兰州理工大学学报 ›› 2022, Vol. 48 ›› Issue (3): 125-132.

• 建筑科学 • 上一篇    下一篇

隔震结构支座布置的两阶段优化方法

党育*, 赵根兄, 田宏图   

  1. 兰州理工大学 土木工程学院, 甘肃 兰州 730050
  • 收稿日期:2020-04-09 出版日期:2022-06-28 发布日期:2022-10-09
  • 通讯作者: 党育(1976-),女,甘肃正宁人,博士,教授.Email:601363791@qq.com
  • 基金资助:
    国家自然科学基金(51668043)

Two-stage optimization method for bearing layout of isolated structures

DANG Yu, ZHAO Gen-xiong, TIAN Hong-tu   

  1. School of Civil Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China
  • Received:2020-04-09 Online:2022-06-28 Published:2022-10-09

摘要: 针对隔震结构隔震支座布置最优问题,提出一种两阶段的隔震支座布置优化方法:先采用多种群遗传算法进行隔震层参数优化,再采用线性规划法完成隔震支座布置优化.整个过程需要优化算法和动力分析相结合,采用SAP2000 API函数库与MATLAB,实现隔震结构动力时程分析与优化程序的相互调用.用一个实际隔震工程分析表明:与原设计方案相比,采用本方法确定的隔震支座布置方案,水平向减震系数可减小约12%,各支座最大位移减小约21%,隔震层造价增加约14%,说明该方法优化结果可靠,可有效提高隔震工程的设计质量和设计效率.

关键词: 隔震结构, 优化, SAP2000 API, 多种群遗传算法, 线性规划法

Abstract: A two-stage optimization method is proposed to determine the optimum layout of isolation bearings. In the first stage, genetic optimization is performed to identify the parameters of the isolated layer. In the second stage, a linear programming method is adopted to optimize the layout of isolators. This study constructs a hybrid framework in which the nonlinear time history analyses are conducted using the software SAP2000 and the optimization is accomplished by MATLAB. The former provides the responses of isolated buildings, and the latter calculates the associated objective function and identifies the optimal design. The proposed method is demonstrated in a typical isolated building in China. Compared with the original design scheme, the horizontal damping coefficient of the isolation bearing arrangement scheme determined by this method can be reduced by about 12%, the maximum displacement of bearing can be reduced by about 21%, and the cost of the isolation layer can be increased by about 14%. It shows that the optimization result of this method is reliable and can effectively improve the design quality and efficiency of isolation engineering.

Key words: isolated structure, optimization, SAP2000 API, multiple population genetic algorithm, linear programming method

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