摘要
试验分析了5种不同高度比情况下3个任意排列高层建筑间横风向基底弯矩响应的动力干扰效应,结果显示2个施扰建筑的协同作用会产生远高于单个施扰建筑的干扰效应.对3个建筑物间的包络干扰因子(FEI)分布提出了有效的简化表示方法,解决了三建筑物间干扰效应难以表示的难点.采用神经网络、统计方法对不同参数配置的FEI分布进行了分析,发现不同高度比配置以及不同地面粗糙度类别下的FEI分布存在较为明显的相关特征,并由此得到了可以反映不同参数对FEI分布影响的定量关系,大大简化了考虑多参数干扰效应所得结果的繁杂程度,使结构受扰后的荷载估计计算更趋于简洁合理.
Crosswind dynamic response of the grouped high-rise buildings was studied by a series of wind tunnel tests. Interference excitations of upwind buildings with various heights in different upwind terrains were considered. An effective method was proposed to represent the distribution of the envelope interference factor (EIF) of the interference effects among three tall buildings. The interference characteristics were analyzed by the artificial neural networks and the correlation analysis. The results show that two upstream buildings cause more adverse dynamic effects on the downstream building than a single upstream building does. Inherent correlations are found in the distributions of the EIFs of different configurations and upwind terrains, and therefore, relevant regression equations can simplify the complexity of the multi-parameter wind induced interference effects among the three buildings.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2004年第9期967-970,988,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金重点资助项目(5989541 0 )
教育部高等学校博士学科点专项科研基金资助项目
广东省自然科学基金资助项目 (0 1 0 455)
关键词
高层建筑
风洞试验
横风向响应
风荷载
干扰因子
Correlation methods
Dynamic response
Neural networks
Wind effects
Wind stress
Wind tunnels
