Optimization of electrostatic lens systems using genetic algorithms

Abstract (2018)
Author(s)

N. Hesam Mahmoudi Nezhad (TU Delft - ImPhys/Charged Particle Optics)

M. G. Niasar (TU Delft - DC systems, Energy conversion & Storage)

A. Mohammadi Gheidari (TU Delft - ImPhys/Charged Particle Optics)

T.M.L. Janssen (TU Delft - Discrete Mathematics and Optimization)

CW Hagen (TU Delft - ImPhys/Charged Particle Optics)

Pieter Kruit (TU Delft - ImPhys/Charged Particle Optics)

Research Group
ImPhys/Charged Particle Optics
More Info
expand_more
Publication Year
2018
Language
English
Research Group
ImPhys/Charged Particle Optics
Pages (from-to)
24-25
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

To optimize the design of a system of electrostatic lenses can be quite challenging. Especially when many lens electrodes are involved, the number of design parameters, such as electrode thickness, radius, gaps between electrodes and voltage, increases rapidly. Therefore, it would be really helpful when optimization routines can be used. There have been some attempts to develop optimization programs, such as Szilagy et al. [1] and Adriaanse et al. [2], but they used to be not very accurate. In the meantime, computers have become much more powerful, making it attractive to revisit the problem. In this work we apply a Genetic Algorithm [3] for the optimization, and MATLAB was chosen for coding.

Files

Paper_CPO_SPI_2018_ver12.pdf
(pdf | 0.307 Mb)
License info not available

Download not available