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Ge Y, Zhong Y, Murata I, Tamaki S, Yuan N, Sun Y, Ma W, Zou L, Yang Z, Lu L. Efficient optimization of an accelerator neutron source for neutron capture therapy using genetic algorithms. Med Phys 2024; 51:6445-6457. [PMID: 38734991 DOI: 10.1002/mp.17132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 04/19/2024] [Accepted: 05/04/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND In recent years, genetic algorithms have been applied in the field of nuclear technology design, producing superior optimization results compared to traditional methods. They can be employed in the design and optimization of beam shaping assemblies (BSA) BSA to obtain the desired neutron beams. But it should be noted that the direct combination of Monte Carlo methods with genetic algorithms requires a significant amount of computational resources and time. PURPOSE Design and optimize BSA more efficiently to achieve neutron beams that meet specified recommendations. METHODS We propose an approach of NSGA II with crucial variables which are identified by multivariate statistical techniques. This approach significantly reduces the problem sizes, thus reducing the time required for optimization. We illustrate this methodology using the example of BSA design for AB-BNCT. RESULTS The computational efficiency has tripled with crucial variables. By using NSGA II, we obtained optimized models conforming to both the new and old version IAEA BNCT guidelines through a single optimization process and subjected them to phantom analysis. The results demonstrate that models obtained through this method can meet the IAEA recommendations with deep advantage depth (AD) and high absorbed ratio (AR). CONCLUSION The genetic algorithm with crucial variables displays tremendous potential in addressing BSA optimization challenges.
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Affiliation(s)
- Yulin Ge
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
- Department of Sustainable Energy and Environmental Engineering, School of Engineering, Osaka University, Suita, Osaka, Japan
- United Laboratory of Frontier Radiotherapy Technology of Sun Yat-sen University & Chinese Academy of Sciences Ion Medical Technology Co., Ltd, Guangzhou, China
| | - Yao Zhong
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
- Institute of Advanced Energy, Kyoto University, Uji, Kyoto, Japan
| | - Isao Murata
- Department of Sustainable Energy and Environmental Engineering, School of Engineering, Osaka University, Suita, Osaka, Japan
| | - Shingo Tamaki
- Department of Sustainable Energy and Environmental Engineering, School of Engineering, Osaka University, Suita, Osaka, Japan
| | - Nan Yuan
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Yanbing Sun
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Wei Ma
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Liping Zou
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Zhen Yang
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Liang Lu
- Sino-French Institute of Nuclear Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, China
- United Laboratory of Frontier Radiotherapy Technology of Sun Yat-sen University & Chinese Academy of Sciences Ion Medical Technology Co., Ltd, Guangzhou, China
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Optimization of double layered beam shaping assembly using genetic algorithm. POLISH JOURNAL OF MEDICAL PHYSICS AND ENGINEERING 2018. [DOI: 10.2478/pjmpe-2018-0022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Abstract
The genetic algorithm method is a new method used to obtain radiation beams that meet the IAEA requirements. This method is used in optimization of configurations and compositions of materials that compose double layered Beam Shaping Assembly (BSA). The double layered BSA is modeled as having two layers of material for each of the components, which are the moderator, reflector, collimator, and filter. Up to 21st generation, the optimization results in four (4) individuals having the capacity to generate the most optimum radiation beams. The best configuration, producing the most optimum radiation beams, is attained by using combinations of materials, that is by combining Al with either one of CaF2 and PbF2for moderator; combining Pb material with either Ni or Pb for reflector; combining Ni and either FeC or C for collimator, and FeC+LiF and Cd for fast and thermal neutron filter. The parameters of radiation resulted from the four configurations of double layer BSA adequately satisfy the standard of the IAEA.
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