feasible and affordable and overcomes the need of modeling the material law.

Topics & Concepts

SolverLagrange multiplierComputer scienceAnisotropyMagnetostaticsMinificationMagnetic fieldField (mathematics)Material propertiesMultiplier (economics)Applied mathematicsComputer simulationMechanicsSolid modelingMagnetNumerical modelsMagnetic domainNumerical analysisAlgorithmMathematical optimizationModeling and simulationPhysicsData modelingModel Reduction and Neural NetworksMagnetic Properties and ApplicationsElectromagnetic Simulation and Numerical Methods