X-Ray and Neutron Radiography System Optimization by Means of a Multiobjective Approach and a Simplified Ray-Tracing Method-Reference-Cited by-同舟云学术

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X-Ray and Neutron Radiography System Optimization by Means of a Multiobjective Approach and a Simplified Ray-Tracing Method

Published:2020-05-30 Issue:1 Volume:207 Page:147-166
ISSN:0029-5450
Container-title:Nuclear Technology
language:en
Short-container-title:Nuclear Technology

Author:

Nshimirimana Robert¹²^ORCID,Abraham Ajith³^ORCID,Nothnagel Gawie²,Engelbrecht Andries⁴^ORCID

Affiliation:

1. University of Pretoria, Department of Computer Science, Pretoria, South Africa

2. South African Nuclear Energy Corporation SOC Ltd., Radiation Science Department, Brits Magisterial District, South Africa

3. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn, Washington

4. University of Stellenbosch, Department of Industrial Engineering, Stellenbosch, South Africa

Publisher

Informa UK Limited

Subject

Condensed Matter Physics,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

https://www.tandfonline.com/doi/pdf/10.1080/00295450.2020.1740562

Reference86 articles.

1. Design and simulation of neutron radiography system based on 241Am–Be source

2. Computed radiography simulation using the Monte Carlo code MCNPX

3. Methodology for digital radiography simulation using the Monte Carlo code MCNPX for industrial applications

4. Development of a simulator for radiographic image optimization

5. Virtual X-ray imaging techniques in an immersive casting simulation environment

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Iterative reconstruction algorithms in neutron tomography imaging;Journal of Optics;2024-05-18

2. Ageing management of research reactors instrumentation using neutron radiography applications;Alexandria Engineering Journal;2022-04

3. Parametric Study for the Design of a Neutron Radiography Camera-Based Detector System;Advances in Science, Technology and Engineering Systems Journal;2021-05

4. A multi-objective particle swarm for constraint and unconstrained problems;Neural Computing and Applications;2021-01-19

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