Doctoral Dissertations

Keywords and Phrases

Active Interrogation; CNR; Cross section; MCNP; NJOY; TENDL

Abstract

The Switchable Radioisotope Generator utilizes alpha-induced reactions to produce a combination of photons, neutrons, and protons with varying fluxes dependent on target materials and source geometry. The activity/strength of the secondary radiation is further controlled by manipulating the number of alpha particles that can interact with the target material(s). Analytical equations were solved to confirm secondary radiation production from target materials using average cross sections from TENDL data. TENDL and JENDL data was confirmed by analytically solving for the total alpha-induced cross sections. This information was used to produce the provisional and utility Patent No: US20190013109A1. TENDL data was then used to write cross sections within NJOY, including the ACER module. The completed cross sections were arranged in MCNP 6.1.1, such that alpha interactions may be simulated. Angular-energy dependence of secondary neutrons from 9Be(α, n)12C were chosen for simulation study, as this reaction would be validated later on experimentally due to having the highest reaction rate.

The experimental results confirmed data obtained through simulation studies with differences between the two justified. Secondary neutrons produced were coded in SDEF within MCNP 6.1.1 for neutron radiography to allow for defect detection within canister and cask materials. PGNAA was simulated in MCNP with SNM and harmful chemicals using secondary neutrons from the SRG as another application study. The SRG was then proven to detect microstructure defects in cask and canister materials and positively identify SNM and chemical agents using PGNAA”--Abstract, page iii.

Advisor(s)

Lee, Hyoung-Koo

Committee Member(s)

Alajo, Ayodeji Babatunde
Graham, Joseph T.
Liu, Xin (Mining & Nuclear Engr)
Story, J. Greg

Department(s)

Nuclear Engineering and Radiation Science

Degree Name

Ph. D. in Nuclear Engineering

Research Center/Lab(s)

Intelligent Systems Center

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2019

Pagination

xiii, 403 pages

Note about bibliography

Includes bibliographic references (pages 395-402).

Rights

© 2019 Kyle Mitchell Paaren, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12042

Electronic OCLC #

1313117364

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