型钢高强混凝土框架柱位移延性系数研究
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摘要
基于80根混凝土设计强度等级为C60—C80的型钢高强混凝土(SRHSC)框架柱的低周反复加载试验结果,对其位移延性系数进行研究。基于MATLAB利用人工神经网络原理建立4-6-1型BP神经网络模型,分析了混凝土强度、轴压比、体积配箍率和剪跨比等试验设计参数对SRHSC框架柱位移延性的影响规律和机理。结合各因素对SRHSC框架柱位移延性的影响规律,建立位移延性系数计算模型。通过对试验数据和网络预测数据进行多元非线性回归分析,得到考虑多影响因素的SRHSC框架柱位移延性系数经验公式。研究成果可为SRHSC框架柱的抗震与优化设计提供参考。
The displacement ductility factor of SRHSC frame columns was studied by the experimental results of 80C60—C80 column specimens subjected to a constant axial load and cyclic lateral loads. A 4-6-1 BP neural network model was built by using artificial neural network theory based on MATLAB. Furthermore,the influence law and influence mechanism of concrete strength,axial compression ratio,stirrup ratio,shear span ratio on the displacement ductility were investigated by the BP neural network model. The displacement ductility factor calculation model was built based on the influence law of every influencing factor on the displacement ductility. The displacement ductility factor empirical formula considering multiple influencing factors was proposed through multi-variant nonlinear regression analysis on the experimental data and network predicted data,which provided reference for seismic and optimal design for SRHSC frame columns.
The displacement ductility factor of SRHSC frame columns was studied by the experimental results of 80C60—C80 column specimens subjected to a constant axial load and cyclic lateral loads. A 4-6-1 BP neural network model was built by using artificial neural network theory based on MATLAB. Furthermore,the influence law and influence mechanism of concrete strength,axial compression ratio,stirrup ratio,shear span ratio on the displacement ductility were investigated by the BP neural network model. The displacement ductility factor calculation model was built based on the influence law of every influencing factor on the displacement ductility. The displacement ductility factor empirical formula considering multiple influencing factors was proposed through multi-variant nonlinear regression analysis on the experimental data and network predicted data,which provided reference for seismic and optimal design for SRHSC frame columns.
引文
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[5]贾金青,许世烺.钢骨高强混凝土短柱轴压力系数限值的试验研究[J].建筑结构学报,2003,24(1):14-18.
[6]蒋东红,王连广,刘之洋.高强钢骨混凝土框架柱的抗震性能[J].东北大学学报,2002,23(1):67-70.
[7]李俊华,赵鸿铁,薛建阳,等.型钢高强混凝土柱延性的试验研究[J].西安建筑科技大学学报:自然科学版,2004,36(4):383-387.
[8]李俊华,薛建阳,王新堂,等.型钢高强混凝土柱轴压比限值的试验研究[J].世界地震工程,2007,23(2):154-160.
[9]张德丰.MATLAB神经网络应用设计[M].北京:机械工业出版社,2009.
[2]叶列平,方鄂华.钢骨混凝土柱的轴压比限值[J].建筑结构学报,1997,18(5):43-50.
[3]贾金青,孙洪梅,李大永.钢骨高强混凝土短柱轴压力系数限值[J].大连理工大学学报,2002,42(2):218-222.
[4]贾金青,关萍,王建胜.低周反复荷载作用下SRHC短柱延性的试验研究[J].工业建筑,2002,32(9):18-26.
[5]贾金青,许世烺.钢骨高强混凝土短柱轴压力系数限值的试验研究[J].建筑结构学报,2003,24(1):14-18.
[6]蒋东红,王连广,刘之洋.高强钢骨混凝土框架柱的抗震性能[J].东北大学学报,2002,23(1):67-70.
[7]李俊华,赵鸿铁,薛建阳,等.型钢高强混凝土柱延性的试验研究[J].西安建筑科技大学学报:自然科学版,2004,36(4):383-387.
[8]李俊华,薛建阳,王新堂,等.型钢高强混凝土柱轴压比限值的试验研究[J].世界地震工程,2007,23(2):154-160.
[9]张德丰.MATLAB神经网络应用设计[M].北京:机械工业出版社,2009.
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