Design and Optimization of Focusing X-Ray Telescope Based on Intelligent Algorithm

Abstract

Focusing X-ray telescope (FoXT) is widely used in space science detection, pulsar navigation and timing, space X-ray communication, etc. In order to improve the performance and reduce the weight of FoXT, this paper proposes a FoXT design and optimization method based on intelligent algorithm. Firstly, based on the X-ray total reflection theory, a multi-objective optimization model with maximum effective area and light weight is formulated. The Pareto non-inferior solution set of the product is obtained using the non-dominated sorting genetic algorithm (NSGA-II). With data mining methods such as cluster analysis and association analysis, the implicit correlation characteristics and variation rules between design parameters and optimized solution sets are studied. The influence of parameters such as X-ray optic length, optical aperture and nested layer on effective area is revealed. The distribution of focal length and optical aperture ratio, effective collection area and weight ratio are implemented with statistical analysis. Finally, five sets of design optimization solutions are selected according to practical engineering development capability and cost, which provides theoretical basis for design and optimization of FoXT.