1,721,216 research outputs found
A Hybrid Multiobjective Differential Evolution Method for Electromagnetic Device Optimization
No full textPurpose – The purpose of this paper is to show that the performance of differential evolution (DE) can be substantially improved by a combination of techniques. These enhancements are applicable to both single and multiobjective problems. Their combined use allows the optimization of complex 3D electromagnetic devices.
Design/methodology/approach – DE is improved by a combination of techniques which are applied in a cascade way and their single and combined effect is tested on well-known benchmarks and domain-specific applications.
Findings – It is shown that the combined use of enhancement techniques provides substantial improvements in the speed of convergence for both single and multiobjective problems.
Research limitations/implications – The increased speed of convergence may come at the price of a somewhat decreased robustness. However, such behavior is justified by the CPU time constraints under which the optimization has to be performed.
Practical implications – The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems.
Originality/value – This paper explorers the combined use of many of the most recent and successful algorithmic improvements to DE and applies them to both single and multiobjective problems
Robustness and generality issues in the generation of tetrahedral meshes for computational electromagnetics
No full textElectromagnetic Device Optimization with Stochastic MethodsStochastic Optimization - Seeing the Optimal for the Uncertain
Full text linkDevice optimization using metaheuristic methods has been successfully applied to
electromagnetic devices since their development in the early 1980s. Some recent examples of
the application of metaheuristics in electromagnetic device design include, among others,
genetic algorithms [Zaoui2007], evolution strategies [Coelho2007], Tabu search
[Cogotti2000], artificial immune systems [Campelo2006], particle swarm optimization (PSO)
[Ciuprina2002].
In this chapter the author summarizes some of his experiences in the use of two stochastic
optimization techniques which are very suitable to typical electromagnetic devices and
systems. First the algorithms are briefly introduced and then their application to typical
challenging problems, including Polymer Exchange Membrane Fuel Cells (PEMFC), high-
field-uniformity solenoids and Superconducting Magnetic Energy Storage (SMES) systems,
is presented
Electromagnetic optimization based on an improved diversity-guided differential evolution approach and adaptive mutation factor
No full textPurpose – The purpose of this paper is to show, on a widely used benchmark problem, that adaptive mutation factors and attractive/repulsive phases guided by population diversity can improve the search ability of differential evolution (DE) algorithms.
Design/methodology/approach – An adaptive mutation factor and attractive/repulsive phases guided by population diversity are used within the framework of DE algorithms.
Findings – The paper shows that the combined use of adaptive mutation factors and population diversity in order to guide the attractive/repulsive behavior of DE algorithms can provide high-quality solutions with small standard deviation on the selected benchmark problem.
Research limitations/implications – Although the chosen benchmark is considered to be representative of typical electromagnetic problems, different test cases may give less satisfactory results.
Practical implications – The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems.
Originality/value – This paper introduces the use of population diversity in order to guide the attractive/repulsive behavior of DE algorithms
Matrix properties of a vector potential cell method for magnetostatics
No full textIn this paper, a proof of the symmetry of the system matrix arising in a class of vector potential cell methods with non-symmetric material matrices is presented. Some remarks on how to construct other schemes with symmetric system matrices are also presented. The explicit expression of the matrix entries derived in order to prove the symmetry is also used to show that this matrix is identical to the one arising in the standard edge finite-element method. Finally, some remarks on discrete regularizations of these formulations are given
A Bianisotropic FIT Formulation over Polyhedral Grids for Metamaterial Modeling
No full textModeling bianisotropic constitutive equations, i.e. magnetoelectric coupling, in electromagnetics simulation is increasingly important, in particular in
metamaterials applications. This paper introduces for the first time such constitutive relationships in the framework of FIT and, furthermore, does so by allowing full generality in the discretization through arbitrary polyhedral grids. The resulting formulation is consistent, stable and preserves the thermodynamic properties of the bianisotropic constitutive equations thanks to the energetic approach used to construct the interpolating functions
Stochastic Methods for Parameter Estimation of Multiphysics Models of Fuel Cells
No full textThe accurate modeling of complex multiphysical devices and systems is a crucial problem in engineering. Such models are usually characterized by highly nonlinear equations and depend on a high number of parameters which often cannot be directly measured. In this paper two stochastic optimization techniques are adapted and compared to the solution of such challenging problems in the case of a reversible fuel cell system
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