The research team (NEAL) from the University of South China have made significant progress in nuclear reactor radiation-shielding design. The team has developed a radiation-shielding optimization method (RP-NSGA and RP-MOABC) based on a reference-point-selection strategy, which efficiently solves many-objective optimization problems in radiation-shielding design. This achievement provides an innovative solution for the shielding design of new types of nuclear reactors, and the related research has been published in the journal Nuclear Science and Techniques .
Efficient Algorithms to Address the Complex Design Challenges of Radiation-Shielding
Conventional radiation-shielding design methods rely on expert experience, making it difficult to meet the multiple demands for lightweight, compact, and efficient radiation protection in new types of nuclear reactors, such as transportable, marine, and space reactors. The RP-NSGA and RP-MOABC algorithms proposed by the research team significantly enhance optimization performance by integrating the reference point selection strategy with genetic algorithms and artificial bee colony algorithms, respectively.
“The algorithms can automatically identify optimal shielding solutions under multiple objectives and constraints, greatly reducing design complexity,” said Prof. Zhen-Ping Chen, the corresponding author of the paper. “This provides crucial technical support for the conceptual design phase of nuclear reactors, especially for the new types of reactors lacking of engineering experience.”
Remarkable Optimization Results
The team validated the algorithm’s effectiveness through two numerical experiments:
Simple 3D Shielding Structure Optimization: Compared with the conventional crowding-distance strategy, the average volume and weight values for the shielding schemes in the final generation of RP-NSGA are only 24.5% and 14.5% of those of CD-NSGA, and the average volume and weight values of RP-MOABC are only 17.3% and 9.77% of those of CD-MOABC.
Complex Shielding Structure Optimization: The algorithm successfully optimized multi-layer, multi-material shielding, achieving 19.12% volume reduction and 24.50% weight reduction while meeting strict radiation dose constraints.
Broad Application Prospects
The algorithms are not only applicable to nuclear reactor shielding design but can also be extended to other engineering fields that require multi-objective optimization, such as reactor core design, shielding material design, and medical radiation protection. The research team has integrated the algorithms into their self-developed MOSRT software platform, providing an efficient tool for engineering design.
Future Directions
The team plans to further refine the algorithm’s performance and apply it to real-world engineering challenges, driving innovation developments in nuclear technology. The complete study is accessible via DOI: 10.1007/s41365-025-01683-7.
Nuclear Science and Techniques
Computational simulation/modeling
Not applicable
Many-objective evolutionary algorithms based on reference-point-selection strategy for application in reactor radiation-shielding design
22-Apr-2025