Authors:
Colin Ribton
1
and
Wamadeva Balachandran
2
Affiliations:
1
TWI Ltd and Brunel University London, United Kingdom
;
2
Brunel University London, United Kingdom
Keyword(s):
Optimisation, Electron, Modelling, Evolution.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolution Strategies
;
Evolutionary Computing
;
Evolutionary Multiobjective Optimization
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
The design of high quality electron generators is important for a variety of applications including materials processing systems (including welding, cutting and additive manufacture), X-ray tubes for medical, scientific and industrial applications, microscopy, and lithography for integrated circuit manufacture. The many variants of electron gun required, and the increasing demands for highly optimised beam qualities, demands more systematic optimisation methods than offered by trial and error design approaches. This article describes the development of evolutionary algorithms to enable the automatic optimisation of the design of vacuum electron guns. The gun design usually is required to meet specified beam requirements for the applications of interest, so within this work, beam characteristics from the calculated electron trajectories, for example brightness, intensity at focus and beam angle, were derived and used as a measure of the design fitness-for-purpose. Evolutionary paramet
ers were assessed against the efficiency and efficacy of the optimisation process using an analogous design problem. This novel approach offers great potential for producing the next generation of electron guns.
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