摘要
在大气边界层风洞中开展了大跨平屋盖结构刚性模型试验,获得了屋盖表面测点的风压时程,分析了典型风向下屋盖表面平均风压与脉动风压特性。结合本征正交分解技术(POD)与BP神经网络法,提出了一种可用于大跨结构进行空间插值的机器学习法—POD-BPNN法,实现了对风压的高效预测。预测的平均风压系数、脉动风压系数、脉动风压的时域与频域特性均与风洞试验值相吻合。表明运用POD-BPNN方法预测大跨结构表面风压是可行的。
Here,rigid model tests of a long-span flat roof structure were conducted in an atmospheric boundary layer wind tunnel.The wind pressure time histories of measured points on the roof surface were obtained,and characteristics of mean wind pressure and fluctuating wind pressure on the roof surface in typical wind direction were analyzed.Combining the proper orthogonal decomposition(POD)technique and BP neural network method,a machine learning method-—POD-BPNN method for spatial interpolation of long-span structures was proposed to realize the high-efficiency prediction of wind pressure.The predicted mean wind pressure coefficient,fluctuating wind pressure coefficient and fluctuating wind pressure characteristics in time domain and frequency domain were consistent with wind tunnel test values.The results showed that using the proposed POD-BPNN method to predict wind pressure on surface of long-span structure is feasible.
作者
陈伏彬
唐宾芳
蔡虬瑞
李秋胜
CHEN Fubin;TANG Binfang;CAI Qiurui;LI Qiusheng(School of Civil Engineering,Changsha University of Science&Technology,Changsha 410114,China;Hunan Electric Power Design Institute Co,Ltd,China Energy Source Construction Group,Changsha 410007,China;Department of Architecture and Civil Engineering,City University of Hong Kong,Hong Kong 999077,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2021年第3期226-232,共7页
Journal of Vibration and Shock
基金
国家自然科学基金(51778072,51408062)
湖南省研究生科研创新项目(CX2018B545)。
关键词
大跨平屋盖
平均风压
脉动风压
本征正交分解法
BP神经网络
long-span flat roof
mean wind pressure
fluctuating wind pressure
proper orthogonal decomposition(POD)
BP neutral network(BPNN)
