摘要
目前,滑移隔震结构的分析通常只考虑水平地震动而不考虑竖向地震动的影响,有关多向地震动及其相关性的研究也很少。水平与竖向地面运动具有相关性,从而影响控制效果,因此对双向耦合地震作用下滑移隔震结构模型的理论进行研究,建立动力分析模型并得出运动微分方程。以6层滑移隔震结构为例,对其进行地震反应分析。研究表明,在考虑竖向地震作用的情况下,滑移隔震结构也具有良好的控制作用,但是竖向地震作用的存在使结构的地震反应有不同程度的增加,其增量随着竖向地震作用的增加而增加。因此,在高烈度地区的滑移隔震结构应该考虑竖向地震作用对结构的影响。建立滑移隔震装置的参数优化设计模型,采用IHGA程序对结构的重要参数进行优化设计。结果表明,滑移隔震结构在各种工况下的各项地震反应均得到更好的控制。
Only the action of horizontal earthquake was considered generally when the sliding base-isolated structure was analyzed currently. Few researches were done about correlation of motions in horizontal and vertical directions. Therefore, theory of sliding base-isolated structure under bidirectional coupling earthquake is studied. The theory of the model for sliding base-isolated structure under bidirectional coupling earthquake is studied. The dynamic analysis model is set up, and the kinetic differential function is presented accordingly, and the dynamic time history analysis is made. Taking 6-story sliding base-isolated structure as an example, the results show that the sliding base-isolated structure has also a good control effect when the action of earthquake in vertical direction is consid- ered. However, the seismic responses of sliding base-isolated structure increase in some degree under the action of earthquake in vertical direction. Therefore, it is highly recommended that the influence of vertical earthquake action on such structures shoulde be taken into account in high-intensity earthquake regions. The optimal model for sliding base-isolated structure is set up. The various earthquake responses of sliding base-isolated structure under various loading conditions get better control after it is optimized with IHGA.
出处
《地震工程与工程振动》
CSCD
北大核心
2007年第1期141-146,共6页
Earthquake Engineering and Engineering Dynamics
基金
国家自然科学基金项目(50508008)
建设部研究开发项目(06-k1-22)
辽宁省教育厅高等学校科研项目(2005343)
博士后科学基金项目(20060400971)
关键词
结构振动控制
滑移隔震结构
耦合地震作用
结构优化
改进遗传算法
混合遗传算法
vibration control
sliding base-isolated structure
coupling effect of earthquake
structural optimization
improved genetic algorithm
hybrid genetic algorithm