Advanced Computational and Design Techniques in Applied by Song-yop HAHN (Eds.)

By Song-yop HAHN (Eds.)

This symposium was once all for complex computational and layout ideas in utilized electromagnetic platforms together with units and fabrics. The scope of the complaints hide a large choice of themes in utilized electromagnetic fields: optimum layout suggestions and purposes, inverse difficulties, complex numerical innovations, mechanism and dynamics of latest actuators, physics and functions of magnetic levitation, electromagnetic propulsion and superconductivity, modeling and functions of magnetic fluid, plasma and arc discharge, high-frequency box computations, digital machine simulations and magnetic fabrics

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094mm, respectively. So, L r is very small, the allowable iteration time is 5 times. 4. CONCLUSIONS The analysis using automatic shape design produced the following results. (1) Automatic shape design of the solenoid valve can be calculated using the Newton method and the régula falsi method for bath response time of command reference and minimized response time. (2) For the optimum design, our numerical analysis is very effective. (3) In this model, the allowable iteration for both response times is 5 times.

Design Optimization Environment The two fundamental functional bodies in the presented design optimization process are the analysis tool and the search algorithm. They continuously interact. For every new set of design parameters the search algorithm suggests, the analysis tool creates the specific model and provides the field solution. In the proposed technique, the GA performs the search operation and the FEM carries out the analysis. A diagram of the procedure is given in Figure 1. 44 A GA starts the search from an initial population of a certain number of members.

The optimization is based on the survival of the string structures from one generation to the next. Strings that are better suited to the environment, the objective function, are more likely to survive. A new improved generation is created using the bits of information from the survivors of the previous generation. For the optimal design of electromagnetic devices, the applicability of several search methods including artificial neural networks, and evolution strategies, were studied [2-4]. Although there is a well established theory on GAs, resulting from extensive research in other areas of science, they are relatively new to design optimization of electromagnetic devices.

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