Search results

Global optimization in electrical engineering using stochastic methods requires usually a large amount of CPU time to locate the optimum, if the objective function is calculated either with the finite element method (FEM) or the boundary element method (BEM). One approach to reduce the number of FEM or BEM calls using neural networks and another one using multiquadric functions have been introduced recently. This paper compares the efficiency of both methods, which are applied to a couple of test problems and the results are discussed.

The common approach to continuous and discrete optimisation problems in electromagnetics does not take into account uncertainties and variations of the design variables. Local sensitivity analysis is usually performed only after the optimisation run to study the behaviour of the objective function in the neighbourhood of the optimum. However, this procedure may prove inefficient if the optimum has to be rejected due to sensitivity considerations and a new run has then to be performed. In this paper an alternative approach, which takes into account uncertainties in the design variables and physical data, is presented, and an analytical function is used to highlight the features of the proposed method. The essence of the technique is to couple the optimisation with a series of worst case analyses which are embedded in the optimisation loop. The method is fully general and can be applied to any optimisation method. The additional computational costs associated with the procedure maybe relatively high, but in the authors’ opinion the obtained gains in user confidence in the solution and the computational savings in some cases far offset the possible drawbacks of the method.

To show a possible implementation of surface impedance boundary conditions (SIBCs) in a time domain formulation based on the cell method (CM).

The implementation is based on vector fitting (VF), a technique which allows a time domain representation of a rational approximation of the surface impedance to be found.

It is shown that very little computational effort is needed to find a very good VF approximation of simple SIBCs and that such approximation is easily fitted into existing CM codes.

The extension to higher order SIBCs has not been taken into account.

The proposed approach avoids the use of convolution integrals, is accurate and easy to implement.

This paper introduces the use of VF for the approximate time domain representation of SIBCs.

An enhanced version of a mixed field‐based formulation for magnetostatics previously developed by the authors is presented and its features are discussed. The formulation minimises the residual of the constitutive equation, and exactly imposes Maxwell’s equations with Lagrange multipliers. Finite elements satisfying the physical continuity properties for both the magnetic and the magnetic induction fields are used in the numerical approximation. The possibility of decoupling the formulation in two separate sets of equations is discussed. A preconditioned iterative method to solve the final algebraic linear system is presented. Finally, a very natural refinement indicator is defined to guide an adaptive mesh refinement procedure.

The capability of discontinuous finite element methods of handling non‐matching grids is exploited in the simulation of rotating electrical machines. During time stepping, the relative movement of two meshes, consistent with two different regions of the electrical device (rotor and stator), results in the generation of so‐called hanging nodes on the slip surface. A discretisation of the problem in the air‐gap region between rotor and stator, which relies entirely on finite element methods, is presented here. A discontinuous Galerkin method is applied in a small region containing the slip surface, and a conforming method is used in the remaining part.

Discusses the combined use of a modified version of the global optimization technique simulated annealing and a deterministic optimizer based on Shor’s method. Describes the features of the proposed technique and reports on some results regarding a standard benchmark problem.

The purpose of this paper is to simulate in the time domain three‐dimensional electrical, thermal, mechanical coupled contact problems arising in electric resistance welding (ERW) processes.

A three‐dimensional multiphysical numerical model for analyzing contact problems is proposed. Electrical and thermal field equations in bulk domains are discretized with the cell method (CM). Welding resistance at contact interfaces is described locally by synthetic statistic parameters and contacting domains are matched together by a non‐overlapping domain decomposition method. Contact pressure distribution is resolved by a finite‐element procedure. The model is validated with 3D FEM software package.

The semi‐analytical model describing the electric and thermal resistances at contact interfaces can be easily embedded in CM formulations, where problem variables are expressed directly in integral form. Compatibility conditions between contact members are enforced by a domain decomposition approach. System conditioning and computing time are improved by a solution strategy based on the Schur complement method.

The electrical‐thermal analysis is not coupled strongly with the mechanical analysis and contact pressure distribution is assumed to be not depending on thermal stresses, which can be considerable near the contact area where localized joule heating occurs.

Resistance welding processes involve mechanical, electrical, and thermal non‐linear coupled effects that cannot be simulated by standard commercial software packages. The proposed numerical model can be used instead for designing and optimizing ERW processes.

The paper shows that numerical modeling of ERW processes requires a careful prediction of the localized joule heating occurring at the electrode‐material interface. This effect is reconstructed by the proposed approach simulating coupled electrical, thermal, and mechanical effects on different spatial scales.

An adaptive FEM for 3D magnetostatic problems involving non‐linear materials and permanent magnets is presented. The problems are formulated in terms of scalar potentials and discretized on a tetrahedral mesh using linear shape functions. Local error is estimated by approximately solving an independent differential problem in each tetrahedral element.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

Uncertainties in the design variables of non‐linear engineering optimization problems are often neglected. That could result in considerable deterioration of the target function value of an implemented design compared with the computed optimal solution. This effect can be reduced with robust optimization, where it is tried to achieve robust designs by actively embedding the uncertainties and robustness measures in the optimization process. A methodology for robust optimization of non‐linear problems is presented, including practical methods for the solution of such programs. The benefits of the approach are discussed in a numerical field calculation example.