Quantitative basis for component factors of gas flow proportional counting efficiencies

Monte Carlo simulation;Beta spectra;MCNP5;Gas flow proportional counter;Calibration;Uncertainty budget;ICRU

Nichols, Michael ; Mechanical Engineering

University:Georgia Institute of Technology

Department:Mechanical Engineering

关键词: Monte Carlo simulation;    Beta spectra;    MCNP5;    Gas flow proportional counter;    Calibration;    Uncertainty budget;    ICRU;   

Others  :  https://smartech.gatech.edu/bitstream/1853/31834/1/nichols_michael_c_200912_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Counting efficiencies were determined by empirical measurement and Monte Carlo simulation for carbon-14, strontium-89, strontium-90, and yttrium-90 standards counted by low-background gas flow proportional counter for strontium carbonate precipitates in the range from 3 to 33 mg cm⁻². The maximum beta particle energies range from 0.156 MeV for carbon-14 to 2.28 MeV for yttrium-90. The parameters for estimating the counting efficiency are summarized for sources with areal thickness of 14 mg cm⁻² and over the range in strontium carbonate areal thickness from 0.1 mg cm⁻² to 33 mg cm⁻². Uncertainty budgets providing estimates of the uncertainty, sources of variability in the calibration process, and the total expanded uncertainty are presented. Information is presented for the Monte Carlo simulation regarding the composition of the detector window, the energy excluded by the amplifier discriminator of the counting system, and the physical density of materials for this analytical process. The histogram normalization routine implemented within MCNP is described and found to bias the probability distribution for beta-particle energy spectra. The difference in the specification of the probability distribution for beta-particle energy spectra in ICRU 56 Appendix D and MCNP requirements are described and a correction for the bias introduced during the normalization process for beta spectra is provided. Counting efficiencies determined by empirical measurement and Monte Carlo simulations agree within the total expanded uncertainties of the measurements and the uncertainties of the Monte Carlo simulations.