| 论文简介 |
Abstract
The traditional methods for radiation shield design always only focus on either the structure or the components of the shields rather than both of them at the same time, which largely affects the shielding performance of the facilities, so in this paper, a novel method for designing the structure and components of shields simultaneously is put forward to enhance the shielding ability. The method is developed by using the genetic algorithm (GA) and the MCNP software. In the research, six types of shielding materials with different combinations of elements such as polyethylene (PE), lead (Pb) and Boron compounds are applied to the radiation shield design, and the performance of each material is analyzed and compared. Then two typical materials are selected based on the experiment result of the six samples, which are later verified by the Compact Accelerator Neutron Source (CANS) facility. By using this method, the optimal result can be reached rapidly, and since the design progress is semi-automatic for most procedures are completed by computer, the method saves time and improves accuracy.
Keywords
Optimal design,Radiation shielding,Mixed neutrons and γ-rays,StructureComponent
a
Xi'an Jiaotong University, Xi'an, 710049, China
b
State Key Laboratory of Light Alloy Foundry Technology for High-end Equipment Shenyang Research Institute of Foundry Co. Ltd, Shenyang, 110022, China
Received 23 January 2019, Revised 11 July 2019, Accepted 15 July 2019, Available online 16 July 2019.
This research is supported by the NSAF Joint Fund set up by the National Natural Science Foundation of China and the Chinese Academy of Engineering Physics under Grant (U1830128), State Key Laboratory of Light Alloy Foundry Technology for High-end Equipment (No. LACT-001), Postdoctoral Science Foundation of China (2018M633521), Nature Science foundation of Liaoning Province of China (No. 20180550876) and International Project for Associates (IPA) of Riken in Japan. Many thanks go to the members of the neutron beam team in Riken for assistance with the simulation and the experiment.
https://doi.org/10.1016/j.net.2019.07.016 |
(创新港)
