An A.O.D. (Automated Optimal Design) method for the design of inductors for levitation or molten metal confinement is presented. It can modify the geometry of the inductor systems which produce the exciting electromagnetic field, until a specified performance is achieved. A number of constraints can be taken into account, both related to technical parameters, such as insulation thickness and conductor cross-sections, and to designer choices aimed at directing the optimization process toward preferential solutions. Global and local equilibrium equations are used for levitation and confinement, respectively. The algorithm operates as a relaxation method, modifying the turn positions one at time, step by step. At every step the non-linear inverse problem is linearized and solved as a least square problem and the performance of the solution is checked. A second order parabolic interpolation is used, if the least square solution is not satisfactory. Some examples of applications are given and discussed.
An Optimization Procedure for Electromagnetic Confinement and Levitation Systems
LUPI, SERGIO;DUGHIERO, FABRIZIO;GUARNIERI, MASSIMO
1993
Abstract
An A.O.D. (Automated Optimal Design) method for the design of inductors for levitation or molten metal confinement is presented. It can modify the geometry of the inductor systems which produce the exciting electromagnetic field, until a specified performance is achieved. A number of constraints can be taken into account, both related to technical parameters, such as insulation thickness and conductor cross-sections, and to designer choices aimed at directing the optimization process toward preferential solutions. Global and local equilibrium equations are used for levitation and confinement, respectively. The algorithm operates as a relaxation method, modifying the turn positions one at time, step by step. At every step the non-linear inverse problem is linearized and solved as a least square problem and the performance of the solution is checked. A second order parabolic interpolation is used, if the least square solution is not satisfactory. Some examples of applications are given and discussed.Pubblicazioni consigliate
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