多目标进化算法在等时性固定场交变梯度加速器物理设计中的应用研究

Application of Multi-objective Evolution Algorithm in Physical Design of Isochronous Fixed Field Alternating Gradient Accelerator

  • 摘要: 由于等时性固定场交变梯度加速器具有连续束、强聚焦等优点,逐渐成为研究热点。等时性固定场交变梯度加速器的物理设计问题可归结为具有多个设计目标、可调节变量与条件限制的最优化问题。多目标进化算法的发展给复杂的最优化问题提供了解决方案。将多目标进化算法应用于等时性固定场交变梯度加速器的优化中可提高设计效率。为了验证该优化方法的有效性,针对70 MeV与1 GeV等时性固定场交变梯度加速器进行了物理设计优化,并达到了预期设计目标。

     

    Abstract: Isochronous fixed field alternating gradient (FFAG) accelerator has received much attention of late years because of advantages like continues beam, and strong focusing, etc. Physical design problems in isochronism FFAG accelerator can be reduced to optimization problems with multiple targets, variables and constraints. Rapid development of multi-objective evolution algorithms (MOEAs) provide the solution to complex optimization problems. Applying MOEAs to isochronous FFAG accelerator optimization makes physical design of isochronous FFAG accelerator efficiently. To validate the effectiveness and practicability, physical design of 70 MeV and 1 GeV isochronous FFAG accelerator was optimized by MOEAs. The performance indexes are able to fulfil the design requirements.

     

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