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http://hdl.handle.net/11375/27218
Title: | Optimization and Characterization of Bi-detector Coincidence Beta-ray Spectrometer |
Authors: | Sun, Ruoyu |
Advisor: | Byun, Soo Hyun |
Department: | Radiation Sciences (Medical Physics/Radiation Biology) |
Keywords: | Beta spectroscopy;Coincidence operation;Monte Carlo simulation |
Publication Date: | 2021 |
Abstract: | With the recent change of the equivalent dose limit for the lens of eyes from 150 to 20 mSv/yr., averaged over 5 years, it is of great importance to investigate the beta-ray spectrum in the maintenance areas of the nuclear power plants, where workers are exposed to mixed beta-gamma fields. A beta-ray spectrometer consisting of a thin silicon detector and a plastic scintillator has been developed, which can accept only beta detection events while rejecting gamma events via coincidence. Based on the spectroscopy system that has been built, a comprehensive upgrade of software and hardware has been conducted. The data acquisition software MC2 was replaced with CoMPASS, developed by CAEN to achieve higher stability and functionality. Optimal shaping parameters and coincidence time window were determined by instruction and sample tests. The fast event signal from the plastic scintillator does not provide enough energy information. Therefore, three approaches were executed, including adding a capacitor, adding a preamplifier, and changing the digital pulse processor to solve the problem. The method of changing digitizer was accepted as the final solution to obtain the best spectrum through benchmark tests. The experimental measurements characterized the response of the beta-ray coincidence spectrometer under the mixed beta/gamma radiation field with a various count rate ratio from 0.00625 to 0.8. Experimental result shows excellent and stable performance of the detector system under a higher beta to gamma ratio. Gamma contribution of the coincidence spectrum, especially in low energy region, significantly increased when beta count rate was controlled to a minor level. Monte Carlo simulations are also carried out using the MCNP6 code to validate the measurements. |
URI: | http://hdl.handle.net/11375/27218 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Sun_Ruoyu_202111_MSc.pdf | Master Thesis | 4.26 MB | Adobe PDF | View/Open |
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