Deterministic Simulation of Thermal Neutron Radiography and Tomography
In recent years, thermal neutron radiography and tomography have gained much attention as one of the nondestructive testing methods. However, the application of thermal neutron radiography and tomography is hindered by their technical complexity, radiation shielding, and time-consuming data collection processes. Monte Carlo simulations have been developed in the past to improve the neutron imaging facility's ability. In this paper, a new deterministic simulation approach has been proposed and demonstrated to simulate neutron radiographs numerically using a ray tracing algorithm. This approach has made the simulation of neutron radiographs much faster than by previously used stochastic methods (i.e., Monte Carlo methods). The major problem with neutron radiography and tomography simulation is finding a suitable scatter model. In this paper, an analytic scatter model has been proposed that is validated by a Monte Carlo simulation.
R. Pal Chowdhury and X. Liu, "Deterministic Simulation of Thermal Neutron Radiography and Tomography," Radiation Physics and Chemistry, vol. 122, pp. 100-107, Elsevier, May 2016.
The definitive version is available at https://doi.org/10.1016/j.radphyschem.2016.01.036
Nuclear Engineering and Radiation Science
Keywords and Phrases
Intelligent systems; Neutron radiography and tomography; Neutrons; Nondestructive examination; Radiation shielding; Radiography; Ray tracing; Scattering; Stochastic systems; Testing; Tomography; Data collection process; Deterministic simulation; Noise; Nondestructive testing method; Ray-tracing algorithm; Stochastic methods; Technical complexity; Thermal neutron radiography; Monte Carlo methods; Article; Deterministic simulation; Kernel method; Mathematical computing; Monte Carlo method; Neutron radiation; Neutron scattering; Noise reduction; Radiation detection; Simulation; Stochastic model; Scatter
International Standard Serial Number (ISSN)
Article - Journal
© 2016 Elsevier, All rights reserved.
01 May 2016