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By Yuejin Z., Guodong X.

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Extra resources for 3D magnetic field computation of a permanent magnet disc-type generator using scalar potential method

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We note two nontrivial difficulties with this approach and propose solutions, the efficacy of which will be demonstrated in the particular implementation discussed in this monograph. The unknown location of part of the boundary creates computational challenges. During the course of an iterative optimization procedure, simulations will be repeated many times for different locations of the unknown part of the boundary of 0. That is, iterative-based methods generally will involve changing domains and hence changing discretization grids in the usual finite element or finite difference approximation schemes.

The data are measurements of the electric field at points in the exterior domain Q,Q at discrete times. The simulation is a computed 16 Banks, Buksas, and Lin solution to Maxwell's equations with the constitutive laws for polarization, using candidate values of the geometric and material parameters. The criterion for optimization is a least-squares measurement of the difference between the simulation and the observed data given by The Ei are measurements of the electric field taken at specific locations and times.

The data are measurements of the electric field at points in the exterior domain Q,Q at discrete times. The simulation is a computed 16 Banks, Buksas, and Lin solution to Maxwell's equations with the constitutive laws for polarization, using candidate values of the geometric and material parameters. The criterion for optimization is a least-squares measurement of the difference between the simulation and the observed data given by The Ei are measurements of the electric field taken at specific locations and times.

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3D magnetic field computation of a permanent magnet disc-type generator using scalar potential method by Yuejin Z., Guodong X.


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