# Nuclear Science and Techniques

《核技术》(英文版) ISSN 1001-8042 CN 31-1559/TL     2019 Impact factor 1.556

Nuclear Science and Techniques ›› 2017, Vol. 28 ›› Issue (6): 84

• NUCLEAR ELECTRONICS AND INSTRUMENTATION •

### Identification of unknown shielding layer thicknesses using an enhanced differential evolution-based inverse radiation transport model with gamma-ray spectrum

Ying Chen1, Lian-Ping Zhang1, Xue Sai2, Meng-Fu Wei1, Lun-Qiang Wu1,Jian-Min Hu1

1. 1 Institute of Materials, China Academy of Engineering Physics, Jiangyou, Mianyang 621907, China
2 Science and Technology on Surface Physics and Chemistry Laboratory, Mianyang 621908, China
• Supported by:

Supported by the CAEP foundation for Development of Science and Technology (No. 2015B0103014) and National Natural Science Foundation of China (No. 11605163).

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Ying Chen, Lian-Ping Zhang, Xue Sai, Meng-Fu Wei, Lun-Qiang Wu, Jian-Min Hu. Identification of unknown shielding layer thicknesses using an enhanced differential evolution-based inverse radiation transport model with gamma-ray spectrum.Nuclear Science and Techniques, 2017, 28(6): 84
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Abstract:

Identifying the geometric information of an object by analyzing the detected radiation fields is an important problem for national and global security. In the
present work, an inverse radiation transport model, based on the enhanced differential evolution algorithm with global and local neighborhoods (IRT-DEGL), is developed to estimate the unknown layer thickness of the source/shield system with the gamma-ray spectrum. The framework is briefly introduced with the emphasis on handling the enhanced differential evolution algorithm. Using the simulated gamma-ray spectra, the numerical precision of the IRT-DEGL model is evaluated for one-dimensional source systems. Using the detected gamma-ray spectra, the inverse investigations for the unknown thicknesses of multiple shielding layers are performed. By comparing with the traditional gamma-ray absorption method, it is shown that the IRT-EDGL model can provide a much more
accurate result and has great potential to be applied for the complicated systems.