张拉整体高耸结构优化研究

Structural optimization of tensegrity tower structures

张拉整体高耸结构是一种新型结构体系,是张拉整体在竖直方向上的应用,目前尚未有功能性结构建成。针对一座电视塔的张拉整体高耸结构,采用改进的遗传算法和三级混合算法,依靠有限元分析对结构进行了优化设计。改进的遗传算法能够识别迭代过程中松弛的索,通过自动调整对应编码区的变异率来避免索的松弛,采用非线性求解器对结构的侧向刚度进行优化;三级混合算法包含了模式搜索法、单纯形法和齿行法,采用线性求解器对结构的侧向刚度和自重进行了联合优化,提高侧向刚度的同时减小自重。优化结果表明：这两种优化算法都能够在预应力水平基本不变的情况下大幅提高结构侧向刚度,优化效果良好。

Tensegrity tower structures are new structural form and the application of tensegrity in vertical direction. Up till now, no functional tensegrity tower structure has ever been built. A seven-stage tensegrity tower structure was designed and two different algorithms, including a modified genetic algorithm and a three-level hybrid algorithm, were adopted to optimize the structure by using finite-element analysis. The modified genetic algorithm was able to locate slack cables, automatically change their mutation rate in order to prevent slack cables, and optimize the lateral stiffness by using nonlinear solver. The three-level hybrid algorithm consisted of pattern search method, linear programming and full stress method, using linear solver to optimize the structure＇ s shape, prestress distribution and cross-section areas, aimed to improving the structure＇s lateral stiffness while decreasing its self-weight. Results show that the structure＇ s lateral stiffness increases considerably after adopting these two algorithms, so it can be concluded that the optimization is effective.