Given the increasing need for large aperture antennas in space missions, the difficulty of fitting such structures into small launch vehicles has prompted the design of deployable antenna systems. The thesis introduces a new Triple Scissors Deployable Truss Mechanism (TSDTM) for space antenna missions. The new mechanism is to be stowed during launch and efficiently deploy in orbit, offering maximum aperture size while taking up minimal launch volume. The thesis covers the entire design process from geometric modeling, kinematic analysis with screw theory and Newtonian approaches, dynamic analysis by eigenvalue and simulation methods, and verification with SolidWorks. In addition, optimization routines were coded based on Support Vector Machines for material choice in LEO environments and machine learning method for geometric setup. The TSDTM presented has enhanced structural dynamics with good comparison between simulation and analytical predictions. The structure optimized proved highly accurate, with a deviation of just 1.94% between machine learning-predicted and simulated natural frequencies, demonstrating the potential of incorporating AI-based methods in space structural design.
翻译:鉴于空间任务对大口径天线的需求日益增长,而此类结构难以装入小型运载火箭,这促使了可展开天线系统的设计。本文介绍了一种用于空间天线任务的新型三重剪叉式可展开桁架机构(TSDTM)。该新机构在发射期间可收拢,在轨道上高效展开,在占用最小发射体积的同时提供最大孔径尺寸。论文涵盖了从几何建模、基于旋量理论和牛顿方法的运动学分析、通过特征值和仿真方法进行的动力学分析,到使用SolidWorks进行验证的完整设计过程。此外,还基于支持向量机编写了优化程序,用于低地球轨道环境下的材料选择,并应用机器学习方法进行几何配置优化。所提出的TSDTM增强了结构动力学性能,仿真结果与解析预测之间具有良好的一致性。优化后的结构展现出高度准确性,机器学习预测的固有频率与仿真结果之间的偏差仅为1.94%,这证明了将基于人工智能的方法融入空间结构设计的潜力。