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Optimization of electromagnetic devices: Circuit models, neural networks, and gradient methods in concert (abstract) : 37th Annual conference on magnetism and magnetic materials (1993)

Ratnajeevan, S. ; Hoole, H.

[S.l.] : American Institute of Physics (AIP)

Journal of Applied Physics 73 (1993), S. 6802-6802

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ISSN: 1089-7550

Source: AIP Digital Archive

Topics: Physics

Notes: Optimization in designing electromagnetics is now increasingly better understood. As opposed to classical circuit models of magnetic circuits, today, gradient techniques for mathematical optimization have been proposed and are used. These techniques, while being expensive, are exact. More recently, artificial neural networks have been suggested, but they work best only if the data set of parameter-set, performance pairs for training the network is close to the optimal solution we seek. In this paper, it is shown how all three methods may be used in concert to increase efficiency. The circuit model is used to generate an approximate inverse solution. Then direct finite element solutions are used to generate the required training set and this is used with the Neural network to get a better solution. This solution is finally used as a starting point for the gradient optimization scheme which converges quickly because the starting point is close to the actual solution.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1063/1.352489

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A structural mapping technique for geometric parametrization in the optimization of magnetic devices (1992)

Weeber, Konrad ; Ratnajeevan, S. ; Hoole, H.

Chichester [u.a.] : Wiley-Blackwell

International Journal for Numerical Methods in Engineering 33 (1992), S. 2145-2179

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ISSN: 0029-5981

Keywords: Engineering ; Engineering General

Source: Wiley InterScience Backfile Collection 1832-2000

Topics: Mathematics , Technology

Notes: The continuity and differentiability of object functions is a basic prerequisite for the application of gradient methods in optimization. However, for parameters defining the shape of an electromagnetic device, the finite element discretization in the field analysis introduces discontinuities into the object function which slow down the convergence rate. Additionally, depending on the geometric parametrizaiion employed, the optimization frequently yields shape contours that are impracticable for manufacturing purposes. This paper investigates the problems inherent in geometric parametrization and shows that the discontinuities in the object function are caused by changes in mesh topology as the geometric parameters vary; these changes inevitably follow from the use of free meshing algorithms. As a solution to these shortcomings a structural mapping technique is outlined that maps surface displacements onto the parameters of the finite element mesh and obtains the parameter dependent geometric variations without a change in mesh topology. This resulting geometric parametrization yields continuous object functions without artificial local minima and results in smooth surface contours of the optimized device. Using this new parametrization technique, design sensitivity analysis, is shown to be a reliable and essential part in the efficient application of gradient methods for shape optimization.

Additional Material: 16 Ill.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1002/nme.1620331010

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