This paper presents a topology optimization method for multimaterial models based on the normalized Gaussian network (NGnet). In this method, one can determine optimal shapes of machines which are composed of various materials such as iron, magnet and nonmagnetic material. The present method is applied to the optimization of interior permanent magnet motor to determine the distributions of magnetic core and flux barrier as well as magnets. The optimization results show that average torque can be improved using as small amount of magnet as possible. In addition, characteristic of the present method is discussed in detail.Index Terms-interior permanent magnet motor, topology optimization.

No abstract

Abstract-This paper discusses properties of the curl-curl matrix in the finite element formulation with edge elements. Moreover the observed deceleration in convergence of the CG and ICCG methods applied to magnetostatic problems through the tree-cotree gauging is explained on the basis of the eigenvalue separation property. From the eigenvalue separation property it follows that neither minimum nonzero eigenvalue of the curl-curl matrix nor maximum one increase through the tree-cotree gauging. Hence it is concluded that the condition number of the curl-curl matrix tends to grow by its definition. Moreover the maximum eigenvalue tends to keep constant whereas the minimum nonzero eigenvalue reduces. This property also makes the condition number worse.

The model reduction based on the method of snapshots is applied to the finite element analysis of three dimensional transient eddy current problems. It is known that accuracy of the reduced model highly depends on the number of snapshots. In this paper, we introduce a novel method which determines the adequate number of snapshots automatically. It is shown that the computational time can be reduced when using the model reduction based on the present method.Index Terms-Model order reduction, method of snapshots, proper orthogonal decomposition, finite element method, eddy current problem.

This paper presents the topology optimization of a synchronous reluctance motor using the normalized Gaussian network. In the optimization, the average torque and iron loss are considered. In the resultant motor, the area of the rotor surface adjacent to the stator is found to be reduced when the weight for the iron loss is sufficiently large. On the other hand, large flux barriers present in the rotor when the average torque is maximized without considering the iron loss.

This paper presents parameter and topology optimization of inductor shapes using evolutionary algorithms. The goal of the optimization is to reduce the size of inductors satisfying the specifications on inductance values under weak and strong bias-current conditions. The inductance values are computed from the finite-element (FE) method taking magnetic saturation into account. The result of the parameter optimization, which leads to significant reduction in the volume, is realized for test, and the dependence of inductance on bias currents is experimentally measured, which is shown to agree well with the computed values. Moreover, novel methods are introduced for topology optimization to obtain inductor shapes with homogeneous ferrite cores suitable for mass production.Index Terms-Finite-element (FE) method, immune algorithm, inductor, microgenetic algorithm, topology optimization.

Abstract-This paper discusses convergence of the incomplete Cholesky conjugate gradient method (ICCG) which solves edge-based finite-element equations for quasi-static electromagnetic fields. It has been observed in numerical computations that convergence of ICCG for the A-V method is faster than that for the A method. This phenomenon is found to be explained by the fact that, in the A-V method, the preconditioning eliminates the small singular values which deteriorate the condition number while they remain after the preconditioning in the case of the A method.Index Terms-Eddy current, edge element, finite-element method, ICCG, singular value.

In trans-1,3-butadiene, the ultrafast relaxation from the doubly excited state 2(1)Ag and the corresponding recovery of the ground state 1(1)Ag were observed simultaneously for the first time by time-resolved photoelectron spectroscopy (TRPES) using 29.5 eV high harmonic pulses. The fast recovery of 1(1)Ag shows that the following dissociation upon photoexcitation takes place after returning to the ground state. At 427 fs after photoexcitation, only the ionization energy from the C═C σ bond was found to remain shifted. Accompanying theoretical calculations with an assumption of Koopmans' theorem show that the ionization energy of the C═C σ bond is modulated by vibrational excitation of the antisymmetric C═C stretching mode. TRPES by high harmonics can probe the changes in the molecular structure sensitively.