Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/68577
Title: Electron beam dynamic study and Monte Carlo simulation of accelerator-based irradiation system for natural rubber vulcanization
Authors: P. Apiwattanakul
S. Rimjaem
Authors: P. Apiwattanakul
S. Rimjaem
Keywords: Physics and Astronomy
Issue Date: 1-Mar-2020
Abstract: © 2020 Elsevier B.V. This research focused on an electron beam accelerator system for natural rubber vulcanization. In this accelerator, electrons are generated from a 17-keV DC gun and accelerated in a 5-cell RF linac with a resonant frequency of 2996.39 MHz and an effective length of 22.15 cm. The RF macro-pulse has a length of 4 μs with a maximum repetition rate of 200 Hz. Electron beam dynamics in the linac were studied using software ASTRA. It was found that the electron beam can be accelerated to have average kinetic energy in a range of 1–3.86 MeV for accelerating gradients of 16.2 to 39.5 MV/m. This accelerating range corresponds to the RF peak powers of 0.32–1.49 MW. The beam dynamic simulation results were used as the inputs for GEANT4 Monte Carlo simulation of electrons in the irradiation system. The beams exit the linac and collide with a 50-μm titanium window. Then, they travel through 18 cm of air and penetrate in the rubber latex with optimal depths of 0.3–1.3 cm for electron beam energies of 1–3.85 MeV. At the rubber surface, rectangular apertures with well-defined effective area were considered to select the beams with more uniform transverse distribution. The effective volumes defined from the optimum depth and the effective irradiation area are 0.01–6.29 cm3 to obtain the required absorbed dose in a range of 50–150 kGy. The results from this study can be used to determine the parameters and conditions of the machine and the irradiation system for the practical operation.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078547311&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/68577
ISSN: 0168583X
Appears in Collections:CMUL: Journal Articles

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