Generative Design of Deployable Origami Structures for Space Planar Phased Array Antennas

Abstract The growing demand for deployable phased-array antennas in space applications requires innovative solutions to optimize the folded configurations and reduce the computational complexity. Existing methods face limitations due to the low efficiency of traditional algorithms and the lack of effective constraint strategies, resulting in excessive solution spaces. This study proposes forward shannon entropy wave function collapse (FSE-WFC), a novel method for designing panel configurations of one-dimensional deployable phased-array antennas using the wave function collapse algorithm. This addresses two key challenges: the excessive number of panel layout options and high computational costs. First, it analyzes the relationship between the panel connection positions and the folded form to impose constraints on the panel combinations. It then calculates the information entropy of the potential configurations to identify low-entropy solutions, thereby narrowing the solution space. Finally, boundary constraints and interference check were applied to refine the results. This approach significantly reduced the calculation time while improving the folding state and envelope volume of the antenna. The results show that the FSE-WFC algorithm reduces the envelope area by 18.3% for a 350 mm high satellite and 9.0% for a 600 mm high satellite, while satisfying the connectivity constraints. As the first application of the wave-function collapse algorithm to antenna folding design, this study introduces an information entropy-based constraint generation method that provides an efficient solution for deployable antenna optimization.